diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 809c350d4..29d1f973c 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -76,7 +76,7 @@ jobs:
       #    install your root project, if required
       #----------------------------------------------
       - name: Install library
-        run: poetry install --no-interaction
+        run: poetry install --no-interaction --all-extras
 
       #----------------------------------------------
       #             perform linting
@@ -96,7 +96,7 @@ jobs:
         run: |
           # ran only on certain files for now
           # add here when checked
-          poetry run black schematic/configuration/*.py schematic/exceptions.py schematic/help.py schematic/loader.py schematic/version.py --check
+          poetry run black schematic --check
 
       #----------------------------------------------
       #             type checking/enforcement
@@ -116,29 +116,23 @@ jobs:
         run: |
           # ran only on certain files for now
           # add here when checked
-          poetry run pylint schematic/configuration/*.py schematic/exceptions.py schematic/help.py schematic/loader.py schematic/version.py
+          poetry run pylint schematic/visualization/* schematic/configuration/*.py schematic/exceptions.py schematic/help.py schematic/loader.py schematic/version.py
+          # do all utils but schema_utils.py
+          poetry run pylint schematic/utils/cli_utils.py schematic/utils/curie_utils.py schematic/utils/df_utils.py
+          poetry run pylint schematic/utils/general.py schematic/utils/google_api_utils.py schematic/utils/io_utils.py
+          poetry run pylint schematic/utils/validate_rules_utils.py schematic/utils/validate_utils.py schematic/utils/viz_utils.py
 
       #----------------------------------------------
       #              run test suite
       #----------------------------------------------
-      - name: Run regular tests and rule combination tests
-        env:
-          SYNAPSE_ACCESS_TOKEN: ${{ secrets.SYNAPSE_ACCESS_TOKEN }}
-        if: ${{ contains(github.event.head_commit.message, 'runcombos') }}
-        run: >
-          source .venv/bin/activate;
-          pytest --durations=0 --cov-report=term --cov-report=html:htmlcov --cov=schematic/
-          -m "not (google_credentials_needed or schematic_api or table_operations)" --reruns 2 -n auto
-
       - name: Run tests
         env:
           SYNAPSE_ACCESS_TOKEN: ${{ secrets.SYNAPSE_ACCESS_TOKEN }}
           SERVICE_ACCOUNT_CREDS: ${{ secrets.SERVICE_ACCOUNT_CREDS }}
-        if: ${{ false == contains(github.event.head_commit.message, 'runcombos') }}
         run: >
           source .venv/bin/activate;
           pytest --durations=0 --cov-report=term --cov-report=html:htmlcov --cov=schematic/
-          -m "not (google_credentials_needed or rule_combos or schematic_api or table_operations)" --reruns 2  -n auto
+          -m "not (google_credentials_needed or schematic_api or table_operations)" --reruns 2 -n auto
 
       - name: Upload pytest test results
         uses: actions/upload-artifact@v2
diff --git a/.readthedocs.yaml b/.readthedocs.yaml
deleted file mode 100644
index 69f40ffe5..000000000
--- a/.readthedocs.yaml
+++ /dev/null
@@ -1,19 +0,0 @@
-# .readthedocs.yaml
-# Read the Docs configuration file
-# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
-
-# Required
-version: 2
-
-# Build documentation in the docs/ directory with Sphinx
-sphinx:
-  configuration: docs/conf.py
-
-# Optionally set the version of Python and requirements required to build your docs
-python:
-  version: 3.7
-  install:
-    - requirements: docs/requirements.txt
-    - method: pip
-      path: .
-  system_packages: false
\ No newline at end of file
diff --git a/.readthedocs.yml b/.readthedocs.yml
index 6599ad15f..a9472a17d 100644
--- a/.readthedocs.yml
+++ b/.readthedocs.yml
@@ -12,7 +12,7 @@ build:
     python: "3.9"
   jobs:
     post_install:
-      - pip install poetry==1.2.0
+      - pip install poetry==1.3.0
       - poetry config virtualenvs.create false
       - poetry install --with doc
     #Poetry will install my dependencies into the virtualenv created by readthedocs if I set virtualenvs.create=false
diff --git a/README.md b/README.md
index 7d3890de8..dd7263940 100644
--- a/README.md
+++ b/README.md
@@ -71,6 +71,18 @@ poetry install
 ```
 This command will install the dependencies based on what we specify in poetry.lock. If this step is taking a long time, try to go back to step 2 and check your version of poetry. Alternatively, you could also try deleting the lock file and regenerate it by doing `poetry install` (Please note this method should be used as a last resort because this would force other developers to change their development environment)
 
+If you want to install the API you will need to install those dependencies as well:
+
+```
+poetry install --extras "api"
+```
+
+If you want to install the uwsgi:
+
+```
+poetry install --extras "api"
+```
+
 5. Fill in credential files: 
 *Note*: If you won't interact with Synapse, please ignore this section.
 
diff --git a/certificate.conf b/certificate.conf
index eb5bf94d9..a61e8af82 100644
--- a/certificate.conf
+++ b/certificate.conf
@@ -7,6 +7,8 @@ server {
     proxy_read_timeout 300;
     proxy_connect_timeout 300;
     proxy_send_timeout 300;
+    send_timeout 300;
+    uwsgi_read_timeout 300;
     location / {
         try_files $uri @app;
     }
diff --git a/poetry.lock b/poetry.lock
index 746ce0027..5673df9a4 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2,21 +2,19 @@
 
 [[package]]
 name = "alabaster"
-version = "0.7.13"
-description = "A configurable sidebar-enabled Sphinx theme"
-category = "main"
+version = "0.7.16"
+description = "A light, configurable Sphinx theme"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.9"
 files = [
-    {file = "alabaster-0.7.13-py3-none-any.whl", hash = "sha256:1ee19aca801bbabb5ba3f5f258e4422dfa86f82f3e9cefb0859b283cdd7f62a3"},
-    {file = "alabaster-0.7.13.tar.gz", hash = "sha256:a27a4a084d5e690e16e01e03ad2b2e552c61a65469419b907243193de1a84ae2"},
+    {file = "alabaster-0.7.16-py3-none-any.whl", hash = "sha256:b46733c07dce03ae4e150330b975c75737fa60f0a7c591b6c8bf4928a28e2c92"},
+    {file = "alabaster-0.7.16.tar.gz", hash = "sha256:75a8b99c28a5dad50dd7f8ccdd447a121ddb3892da9e53d1ca5cca3106d58d65"},
 ]
 
 [[package]]
 name = "altair"
 version = "4.2.0"
 description = "Altair: A declarative statistical visualization library for Python."
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -37,20 +35,20 @@ dev = ["black", "docutils", "flake8", "ipython", "m2r", "mistune (<2.0.0)", "pyt
 
 [[package]]
 name = "anyio"
-version = "4.1.0"
+version = "4.2.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "anyio-4.1.0-py3-none-any.whl", hash = "sha256:56a415fbc462291813a94528a779597226619c8e78af7de0507333f700011e5f"},
-    {file = "anyio-4.1.0.tar.gz", hash = "sha256:5a0bec7085176715be77df87fc66d6c9d70626bd752fcc85f57cdbee5b3760da"},
+    {file = "anyio-4.2.0-py3-none-any.whl", hash = "sha256:745843b39e829e108e518c489b31dc757de7d2131d53fac32bd8df268227bfee"},
+    {file = "anyio-4.2.0.tar.gz", hash = "sha256:e1875bb4b4e2de1669f4bc7869b6d3f54231cdced71605e6e64c9be77e3be50f"},
 ]
 
 [package.dependencies]
 exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
 idna = ">=2.8"
 sniffio = ">=1.1"
+typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
 doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
@@ -59,21 +57,19 @@ trio = ["trio (>=0.23)"]
 
 [[package]]
 name = "appnope"
-version = "0.1.3"
+version = "0.1.4"
 description = "Disable App Nap on macOS >= 10.9"
-category = "main"
 optional = false
-python-versions = "*"
+python-versions = ">=3.6"
 files = [
-    {file = "appnope-0.1.3-py2.py3-none-any.whl", hash = "sha256:265a455292d0bd8a72453494fa24df5a11eb18373a60c7c0430889f22548605e"},
-    {file = "appnope-0.1.3.tar.gz", hash = "sha256:02bd91c4de869fbb1e1c50aafc4098827a7a54ab2f39d9dcba6c9547ed920e24"},
+    {file = "appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c"},
+    {file = "appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee"},
 ]
 
 [[package]]
 name = "argon2-cffi"
 version = "23.1.0"
 description = "Argon2 for Python"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -94,7 +90,6 @@ typing = ["mypy"]
 name = "argon2-cffi-bindings"
 version = "21.2.0"
 description = "Low-level CFFI bindings for Argon2"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -132,7 +127,6 @@ tests = ["pytest"]
 name = "arrow"
 version = "1.3.0"
 description = "Better dates & times for Python"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -146,13 +140,12 @@ types-python-dateutil = ">=2.8.10"
 
 [package.extras]
 doc = ["doc8", "sphinx (>=7.0.0)", "sphinx-autobuild", "sphinx-autodoc-typehints", "sphinx_rtd_theme (>=1.3.0)"]
-test = ["dateparser (>=1.0.0,<2.0.0)", "pre-commit", "pytest", "pytest-cov", "pytest-mock", "pytz (==2021.1)", "simplejson (>=3.0.0,<4.0.0)"]
+test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock", "pytz (==2021.1)", "simplejson (==3.*)"]
 
 [[package]]
 name = "astroid"
 version = "2.15.8"
 description = "An abstract syntax tree for Python with inference support."
-category = "dev"
 optional = false
 python-versions = ">=3.7.2"
 files = [
@@ -169,7 +162,6 @@ wrapt = {version = ">=1.11,<2", markers = "python_version < \"3.11\""}
 name = "asttokens"
 version = "2.4.1"
 description = "Annotate AST trees with source code positions"
-category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -188,7 +180,6 @@ test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
 name = "async-lru"
 version = "2.0.4"
 description = "Simple LRU cache for asyncio"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -201,33 +192,32 @@ typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""}
 
 [[package]]
 name = "attrs"
-version = "23.1.0"
+version = "23.2.0"
 description = "Classes Without Boilerplate"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"},
-    {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"},
+    {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"},
+    {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"},
 ]
 
 [package.extras]
 cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
-dev = ["attrs[docs,tests]", "pre-commit"]
+dev = ["attrs[tests]", "pre-commit"]
 docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
 tests = ["attrs[tests-no-zope]", "zope-interface"]
-tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
+tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
 
 [[package]]
 name = "babel"
-version = "2.13.1"
+version = "2.14.0"
 description = "Internationalization utilities"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "Babel-2.13.1-py3-none-any.whl", hash = "sha256:7077a4984b02b6727ac10f1f7294484f737443d7e2e66c5e4380e41a3ae0b4ed"},
-    {file = "Babel-2.13.1.tar.gz", hash = "sha256:33e0952d7dd6374af8dbf6768cc4ddf3ccfefc244f9986d4074704f2fbd18900"},
+    {file = "Babel-2.14.0-py3-none-any.whl", hash = "sha256:efb1a25b7118e67ce3a259bed20545c29cb68be8ad2c784c83689981b7a57287"},
+    {file = "Babel-2.14.0.tar.gz", hash = "sha256:6919867db036398ba21eb5c7a0f6b28ab8cbc3ae7a73a44ebe34ae74a4e7d363"},
 ]
 
 [package.extras]
@@ -246,49 +236,54 @@ files = [
 
 [[package]]
 name = "beautifulsoup4"
-version = "4.12.2"
+version = "4.12.3"
 description = "Screen-scraping library"
-category = "main"
 optional = false
 python-versions = ">=3.6.0"
 files = [
-    {file = "beautifulsoup4-4.12.2-py3-none-any.whl", hash = "sha256:bd2520ca0d9d7d12694a53d44ac482d181b4ec1888909b035a3dbf40d0f57d4a"},
-    {file = "beautifulsoup4-4.12.2.tar.gz", hash = "sha256:492bbc69dca35d12daac71c4db1bfff0c876c00ef4a2ffacce226d4638eb72da"},
+    {file = "beautifulsoup4-4.12.3-py3-none-any.whl", hash = "sha256:b80878c9f40111313e55da8ba20bdba06d8fa3969fc68304167741bbf9e082ed"},
+    {file = "beautifulsoup4-4.12.3.tar.gz", hash = "sha256:74e3d1928edc070d21748185c46e3fb33490f22f52a3addee9aee0f4f7781051"},
 ]
 
 [package.dependencies]
 soupsieve = ">1.2"
 
 [package.extras]
+cchardet = ["cchardet"]
+chardet = ["chardet"]
+charset-normalizer = ["charset-normalizer"]
 html5lib = ["html5lib"]
 lxml = ["lxml"]
 
 [[package]]
 name = "black"
-version = "23.11.0"
+version = "23.12.1"
 description = "The uncompromising code formatter."
-category = "dev"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -302,7 +297,7 @@ typing-extensions = {version = ">=4.0.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
 colorama = ["colorama (>=0.4.3)"]
-d = ["aiohttp (>=3.7.4)"]
+d = ["aiohttp (>=3.7.4)", "aiohttp (>=3.7.4,!=3.9.0)"]
 jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
 uvloop = ["uvloop (>=0.15.2)"]
 
@@ -310,7 +305,6 @@ uvloop = ["uvloop (>=0.15.2)"]
 name = "bleach"
 version = "6.1.0"
 description = "An easy safelist-based HTML-sanitizing tool."
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -329,7 +323,6 @@ css = ["tinycss2 (>=1.1.0,<1.3)"]
 name = "cachetools"
 version = "5.3.2"
 description = "Extensible memoizing collections and decorators"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -339,21 +332,19 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2023.11.17"
+version = "2024.2.2"
 description = "Python package for providing Mozilla's CA Bundle."
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [[package]]
 name = "cffi"
 version = "1.16.0"
 description = "Foreign Function Interface for Python calling C code."
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -418,7 +409,6 @@ pycparser = "*"
 name = "charset-normalizer"
 version = "3.3.2"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
-category = "main"
 optional = false
 python-versions = ">=3.7.0"
 files = [
@@ -518,7 +508,6 @@ files = [
 name = "click"
 version = "8.1.7"
 description = "Composable command line interface toolkit"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -533,7 +522,6 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 name = "click-log"
 version = "0.4.0"
 description = "Logging integration for Click"
-category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -548,8 +536,7 @@ click = "*"
 name = "clickclick"
 version = "20.10.2"
 description = "Click utility functions"
-category = "main"
-optional = false
+optional = true
 python-versions = "*"
 files = [
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@@ -564,7 +551,6 @@ PyYAML = ">=3.11"
 name = "colorama"
 version = "0.4.6"
 description = "Cross-platform colored terminal text."
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 files = [
@@ -574,14 +560,13 @@ files = [
 
 [[package]]
 name = "comm"
-version = "0.2.0"
+version = "0.2.1"
 description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "comm-0.2.1.tar.gz", hash = "sha256:0bc91edae1344d39d3661dcbc36937181fdaddb304790458f8b044dbc064b89a"},
 ]
 
 [package.dependencies]
@@ -594,8 +579,7 @@ test = ["pytest"]
 name = "connexion"
 version = "2.14.2"
 description = "Connexion - API first applications with OpenAPI/Swagger and Flask"
-category = "main"
-optional = false
+optional = true
 python-versions = ">=3.6"
 files = [
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@@ -623,64 +607,63 @@ tests = ["MarkupSafe (>=0.23)", "aiohttp (>=2.3.10,<4)", "aiohttp-jinja2 (>=0.14
 
 [[package]]
 name = "coverage"
-version = "7.3.2"
+version = "7.4.1"
 description = "Code coverage measurement for Python"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
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 version = "41.0.7"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
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@@ -737,14 +719,13 @@ test-randomorder = ["pytest-randomly"]
 
 [[package]]
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 description = "Date parsing library designed to parse dates from HTML pages"
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 python-versions = ">=3.7"
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 name = "decorator"
 version = "5.1.1"
 description = "Decorators for Humans"
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 optional = false
 python-versions = ">=3.5"
 files = [
@@ -818,7 +800,6 @@ files = [
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 version = "0.7.1"
 description = "XML bomb protection for Python stdlib modules"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 files = [
@@ -830,7 +811,6 @@ files = [
 name = "deprecated"
 version = "1.2.14"
 description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
@@ -848,7 +828,6 @@ dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "sphinx (<2)", "tox"]
 name = "deprecation"
 version = "2.1.0"
 description = "A library to handle automated deprecations"
-category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -861,24 +840,23 @@ packaging = "*"
 
 [[package]]
 name = "dill"
-version = "0.3.7"
+version = "0.3.8"
 description = "serialize all of Python"
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "dill-0.3.7-py3-none-any.whl", hash = "sha256:76b122c08ef4ce2eedcd4d1abd8e641114bfc6c2867f49f3c41facf65bf19f5e"},
-    {file = "dill-0.3.7.tar.gz", hash = "sha256:cc1c8b182eb3013e24bd475ff2e9295af86c1a38eb1aff128dac8962a9ce3c03"},
+    {file = "dill-0.3.8-py3-none-any.whl", hash = "sha256:c36ca9ffb54365bdd2f8eb3eff7d2a21237f8452b57ace88b1ac615b7e815bd7"},
+    {file = "dill-0.3.8.tar.gz", hash = "sha256:3ebe3c479ad625c4553aca177444d89b486b1d84982eeacded644afc0cf797ca"},
 ]
 
 [package.extras]
 graph = ["objgraph (>=1.7.2)"]
+profile = ["gprof2dot (>=2022.7.29)"]
 
 [[package]]
 name = "docutils"
 version = "0.20.1"
 description = "Docutils -- Python Documentation Utilities"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -890,7 +868,6 @@ files = [
 name = "entrypoints"
 version = "0.4"
 description = "Discover and load entry points from installed packages."
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -902,7 +879,6 @@ files = [
 name = "et-xmlfile"
 version = "1.1.0"
 description = "An implementation of lxml.xmlfile for the standard library"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -914,7 +890,6 @@ files = [
 name = "exceptiongroup"
 version = "1.2.0"
 description = "Backport of PEP 654 (exception groups)"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -943,7 +918,6 @@ testing = ["hatch", "pre-commit", "pytest", "tox"]
 name = "executing"
 version = "2.0.1"
 description = "Get the currently executing AST node of a frame, and other information"
-category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -956,14 +930,13 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth
 
 [[package]]
 name = "fastjsonschema"
-version = "2.19.0"
+version = "2.19.1"
 description = "Fastest Python implementation of JSON schema"
-category = "main"
 optional = false
 python-versions = "*"
 files = [
-    {file = "fastjsonschema-2.19.0-py3-none-any.whl", hash = "sha256:b9fd1a2dd6971dbc7fee280a95bd199ae0dd9ce22beb91cc75e9c1c528a5170e"},
-    {file = "fastjsonschema-2.19.0.tar.gz", hash = "sha256:e25df6647e1bc4a26070b700897b07b542ec898dd4f1f6ea013e7f6a88417225"},
+    {file = "fastjsonschema-2.19.1-py3-none-any.whl", hash = "sha256:3672b47bc94178c9f23dbb654bf47440155d4db9df5f7bc47643315f9c405cd0"},
+    {file = "fastjsonschema-2.19.1.tar.gz", hash = "sha256:e3126a94bdc4623d3de4485f8d468a12f02a67921315ddc87836d6e456dc789d"},
 ]
 
 [package.extras]
@@ -973,7 +946,6 @@ devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benc
 name = "flake8"
 version = "6.1.0"
 description = "the modular source code checker: pep8 pyflakes and co"
-category = "dev"
 optional = false
 python-versions = ">=3.8.1"
 files = [
@@ -990,8 +962,7 @@ pyflakes = ">=3.1.0,<3.2.0"
 name = "flask"
 version = "2.1.3"
 description = "A simple framework for building complex web applications."
-category = "main"
-optional = false
+optional = true
 python-versions = ">=3.7"
 files = [
     {file = "Flask-2.1.3-py3-none-any.whl", hash = "sha256:9013281a7402ad527f8fd56375164f3aa021ecfaff89bfe3825346c24f87e04c"},
@@ -1013,8 +984,7 @@ dotenv = ["python-dotenv"]
 name = "flask-cors"
 version = "3.0.10"
 description = "A Flask extension adding a decorator for CORS support"
-category = "main"
-optional = false
+optional = true
 python-versions = "*"
 files = [
     {file = "Flask-Cors-3.0.10.tar.gz", hash = "sha256:b60839393f3b84a0f3746f6cdca56c1ad7426aa738b70d6c61375857823181de"},
@@ -1029,7 +999,6 @@ Six = "*"
 name = "fqdn"
 version = "1.5.1"
 description = "Validates fully-qualified domain names against RFC 1123, so that they are acceptable to modern bowsers"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4"
 files = [
@@ -1039,14 +1008,13 @@ files = [
 
 [[package]]
 name = "google-api-core"
-version = "2.14.0"
+version = "2.17.0"
 description = "Google API client core library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-core-2.14.0.tar.gz", hash = "sha256:5368a4502b793d9bbf812a5912e13e4e69f9bd87f6efb508460c43f5bbd1ce41"},
-    {file = "google_api_core-2.14.0-py3-none-any.whl", hash = "sha256:de2fb50ed34d47ddbb2bd2dcf680ee8fead46279f4ed6b16de362aca23a18952"},
+    {file = "google-api-core-2.17.0.tar.gz", hash = "sha256:de7ef0450faec7c75e0aea313f29ac870fdc44cfaec9d6499a9a17305980ef66"},
+    {file = "google_api_core-2.17.0-py3-none-any.whl", hash = "sha256:08ed79ed8e93e329de5e3e7452746b734e6bf8438d8d64dd3319d21d3164890c"},
 ]
 
 [package.dependencies]
@@ -1062,18 +1030,17 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-api-python-client"
-version = "2.108.0"
+version = "2.117.0"
 description = "Google API Client Library for Python"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "google-api-python-client-2.117.0.tar.gz", hash = "sha256:b38cd1477ee3c341a0d2f7427326499b416f36c44e9b20d1da229df8be0c596e"},
+    {file = "google_api_python_client-2.117.0-py2.py3-none-any.whl", hash = "sha256:bd6d393d0eaa7ea1fa13aefb44be787d1ebdc068ab8255f1c3f1d8b486f46afd"},
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0.dev0"
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0.dev0"
 google-auth = ">=1.19.0,<3.0.0.dev0"
 google-auth-httplib2 = ">=0.1.0"
 httplib2 = ">=0.15.0,<1.dev0"
@@ -1081,14 +1048,13 @@ uritemplate = ">=3.0.1,<5"
 
 [[package]]
 name = "google-auth"
-version = "2.23.4"
+version = "2.27.0"
 description = "Google Authentication Library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-auth-2.23.4.tar.gz", hash = "sha256:79905d6b1652187def79d491d6e23d0cbb3a21d3c7ba0dbaa9c8a01906b13ff3"},
-    {file = "google_auth-2.23.4-py2.py3-none-any.whl", hash = "sha256:d4bbc92fe4b8bfd2f3e8d88e5ba7085935da208ee38a134fc280e7ce682a05f2"},
+    {file = "google-auth-2.27.0.tar.gz", hash = "sha256:e863a56ccc2d8efa83df7a80272601e43487fa9a728a376205c86c26aaefa821"},
+    {file = "google_auth-2.27.0-py2.py3-none-any.whl", hash = "sha256:8e4bad367015430ff253fe49d500fdc3396c1a434db5740828c728e45bcce245"},
 ]
 
 [package.dependencies]
@@ -1107,7 +1073,6 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 name = "google-auth-httplib2"
 version = "0.1.1"
 description = "Google Authentication Library: httplib2 transport"
-category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -1123,7 +1088,6 @@ httplib2 = ">=0.19.0"
 name = "google-auth-oauthlib"
 version = "0.8.0"
 description = "Google Authentication Library"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1140,14 +1104,13 @@ tool = ["click (>=6.0.0)"]
 
 [[package]]
 name = "googleapis-common-protos"
-version = "1.61.0"
+version = "1.62.0"
 description = "Common protobufs used in Google APIs"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "googleapis-common-protos-1.61.0.tar.gz", hash = "sha256:8a64866a97f6304a7179873a465d6eee97b7a24ec6cfd78e0f575e96b821240b"},
-    {file = "googleapis_common_protos-1.61.0-py2.py3-none-any.whl", hash = "sha256:22f1915393bb3245343f6efe87f6fe868532efc12aa26b391b15132e1279f1c0"},
+    {file = "googleapis-common-protos-1.62.0.tar.gz", hash = "sha256:83f0ece9f94e5672cced82f592d2a5edf527a96ed1794f0bab36d5735c996277"},
+    {file = "googleapis_common_protos-1.62.0-py2.py3-none-any.whl", hash = "sha256:4750113612205514f9f6aa4cb00d523a94f3e8c06c5ad2fee466387dc4875f07"},
 ]
 
 [package.dependencies]
@@ -1160,7 +1123,6 @@ grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
 name = "graphviz"
 version = "0.20.1"
 description = "Simple Python interface for Graphviz"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1177,7 +1139,6 @@ test = ["coverage", "mock (>=4)", "pytest (>=7)", "pytest-cov", "pytest-mock (>=
 name = "great-expectations"
 version = "0.15.50"
 description = "Always know what to expect from your data."
-category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -1250,80 +1211,111 @@ vertica = ["sqlalchemy (>=1.3.18,<2.0.0)", "sqlalchemy-vertica-python (>=0.5.10)
 
 [[package]]
 name = "greenlet"
-version = "3.0.1"
+version = "3.0.3"
 description = "Lightweight in-process concurrent programming"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
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 [package.extras]
-docs = ["Sphinx"]
+docs = ["Sphinx", "furo"]
 test = ["objgraph", "psutil"]
 
+[[package]]
+name = "h11"
+version = "0.14.0"
+description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
+optional = false
+python-versions = ">=3.7"
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+
+[[package]]
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+optional = false
+python-versions = ">=3.8"
+files = [
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+
+[package.dependencies]
+certifi = "*"
+h11 = ">=0.13,<0.15"
+
+[package.extras]
+asyncio = ["anyio (>=4.0,<5.0)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+trio = ["trio (>=0.22.0,<0.23.0)"]
+
 [[package]]
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 version = "0.22.0"
 description = "A comprehensive HTTP client library."
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
@@ -1334,11 +1326,34 @@ files = [
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+[[package]]
+name = "httpx"
+version = "0.26.0"
+description = "The next generation HTTP client."
+optional = false
+python-versions = ">=3.8"
+files = [
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+
+[package.dependencies]
+anyio = "*"
+certifi = "*"
+httpcore = "==1.*"
+idna = "*"
+sniffio = "*"
+
+[package.extras]
+brotli = ["brotli", "brotlicffi"]
+cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+
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 name = "idna"
 version = "3.6"
 description = "Internationalized Domain Names in Applications (IDNA)"
-category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -1350,7 +1365,6 @@ files = [
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 description = "Getting image size from png/jpeg/jpeg2000/gif file"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
@@ -1360,21 +1374,20 @@ files = [
 
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+version = "6.11.0"
 description = "Read metadata from Python packages"
-category = "main"
 optional = false
 python-versions = ">=3.8"
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-    {file = "importlib_metadata-6.8.0.tar.gz", hash = "sha256:dbace7892d8c0c4ac1ad096662232f831d4e64f4c4545bd53016a3e9d4654743"},
+    {file = "importlib_metadata-6.11.0-py3-none-any.whl", hash = "sha256:f0afba6205ad8f8947c7d338b5342d5db2afbfd82f9cbef7879a9539cc12eb9b"},
+    {file = "importlib_metadata-6.11.0.tar.gz", hash = "sha256:1231cf92d825c9e03cfc4da076a16de6422c863558229ea0b22b675657463443"},
 ]
 
 [package.dependencies]
 zipp = ">=0.5"
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
 perf = ["ipython"]
 testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)", "pytest-ruff"]
 
@@ -1382,7 +1395,6 @@ testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs
 name = "inflection"
 version = "0.5.1"
 description = "A port of Ruby on Rails inflector to Python"
-category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -1394,7 +1406,6 @@ files = [
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1406,7 +1417,6 @@ files = [
 name = "interrogate"
 version = "1.5.0"
 description = "Interrogate a codebase for docstring coverage."
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1430,14 +1440,13 @@ tests = ["pytest", "pytest-cov", "pytest-mock"]
 
 [[package]]
 name = "ipykernel"
-version = "6.27.1"
+version = "6.29.2"
 description = "IPython Kernel for Jupyter"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "ipykernel-6.27.1-py3-none-any.whl", hash = "sha256:dab88b47f112f9f7df62236511023c9bdeef67abc73af7c652e4ce4441601686"},
-    {file = "ipykernel-6.27.1.tar.gz", hash = "sha256:7d5d594b6690654b4d299edba5e872dc17bb7396a8d0609c97cb7b8a1c605de6"},
+    {file = "ipykernel-6.29.2-py3-none-any.whl", hash = "sha256:50384f5c577a260a1d53f1f59a828c7266d321c9b7d00d345693783f66616055"},
+    {file = "ipykernel-6.29.2.tar.gz", hash = "sha256:3bade28004e3ff624ed57974948116670604ac5f676d12339693f3142176d3f0"},
 ]
 
 [package.dependencies]
@@ -1446,12 +1455,12 @@ comm = ">=0.1.1"
 debugpy = ">=1.6.5"
 ipython = ">=7.23.1"
 jupyter-client = ">=6.1.12"
-jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
 matplotlib-inline = ">=0.1"
 nest-asyncio = "*"
 packaging = "*"
 psutil = "*"
-pyzmq = ">=20"
+pyzmq = ">=24"
 tornado = ">=6.1"
 traitlets = ">=5.4.0"
 
@@ -1460,13 +1469,12 @@ cov = ["coverage[toml]", "curio", "matplotlib", "pytest-cov", "trio"]
 docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
 pyqt5 = ["pyqt5"]
 pyside6 = ["pyside6"]
-test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov", "pytest-timeout"]
+test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (==0.23.4)", "pytest-cov", "pytest-timeout"]
 
 [[package]]
 name = "ipython"
 version = "8.18.1"
 description = "IPython: Productive Interactive Computing"
-category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
@@ -1502,22 +1510,21 @@ test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.22)", "pa
 
 [[package]]
 name = "ipywidgets"
-version = "8.1.1"
+version = "8.1.2"
 description = "Jupyter interactive widgets"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "ipywidgets-8.1.1-py3-none-any.whl", hash = "sha256:2b88d728656aea3bbfd05d32c747cfd0078f9d7e159cf982433b58ad717eed7f"},
-    {file = "ipywidgets-8.1.1.tar.gz", hash = "sha256:40211efb556adec6fa450ccc2a77d59ca44a060f4f9f136833df59c9f538e6e8"},
+    {file = "ipywidgets-8.1.2-py3-none-any.whl", hash = "sha256:bbe43850d79fb5e906b14801d6c01402857996864d1e5b6fa62dd2ee35559f60"},
+    {file = "ipywidgets-8.1.2.tar.gz", hash = "sha256:d0b9b41e49bae926a866e613a39b0f0097745d2b9f1f3dd406641b4a57ec42c9"},
 ]
 
 [package.dependencies]
 comm = ">=0.1.3"
 ipython = ">=6.1.0"
-jupyterlab-widgets = ">=3.0.9,<3.1.0"
+jupyterlab-widgets = ">=3.0.10,<3.1.0"
 traitlets = ">=4.3.1"
-widgetsnbextension = ">=4.0.9,<4.1.0"
+widgetsnbextension = ">=4.0.10,<4.1.0"
 
 [package.extras]
 test = ["ipykernel", "jsonschema", "pytest (>=3.6.0)", "pytest-cov", "pytz"]
@@ -1526,7 +1533,6 @@ test = ["ipykernel", "jsonschema", "pytest (>=3.6.0)", "pytest-cov", "pytz"]
 name = "isodate"
 version = "0.6.1"
 description = "An ISO 8601 date/time/duration parser and formatter"
-category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -1541,7 +1547,6 @@ six = "*"
 name = "isoduration"
 version = "20.11.0"
 description = "Operations with ISO 8601 durations"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1554,27 +1559,22 @@ arrow = ">=0.15.0"
 
 [[package]]
 name = "isort"
-version = "5.12.0"
+version = "5.13.2"
 description = "A Python utility / library to sort Python imports."
-category = "dev"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "isort-5.12.0-py3-none-any.whl", hash = "sha256:f84c2818376e66cf843d497486ea8fed8700b340f308f076c6fb1229dff318b6"},
-    {file = "isort-5.12.0.tar.gz", hash = "sha256:8bef7dde241278824a6d83f44a544709b065191b95b6e50894bdc722fcba0504"},
+    {file = "isort-5.13.2-py3-none-any.whl", hash = "sha256:8ca5e72a8d85860d5a3fa69b8745237f2939afe12dbf656afbcb47fe72d947a6"},
+    {file = "isort-5.13.2.tar.gz", hash = "sha256:48fdfcb9face5d58a4f6dde2e72a1fb8dcaf8ab26f95ab49fab84c2ddefb0109"},
 ]
 
 [package.extras]
-colors = ["colorama (>=0.4.3)"]
-pipfile-deprecated-finder = ["pip-shims (>=0.5.2)", "pipreqs", "requirementslib"]
-plugins = ["setuptools"]
-requirements-deprecated-finder = ["pip-api", "pipreqs"]
+colors = ["colorama (>=0.4.6)"]
 
 [[package]]
 name = "itsdangerous"
 version = "2.1.2"
 description = "Safely pass data to untrusted environments and back."
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1586,7 +1586,6 @@ files = [
 name = "jedi"
 version = "0.19.1"
 description = "An autocompletion tool for Python that can be used for text editors."
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1606,7 +1605,6 @@ testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 name = "jeepney"
 version = "0.8.0"
 description = "Low-level, pure Python DBus protocol wrapper."
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1620,14 +1618,13 @@ trio = ["async_generator", "trio"]
 
 [[package]]
 name = "jinja2"
-version = "3.1.2"
+version = "3.1.3"
 description = "A very fast and expressive template engine."
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "Jinja2-3.1.2-py3-none-any.whl", hash = "sha256:6088930bfe239f0e6710546ab9c19c9ef35e29792895fed6e6e31a023a182a61"},
-    {file = "Jinja2-3.1.2.tar.gz", hash = "sha256:31351a702a408a9e7595a8fc6150fc3f43bb6bf7e319770cbc0db9df9437e852"},
+    {file = "Jinja2-3.1.3-py3-none-any.whl", hash = "sha256:7d6d50dd97d52cbc355597bd845fabfbac3f551e1f99619e39a35ce8c370b5fa"},
+    {file = "Jinja2-3.1.3.tar.gz", hash = "sha256:ac8bd6544d4bb2c9792bf3a159e80bba8fda7f07e81bc3aed565432d5925ba90"},
 ]
 
 [package.dependencies]
@@ -1640,7 +1637,6 @@ i18n = ["Babel (>=2.7)"]
 name = "json5"
 version = "0.9.14"
 description = "A Python implementation of the JSON5 data format."
-category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -1655,7 +1651,6 @@ dev = ["hypothesis"]
 name = "jsonpatch"
 version = "1.33"
 description = "Apply JSON-Patches (RFC 6902)"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
 files = [
@@ -1670,7 +1665,6 @@ jsonpointer = ">=1.9"
 name = "jsonpointer"
 version = "2.4"
 description = "Identify specific nodes in a JSON document (RFC 6901)"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
 files = [
@@ -1680,14 +1674,13 @@ files = [
 
 [[package]]
 name = "jsonschema"
-version = "4.20.0"
+version = "4.21.1"
 description = "An implementation of JSON Schema validation for Python"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jsonschema-4.20.0-py3-none-any.whl", hash = "sha256:ed6231f0429ecf966f5bc8dfef245998220549cbbcf140f913b7464c52c3b6b3"},
-    {file = "jsonschema-4.20.0.tar.gz", hash = "sha256:4f614fd46d8d61258610998997743ec5492a648b33cf478c1ddc23ed4598a5fa"},
+    {file = "jsonschema-4.21.1-py3-none-any.whl", hash = "sha256:7996507afae316306f9e2290407761157c6f78002dcf7419acb99822143d1c6f"},
+    {file = "jsonschema-4.21.1.tar.gz", hash = "sha256:85727c00279f5fa6bedbe6238d2aa6403bedd8b4864ab11207d07df3cc1b2ee5"},
 ]
 
 [package.dependencies]
@@ -1710,14 +1703,13 @@ format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-
 
 [[package]]
 name = "jsonschema-specifications"
-version = "2023.11.1"
+version = "2023.12.1"
 description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jsonschema_specifications-2023.11.1-py3-none-any.whl", hash = "sha256:f596778ab612b3fd29f72ea0d990393d0540a5aab18bf0407a46632eab540779"},
-    {file = "jsonschema_specifications-2023.11.1.tar.gz", hash = "sha256:c9b234904ffe02f079bf91b14d79987faa685fd4b39c377a0996954c0090b9ca"},
+    {file = "jsonschema_specifications-2023.12.1-py3-none-any.whl", hash = "sha256:87e4fdf3a94858b8a2ba2778d9ba57d8a9cafca7c7489c46ba0d30a8bc6a9c3c"},
+    {file = "jsonschema_specifications-2023.12.1.tar.gz", hash = "sha256:48a76787b3e70f5ed53f1160d2b81f586e4ca6d1548c5de7085d1682674764cc"},
 ]
 
 [package.dependencies]
@@ -1727,7 +1719,6 @@ referencing = ">=0.31.0"
 name = "jupyter-client"
 version = "8.6.0"
 description = "Jupyter protocol implementation and client libraries"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -1737,7 +1728,7 @@ files = [
 
 [package.dependencies]
 importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""}
-jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
 python-dateutil = ">=2.8.2"
 pyzmq = ">=23.0"
 tornado = ">=6.2"
@@ -1749,14 +1740,13 @@ test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pyt
 
 [[package]]
 name = "jupyter-core"
-version = "5.5.0"
+version = "5.7.1"
 description = "Jupyter core package. A base package on which Jupyter projects rely."
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter_core-5.5.0-py3-none-any.whl", hash = "sha256:e11e02cd8ae0a9de5c6c44abf5727df9f2581055afe00b22183f621ba3585805"},
-    {file = "jupyter_core-5.5.0.tar.gz", hash = "sha256:880b86053bf298a8724994f95e99b99130659022a4f7f45f563084b6223861d3"},
+    {file = "jupyter_core-5.7.1-py3-none-any.whl", hash = "sha256:c65c82126453a723a2804aa52409930434598fd9d35091d63dfb919d2b765bb7"},
+    {file = "jupyter_core-5.7.1.tar.gz", hash = "sha256:de61a9d7fc71240f688b2fb5ab659fbb56979458dc66a71decd098e03c79e218"},
 ]
 
 [package.dependencies]
@@ -1772,7 +1762,6 @@ test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"]
 name = "jupyter-events"
 version = "0.9.0"
 description = "Jupyter Event System library"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -1796,14 +1785,13 @@ test = ["click", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "p
 
 [[package]]
 name = "jupyter-lsp"
-version = "2.2.1"
+version = "2.2.2"
 description = "Multi-Language Server WebSocket proxy for Jupyter Notebook/Lab server"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter-lsp-2.2.1.tar.gz", hash = "sha256:b17fab6d70fe83c8896b0cff59237640038247c196056b43684a0902b6a9e0fb"},
-    {file = "jupyter_lsp-2.2.1-py3-none-any.whl", hash = "sha256:17a689910c5e4ae5e7d334b02f31d08ffbe98108f6f658fb05e4304b4345368b"},
+    {file = "jupyter-lsp-2.2.2.tar.gz", hash = "sha256:256d24620542ae4bba04a50fc1f6ffe208093a07d8e697fea0a8d1b8ca1b7e5b"},
+    {file = "jupyter_lsp-2.2.2-py3-none-any.whl", hash = "sha256:3b95229e4168355a8c91928057c1621ac3510ba98b2a925e82ebd77f078b1aa5"},
 ]
 
 [package.dependencies]
@@ -1812,14 +1800,13 @@ jupyter-server = ">=1.1.2"
 
 [[package]]
 name = "jupyter-server"
-version = "2.11.1"
+version = "2.12.5"
 description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications."
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter_server-2.11.1-py3-none-any.whl", hash = "sha256:4b3a16e3ed16fd202588890f10b8ca589bd3e29405d128beb95935f059441373"},
-    {file = "jupyter_server-2.11.1.tar.gz", hash = "sha256:fe80bab96493acf5f7d6cd9a1575af8fbd253dc2591aa4d015131a1e03b5799a"},
+    {file = "jupyter_server-2.12.5-py3-none-any.whl", hash = "sha256:184a0f82809a8522777cfb6b760ab6f4b1bb398664c5860a27cec696cb884923"},
+    {file = "jupyter_server-2.12.5.tar.gz", hash = "sha256:0edb626c94baa22809be1323f9770cf1c00a952b17097592e40d03e6a3951689"},
 ]
 
 [package.dependencies]
@@ -1849,14 +1836,13 @@ test = ["flaky", "ipykernel", "pre-commit", "pytest (>=7.0)", "pytest-console-sc
 
 [[package]]
 name = "jupyter-server-terminals"
-version = "0.4.4"
+version = "0.5.2"
 description = "A Jupyter Server Extension Providing Terminals."
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter_server_terminals-0.4.4-py3-none-any.whl", hash = "sha256:75779164661cec02a8758a5311e18bb8eb70c4e86c6b699403100f1585a12a36"},
-    {file = "jupyter_server_terminals-0.4.4.tar.gz", hash = "sha256:57ab779797c25a7ba68e97bcfb5d7740f2b5e8a83b5e8102b10438041a7eac5d"},
+    {file = "jupyter_server_terminals-0.5.2-py3-none-any.whl", hash = "sha256:1b80c12765da979513c42c90215481bbc39bd8ae7c0350b4f85bc3eb58d0fa80"},
+    {file = "jupyter_server_terminals-0.5.2.tar.gz", hash = "sha256:396b5ccc0881e550bf0ee7012c6ef1b53edbde69e67cab1d56e89711b46052e8"},
 ]
 
 [package.dependencies]
@@ -1864,23 +1850,23 @@ pywinpty = {version = ">=2.0.3", markers = "os_name == \"nt\""}
 terminado = ">=0.8.3"
 
 [package.extras]
-docs = ["jinja2", "jupyter-server", "mistune (<3.0)", "myst-parser", "nbformat", "packaging", "pydata-sphinx-theme", "sphinxcontrib-github-alt", "sphinxcontrib-openapi", "sphinxcontrib-spelling", "sphinxemoji", "tornado"]
-test = ["coverage", "jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-cov", "pytest-jupyter[server] (>=0.5.3)", "pytest-timeout"]
+docs = ["jinja2", "jupyter-server", "mistune (<4.0)", "myst-parser", "nbformat", "packaging", "pydata-sphinx-theme", "sphinxcontrib-github-alt", "sphinxcontrib-openapi", "sphinxcontrib-spelling", "sphinxemoji", "tornado"]
+test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>=0.5.3)", "pytest-timeout"]
 
 [[package]]
 name = "jupyterlab"
-version = "4.0.9"
+version = "4.1.0"
 description = "JupyterLab computational environment"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyterlab-4.0.9-py3-none-any.whl", hash = "sha256:9f6f8e36d543fdbcc3df961a1d6a3f524b4a4001be0327a398f68fa4e534107c"},
-    {file = "jupyterlab-4.0.9.tar.gz", hash = "sha256:9ebada41d52651f623c0c9f069ddb8a21d6848e4c887d8e5ddc0613166ed5c0b"},
+    {file = "jupyterlab-4.1.0-py3-none-any.whl", hash = "sha256:5380e85fb4f11a227ed2db13103e513cfea274d1011f6210e62d611e92e0369d"},
+    {file = "jupyterlab-4.1.0.tar.gz", hash = "sha256:92cdfd86c53e163fb9e91e14497901153536c5a889c9225dade270f6107a077f"},
 ]
 
 [package.dependencies]
 async-lru = ">=1.0.0"
+httpx = ">=0.25.0"
 importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""}
 ipykernel = "*"
 jinja2 = ">=3.0.3"
@@ -1895,16 +1881,15 @@ tornado = ">=6.2.0"
 traitlets = "*"
 
 [package.extras]
-dev = ["black[jupyter] (==23.10.1)", "build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.1.4)"]
-docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-tornasync", "sphinx (>=1.8,<7.2.0)", "sphinx-copybutton"]
-docs-screenshots = ["altair (==5.0.1)", "ipython (==8.14.0)", "ipywidgets (==8.0.6)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.0.post0)", "matplotlib (==3.7.1)", "nbconvert (>=7.0.0)", "pandas (==2.0.2)", "scipy (==1.10.1)", "vega-datasets (==0.9.0)"]
+dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.1.15)"]
+docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<7.3.0)", "sphinx-copybutton"]
+docs-screenshots = ["altair (==5.2.0)", "ipython (==8.16.1)", "ipywidgets (==8.1.1)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.0.post6)", "matplotlib (==3.8.2)", "nbconvert (>=7.0.0)", "pandas (==2.2.0)", "scipy (==1.12.0)", "vega-datasets (==0.9.0)"]
 test = ["coverage", "pytest (>=7.0)", "pytest-check-links (>=0.7)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter (>=0.5.3)", "pytest-timeout", "pytest-tornasync", "requests", "requests-cache", "virtualenv"]
 
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 version = "0.3.0"
 description = "Pygments theme using JupyterLab CSS variables"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -1916,7 +1901,6 @@ files = [
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 version = "2.25.2"
 description = "A set of server components for JupyterLab and JupyterLab like applications."
-category = "main"
 optional = false
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@@ -1941,21 +1925,19 @@ test = ["hatch", "ipykernel", "openapi-core (>=0.18.0,<0.19.0)", "openapi-spec-v
 
 [[package]]
 name = "jupyterlab-widgets"
-version = "3.0.9"
+version = "3.0.10"
 description = "Jupyter interactive widgets for JupyterLab"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
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 [[package]]
 name = "keyring"
 version = "23.4.1"
 description = "Store and access your passwords safely."
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1977,7 +1959,6 @@ testing = ["pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)",
 name = "keyrings-alt"
 version = "3.1"
 description = "Alternate keyring implementations"
-category = "main"
 optional = false
 python-versions = ">=2.7"
 files = [
@@ -1994,55 +1975,54 @@ testing = ["backports.unittest-mock", "collective.checkdocs", "fs (>=0.5,<2)", "
 
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 version = "1.15.2"
 description = "Small library to dynamically create python functions."
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 optional = false
 python-versions = "*"
 files = [
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 name = "markupsafe"
 version = "2.1.0"
 description = "Safely add untrusted strings to HTML/XML markup."
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -2102,30 +2081,28 @@ files = [
 
 [[package]]
 name = "marshmallow"
-version = "3.20.1"
+version = "3.20.2"
 description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
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-lint = ["flake8 (==6.0.0)", "flake8-bugbear (==23.7.10)", "mypy (==1.4.1)", "pre-commit (>=2.4,<4.0)"]
+dev = ["pre-commit (>=2.4,<4.0)", "pytest", "pytz", "simplejson", "tox"]
+docs = ["alabaster (==0.7.15)", "autodocsumm (==0.2.12)", "sphinx (==7.2.6)", "sphinx-issues (==3.0.1)", "sphinx-version-warning (==1.1.2)"]
+lint = ["pre-commit (>=2.4,<4.0)"]
 tests = ["pytest", "pytz", "simplejson"]
 
 [[package]]
 name = "matplotlib-inline"
 version = "0.1.6"
 description = "Inline Matplotlib backend for Jupyter"
-category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -2140,7 +2117,6 @@ traitlets = "*"
 name = "mccabe"
 version = "0.7.0"
 description = "McCabe checker, plugin for flake8"
-category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -2152,7 +2128,6 @@ files = [
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 version = "3.0.2"
 description = "A sane and fast Markdown parser with useful plugins and renderers"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -2162,39 +2137,38 @@ files = [
 
 [[package]]
 name = "mypy"
-version = "1.7.1"
+version = "1.8.0"
 description = "Optional static typing for Python"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
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+    {file = "mypy-1.8.0.tar.gz", hash = "sha256:6ff8b244d7085a0b425b56d327b480c3b29cafbd2eff27316a004f9a7391ae07"},
 ]
 
 [package.dependencies]
@@ -2212,7 +2186,6 @@ reports = ["lxml"]
 name = "mypy-extensions"
 version = "1.0.0"
 description = "Type system extensions for programs checked with the mypy type checker."
-category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -2224,7 +2197,6 @@ files = [
 name = "nbclient"
 version = "0.9.0"
 description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor."
-category = "main"
 optional = false
 python-versions = ">=3.8.0"
 files = [
@@ -2234,7 +2206,7 @@ files = [
 
 [package.dependencies]
 jupyter-client = ">=6.1.12"
-jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
 nbformat = ">=5.1"
 traitlets = ">=5.4"
 
@@ -2245,14 +2217,13 @@ test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=
 
 [[package]]
 name = "nbconvert"
-version = "7.11.0"
+version = "7.16.0"
 description = "Converting Jupyter Notebooks"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "nbconvert-7.16.0.tar.gz", hash = "sha256:813e6553796362489ae572e39ba1bff978536192fb518e10826b0e8cadf03ec8"},
 ]
 
 [package.dependencies]
@@ -2279,14 +2250,13 @@ docs = ["ipykernel", "ipython", "myst-parser", "nbsphinx (>=0.2.12)", "pydata-sp
 qtpdf = ["nbconvert[qtpng]"]
 qtpng = ["pyqtwebengine (>=5.15)"]
 serve = ["tornado (>=6.1)"]
-test = ["flaky", "ipykernel", "ipywidgets (>=7)", "pytest"]
+test = ["flaky", "ipykernel", "ipywidgets (>=7.5)", "pytest"]
 webpdf = ["playwright"]
 
 [[package]]
 name = "nbformat"
 version = "5.9.2"
 description = "The Jupyter Notebook format"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -2306,21 +2276,19 @@ test = ["pep440", "pre-commit", "pytest", "testpath"]
 
 [[package]]
 name = "nest-asyncio"
-version = "1.5.8"
+version = "1.6.0"
 description = "Patch asyncio to allow nested event loops"
-category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
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 ]
 
 [[package]]
 name = "networkx"
 version = "2.8.8"
 description = "Python package for creating and manipulating graphs and networks"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -2337,14 +2305,13 @@ test = ["codecov (>=2.1)", "pytest (>=7.2)", "pytest-cov (>=4.0)"]
 
 [[package]]
 name = "notebook"
-version = "7.0.6"
+version = "7.0.7"
 description = "Jupyter Notebook - A web-based notebook environment for interactive computing"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2363,7 +2330,6 @@ test = ["importlib-resources (>=5.0)", "ipykernel", "jupyter-server[test] (>=2.4
 name = "notebook-shim"
 version = "0.2.3"
 description = "A shim layer for notebook traits and config"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -2379,55 +2345,53 @@ test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync"
 
 [[package]]
 name = "numpy"
-version = "1.26.2"
+version = "1.26.4"
 description = "Fundamental package for array computing in Python"
-category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
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 [package.dependencies]
-numpy = [
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-    {version = ">=1.21.0", markers = "python_version >= \"3.10\""},
-]
-python-dateutil = ">=2.8.1"
+numpy = {version = ">=1.22.4,<2", markers = "python_version < \"3.11\""}
+python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
+tzdata = ">=2022.7"
 
 [package.extras]
-test = ["hypothesis (>=5.5.3)", "pytest (>=6.0)", "pytest-xdist (>=1.31)"]
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+hdf5 = ["tables (>=3.8.0)"]
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+xml = ["lxml (>=4.9.2)"]
 
 [[package]]
 name = "pandocfilters"
-version = "1.5.0"
+version = "1.5.1"
 description = "Utilities for writing pandoc filters in python"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
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 ]
 
 [[package]]
 name = "parso"
 version = "0.8.3"
 description = "A Python Parser"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -2691,21 +2668,19 @@ testing = ["docopt", "pytest (<6.0.0)"]
 
 [[package]]
 name = "pathspec"
-version = "0.11.2"
+version = "0.12.1"
 description = "Utility library for gitignore style pattern matching of file paths."
-category = "dev"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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+    {file = "pathspec-0.12.1.tar.gz", hash = "sha256:a482d51503a1ab33b1c67a6c3813a26953dbdc71c31dacaef9a838c4e29f5712"},
 ]
 
 [[package]]
 name = "pdoc"
 version = "12.3.1"
 description = "API Documentation for Python Projects"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -2725,7 +2700,6 @@ dev = ["black", "hypothesis", "mypy", "pytest", "pytest-cov", "pytest-timeout",
 name = "pexpect"
 version = "4.9.0"
 description = "Pexpect allows easy control of interactive console applications."
-category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -2738,30 +2712,28 @@ ptyprocess = ">=0.5"
 
 [[package]]
 name = "platformdirs"
-version = "4.0.0"
+version = "4.2.0"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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+    {file = "platformdirs-4.2.0.tar.gz", hash = "sha256:ef0cc731df711022c174543cb70a9b5bd22e5a9337c8624ef2c2ceb8ddad8768"},
 ]
 
 [package.extras]
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-test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)"]
+docs = ["furo (>=2023.9.10)", "proselint (>=0.13)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
+test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)"]
 
 [[package]]
 name = "pluggy"
-version = "1.3.0"
+version = "1.4.0"
 description = "plugin and hook calling mechanisms for python"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "pluggy-1.4.0-py3-none-any.whl", hash = "sha256:7db9f7b503d67d1c5b95f59773ebb58a8c1c288129a88665838012cfb07b8981"},
+    {file = "pluggy-1.4.0.tar.gz", hash = "sha256:8c85c2876142a764e5b7548e7d9a0e0ddb46f5185161049a79b7e974454223be"},
 ]
 
 [package.extras]
@@ -2772,7 +2744,6 @@ testing = ["pytest", "pytest-benchmark"]
 name = "prometheus-client"
 version = "0.19.0"
 description = "Python client for the Prometheus monitoring system."
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -2785,14 +2756,13 @@ twisted = ["twisted"]
 
 [[package]]
 name = "prompt-toolkit"
-version = "3.0.41"
+version = "3.0.43"
 description = "Library for building powerful interactive command lines in Python"
-category = "main"
 optional = false
 python-versions = ">=3.7.0"
 files = [
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-    {file = "prompt_toolkit-3.0.41.tar.gz", hash = "sha256:941367d97fc815548822aa26c2a269fdc4eb21e9ec05fc5d447cf09bad5d75f0"},
+    {file = "prompt_toolkit-3.0.43-py3-none-any.whl", hash = "sha256:a11a29cb3bf0a28a387fe5122cdb649816a957cd9261dcedf8c9f1fef33eacf6"},
+    {file = "prompt_toolkit-3.0.43.tar.gz", hash = "sha256:3527b7af26106cbc65a040bcc84839a3566ec1b051bb0bfe953631e704b0ff7d"},
 ]
 
 [package.dependencies]
@@ -2800,49 +2770,47 @@ wcwidth = "*"
 
 [[package]]
 name = "protobuf"
-version = "4.25.1"
+version = "4.25.2"
 description = ""
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
@@ -2995,7 +2955,6 @@ email = ["email-validator (>=1.0.3)"]
 name = "pyflakes"
 version = "3.1.0"
 description = "passive checker of Python programs"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -3007,7 +2966,6 @@ files = [
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 description = "Pygments is a syntax highlighting package written in Python."
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 python-versions = ">=3.7"
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@@ -3023,7 +2981,6 @@ windows-terminal = ["colorama (>=0.4.6)"]
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 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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@@ -3042,7 +2999,6 @@ pandas = ["pandas (>=0.14.0)"]
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@@ -3069,7 +3025,6 @@ testutils = ["gitpython (>3)"]
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 python-versions = ">=3.7"
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@@ -3088,7 +3043,6 @@ test = ["flaky", "pretend", "pytest (>=3.0.1)"]
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 files = [
@@ -3101,14 +3055,13 @@ diagrams = ["jinja2", "railroad-diagrams"]
 
 [[package]]
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 description = "pytest: simple powerful testing with Python"
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 [package.dependencies]
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 version = "4.1.0"
 description = "Pytest plugin for measuring coverage."
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@@ -3145,7 +3097,6 @@ testing = ["fields", "hunter", "process-tests", "pytest-xdist", "six", "virtuale
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 ]
 
 [[package]]
 name = "requests"
 version = "2.31.0"
 description = "Python HTTP for Humans."
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -3628,7 +3572,6 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 name = "requests-oauthlib"
 version = "1.3.1"
 description = "OAuthlib authentication support for Requests."
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
@@ -3647,7 +3590,6 @@ rsa = ["oauthlib[signedtoken] (>=3.0.0)"]
 name = "rfc3339-validator"
 version = "0.1.4"
 description = "A pure python RFC3339 validator"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 files = [
@@ -3662,7 +3604,6 @@ six = "*"
 name = "rfc3986-validator"
 version = "0.1.1"
 description = "Pure python rfc3986 validator"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 files = [
@@ -3672,118 +3613,116 @@ files = [
 
 [[package]]
 name = "rpds-py"
-version = "0.13.1"
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 description = "Pure-Python RSA implementation"
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 description = "ruamel.yaml is a YAML parser/emitter that supports roundtrip preservation of comments, seq/map flow style, and map key order"
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@@ -3817,7 +3755,6 @@ jinja2 = ["ruamel.yaml.jinja2 (>=0.2)"]
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 version = "0.2.8"
 description = "C version of reader, parser and emitter for ruamel.yaml derived from libyaml"
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 optional = false
 python-versions = ">=3.6"
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 requests = ">=2.28.1,<3.0.0"
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 ]
 
 [package.dependencies]
-numpy = ">=1.21.6,<1.28.0"
+numpy = ">=1.22.4,<1.29.0"
 
 [package.extras]
 dev = ["click", "cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy", "pycodestyle", "pydevtool", "rich-click", "ruff", "types-psutil", "typing_extensions"]
 doc = ["jupytext", "matplotlib (>2)", "myst-nb", "numpydoc", "pooch", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-design (>=0.2.0)"]
-test = ["asv", "gmpy2", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
+test = ["asv", "gmpy2", "hypothesis", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
 
 [[package]]
 name = "secretstorage"
 version = "3.3.3"
 description = "Python bindings to FreeDesktop.org Secret Service API"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -3961,7 +3901,6 @@ jeepney = ">=0.6"
 name = "send2trash"
 version = "1.8.2"
 description = "Send file to trash natively under Mac OS X, Windows and Linux"
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
 files = [
@@ -3978,7 +3917,6 @@ win32 = ["pywin32"]
 name = "setuptools"
 version = "66.1.1"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -3995,7 +3933,6 @@ testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (
 name = "six"
 version = "1.16.0"
 description = "Python 2 and 3 compatibility utilities"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
 files = [
@@ -4007,7 +3944,6 @@ files = [
 name = "sniffio"
 version = "1.3.0"
 description = "Sniff out which async library your code is running under"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -4019,7 +3955,6 @@ files = [
 name = "snowballstemmer"
 version = "2.2.0"
 description = "This package provides 29 stemmers for 28 languages generated from Snowball algorithms."
-category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -4031,7 +3966,6 @@ files = [
 name = "soupsieve"
 version = "2.5"
 description = "A modern CSS selector implementation for Beautiful Soup."
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -4043,7 +3977,6 @@ files = [
 name = "sphinx"
 version = "7.2.6"
 description = "Python documentation generator"
-category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
@@ -4079,7 +4012,6 @@ test = ["cython (>=3.0)", "filelock", "html5lib", "pytest (>=4.6)", "setuptools
 name = "sphinx-click"
 version = "4.4.0"
 description = "Sphinx extension that automatically documents click applications"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -4094,66 +4026,56 @@ sphinx = ">=2.0"
 
 [[package]]
 name = "sphinxcontrib-applehelp"
-version = "1.0.7"
+version = "1.0.8"
 description = "sphinxcontrib-applehelp is a Sphinx extension which outputs Apple help books"
-category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
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 ]
 
-[package.dependencies]
-Sphinx = ">=5"
-
 [package.extras]
 lint = ["docutils-stubs", "flake8", "mypy"]
+standalone = ["Sphinx (>=5)"]
 test = ["pytest"]
 
 [[package]]
 name = "sphinxcontrib-devhelp"
-version = "1.0.5"
+version = "1.0.6"
 description = "sphinxcontrib-devhelp is a sphinx extension which outputs Devhelp documents"
-category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
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 ]
 
-[package.dependencies]
-Sphinx = ">=5"
-
 [package.extras]
 lint = ["docutils-stubs", "flake8", "mypy"]
+standalone = ["Sphinx (>=5)"]
 test = ["pytest"]
 
 [[package]]
 name = "sphinxcontrib-htmlhelp"
-version = "2.0.4"
+version = "2.0.5"
 description = "sphinxcontrib-htmlhelp is a sphinx extension which renders HTML help files"
-category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
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 ]
 
-[package.dependencies]
-Sphinx = ">=5"
-
 [package.extras]
 lint = ["docutils-stubs", "flake8", "mypy"]
+standalone = ["Sphinx (>=5)"]
 test = ["html5lib", "pytest"]
 
 [[package]]
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 version = "1.0.1"
 description = "A sphinx extension which renders display math in HTML via JavaScript"
-category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -4166,99 +4088,92 @@ test = ["flake8", "mypy", "pytest"]
 
 [[package]]
 name = "sphinxcontrib-qthelp"
-version = "1.0.6"
+version = "1.0.7"
 description = "sphinxcontrib-qthelp is a sphinx extension which outputs QtHelp documents"
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 optional = false
 python-versions = ">=3.9"
 files = [
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 ]
 
-[package.dependencies]
-Sphinx = ">=5"
-
 [package.extras]
 lint = ["docutils-stubs", "flake8", "mypy"]
+standalone = ["Sphinx (>=5)"]
 test = ["pytest"]
 
 [[package]]
 name = "sphinxcontrib-serializinghtml"
-version = "1.1.9"
+version = "1.1.10"
 description = "sphinxcontrib-serializinghtml is a sphinx extension which outputs \"serialized\" HTML files (json and pickle)"
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 optional = false
 python-versions = ">=3.9"
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 ]
 
-[package.dependencies]
-Sphinx = ">=5"
-
 [package.extras]
 lint = ["docutils-stubs", "flake8", "mypy"]
+standalone = ["Sphinx (>=5)"]
 test = ["pytest"]
 
 [[package]]
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 ]
 
 [package.dependencies]
@@ -4268,7 +4183,7 @@ typing-extensions = ">=4.2.0"
 [package.extras]
 aiomysql = ["aiomysql (>=0.2.0)", "greenlet (!=0.4.17)"]
 aioodbc = ["aioodbc", "greenlet (!=0.4.17)"]
-aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing-extensions (!=3.10.0.1)"]
+aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing_extensions (!=3.10.0.1)"]
 asyncio = ["greenlet (!=0.4.17)"]
 asyncmy = ["asyncmy (>=0.2.3,!=0.2.4,!=0.2.6)", "greenlet (!=0.4.17)"]
 mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5)"]
@@ -4278,7 +4193,7 @@ mssql-pyodbc = ["pyodbc"]
 mypy = ["mypy (>=0.910)"]
 mysql = ["mysqlclient (>=1.4.0)"]
 mysql-connector = ["mysql-connector-python"]
-oracle = ["cx-oracle (>=8)"]
+oracle = ["cx_oracle (>=8)"]
 oracle-oracledb = ["oracledb (>=1.0.1)"]
 postgresql = ["psycopg2 (>=2.7)"]
 postgresql-asyncpg = ["asyncpg", "greenlet (!=0.4.17)"]
@@ -4288,13 +4203,12 @@ postgresql-psycopg2binary = ["psycopg2-binary"]
 postgresql-psycopg2cffi = ["psycopg2cffi"]
 postgresql-psycopgbinary = ["psycopg[binary] (>=3.0.7)"]
 pymysql = ["pymysql"]
-sqlcipher = ["sqlcipher3-binary"]
+sqlcipher = ["sqlcipher3_binary"]
 
 [[package]]
 name = "sqlalchemy-utils"
 version = "0.41.1"
 description = "Various utility functions for SQLAlchemy."
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -4323,7 +4237,6 @@ url = ["furl (>=0.4.1)"]
 name = "stack-data"
 version = "0.6.3"
 description = "Extract data from python stack frames and tracebacks for informative displays"
-category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -4343,8 +4256,7 @@ tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 name = "swagger-ui-bundle"
 version = "0.0.9"
 description = "swagger_ui_bundle - swagger-ui files in a pip package"
-category = "main"
-optional = false
+optional = true
 python-versions = "*"
 files = [
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@@ -4358,7 +4270,6 @@ Jinja2 = ">=2.0"
 name = "synapseclient"
 version = "3.2.0"
 description = "A client for Synapse, a collaborative, open-source research platform that allows teams to share data, track analyses, and collaborate."
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -4388,7 +4299,6 @@ tests = ["flake8 (>=3.7.0,<4.0)", "func-timeout (>=4.3,<5.0)", "pytest (>=6.0.0,
 name = "tabulate"
 version = "0.9.0"
 description = "Pretty-print tabular data"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -4403,7 +4313,6 @@ widechars = ["wcwidth"]
 name = "tenacity"
 version = "8.2.3"
 description = "Retry code until it succeeds"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -4418,7 +4327,6 @@ doc = ["reno", "sphinx", "tornado (>=4.5)"]
 name = "terminado"
 version = "0.18.0"
 description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library."
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -4440,7 +4348,6 @@ typing = ["mypy (>=1.6,<2.0)", "traitlets (>=5.11.1)"]
 name = "tinycss2"
 version = "1.2.1"
 description = "A tiny CSS parser"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -4459,7 +4366,6 @@ test = ["flake8", "isort", "pytest"]
 name = "toml"
 version = "0.10.2"
 description = "Python Library for Tom's Obvious, Minimal Language"
-category = "main"
 optional = false
 python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
 files = [
@@ -4471,7 +4377,6 @@ files = [
 name = "tomli"
 version = "2.0.1"
 description = "A lil' TOML parser"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -4483,7 +4388,6 @@ files = [
 name = "tomlkit"
 version = "0.12.3"
 description = "Style preserving TOML library"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -4493,42 +4397,39 @@ files = [
 
 [[package]]
 name = "toolz"
-version = "0.12.0"
+version = "0.12.1"
 description = "List processing tools and functional utilities"
-category = "main"
 optional = false
-python-versions = ">=3.5"
+python-versions = ">=3.7"
 files = [
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 ]
 
 [[package]]
 name = "tornado"
-version = "6.3.3"
+version = "6.4"
 description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
-category = "main"
 optional = false
 python-versions = ">= 3.8"
 files = [
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-    {file = "tornado-6.3.3-cp38-abi3-win_amd64.whl", hash = "sha256:22d3c2fa10b5793da13c807e6fc38ff49a4f6e1e3868b0a6f4164768bb8e20f5"},
-    {file = "tornado-6.3.3.tar.gz", hash = "sha256:e7d8db41c0181c80d76c982aacc442c0783a2c54d6400fe028954201a2e032fe"},
+    {file = "tornado-6.4-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:02ccefc7d8211e5a7f9e8bc3f9e5b0ad6262ba2fbb683a6443ecc804e5224ce0"},
+    {file = "tornado-6.4-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:27787de946a9cffd63ce5814c33f734c627a87072ec7eed71f7fc4417bb16263"},
+    {file = "tornado-6.4-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f7894c581ecdcf91666a0912f18ce5e757213999e183ebfc2c3fdbf4d5bd764e"},
+    {file = "tornado-6.4-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e43bc2e5370a6a8e413e1e1cd0c91bedc5bd62a74a532371042a18ef19e10579"},
+    {file = "tornado-6.4-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f0251554cdd50b4b44362f73ad5ba7126fc5b2c2895cc62b14a1c2d7ea32f212"},
+    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:fd03192e287fbd0899dd8f81c6fb9cbbc69194d2074b38f384cb6fa72b80e9c2"},
+    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_i686.whl", hash = "sha256:88b84956273fbd73420e6d4b8d5ccbe913c65d31351b4c004ae362eba06e1f78"},
+    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:71ddfc23a0e03ef2df1c1397d859868d158c8276a0603b96cf86892bff58149f"},
+    {file = "tornado-6.4-cp38-abi3-win32.whl", hash = "sha256:6f8a6c77900f5ae93d8b4ae1196472d0ccc2775cc1dfdc9e7727889145c45052"},
+    {file = "tornado-6.4-cp38-abi3-win_amd64.whl", hash = "sha256:10aeaa8006333433da48dec9fe417877f8bcc21f48dda8d661ae79da357b2a63"},
+    {file = "tornado-6.4.tar.gz", hash = "sha256:72291fa6e6bc84e626589f1c29d90a5a6d593ef5ae68052ee2ef000dfd273dee"},
 ]
 
 [[package]]
 name = "tqdm"
 version = "4.66.1"
 description = "Fast, Extensible Progress Meter"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -4547,14 +4448,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "traitlets"
-version = "5.14.0"
+version = "5.14.1"
 description = "Traitlets Python configuration system"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "traitlets-5.14.0-py3-none-any.whl", hash = "sha256:f14949d23829023013c47df20b4a76ccd1a85effb786dc060f34de7948361b33"},
-    {file = "traitlets-5.14.0.tar.gz", hash = "sha256:fcdaa8ac49c04dfa0ed3ee3384ef6dfdb5d6f3741502be247279407679296772"},
+    {file = "traitlets-5.14.1-py3-none-any.whl", hash = "sha256:2e5a030e6eff91737c643231bfcf04a65b0132078dad75e4936700b213652e74"},
+    {file = "traitlets-5.14.1.tar.gz", hash = "sha256:8585105b371a04b8316a43d5ce29c098575c2e477850b62b848b964f1444527e"},
 ]
 
 [package.extras]
@@ -4563,21 +4463,19 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
 
 [[package]]
 name = "types-python-dateutil"
-version = "2.8.19.14"
+version = "2.8.19.20240106"
 description = "Typing stubs for python-dateutil"
-category = "main"
 optional = false
-python-versions = "*"
+python-versions = ">=3.8"
 files = [
-    {file = "types-python-dateutil-2.8.19.14.tar.gz", hash = "sha256:1f4f10ac98bb8b16ade9dbee3518d9ace017821d94b057a425b069f834737f4b"},
-    {file = "types_python_dateutil-2.8.19.14-py3-none-any.whl", hash = "sha256:f977b8de27787639986b4e28963263fd0e5158942b3ecef91b9335c130cb1ce9"},
+    {file = "types-python-dateutil-2.8.19.20240106.tar.gz", hash = "sha256:1f8db221c3b98e6ca02ea83a58371b22c374f42ae5bbdf186db9c9a76581459f"},
+    {file = "types_python_dateutil-2.8.19.20240106-py3-none-any.whl", hash = "sha256:efbbdc54590d0f16152fa103c9879c7d4a00e82078f6e2cf01769042165acaa2"},
 ]
 
 [[package]]
 name = "typing-extensions"
 version = "4.5.0"
 description = "Backported and Experimental Type Hints for Python 3.7+"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -4589,7 +4487,6 @@ files = [
 name = "typing-inspect"
 version = "0.9.0"
 description = "Runtime inspection utilities for typing module."
-category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -4603,21 +4500,19 @@ typing-extensions = ">=3.7.4"
 
 [[package]]
 name = "tzdata"
-version = "2023.3"
+version = "2023.4"
 description = "Provider of IANA time zone data"
-category = "main"
 optional = false
 python-versions = ">=2"
 files = [
-    {file = "tzdata-2023.3-py2.py3-none-any.whl", hash = "sha256:7e65763eef3120314099b6939b5546db7adce1e7d6f2e179e3df563c70511eda"},
-    {file = "tzdata-2023.3.tar.gz", hash = "sha256:11ef1e08e54acb0d4f95bdb1be05da659673de4acbd21bf9c69e94cc5e907a3a"},
+    {file = "tzdata-2023.4-py2.py3-none-any.whl", hash = "sha256:aa3ace4329eeacda5b7beb7ea08ece826c28d761cda36e747cfbf97996d39bf3"},
+    {file = "tzdata-2023.4.tar.gz", hash = "sha256:dd54c94f294765522c77399649b4fefd95522479a664a0cec87f41bebc6148c9"},
 ]
 
 [[package]]
 name = "tzlocal"
 version = "5.2"
 description = "tzinfo object for the local timezone"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -4635,7 +4530,6 @@ devenv = ["check-manifest", "pytest (>=4.3)", "pytest-cov", "pytest-mock (>=3.3)
 name = "uri-template"
 version = "1.3.0"
 description = "RFC 6570 URI Template Processor"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -4650,7 +4544,6 @@ dev = ["flake8", "flake8-annotations", "flake8-bandit", "flake8-bugbear", "flake
 name = "uritemplate"
 version = "4.1.1"
 description = "Implementation of RFC 6570 URI Templates"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -4662,7 +4555,6 @@ files = [
 name = "urllib3"
 version = "1.26.18"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
@@ -4677,20 +4569,18 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
 name = "uwsgi"
-version = "2.0.23"
+version = "2.0.24"
 description = "The uWSGI server"
-category = "dev"
-optional = false
+optional = true
 python-versions = "*"
 files = [
-    {file = "uwsgi-2.0.23.tar.gz", hash = "sha256:0cafda0c16f921db7fe42cfaf81b167cf884ee17350efbdd87d1ecece2d7de37"},
+    {file = "uwsgi-2.0.24.tar.gz", hash = "sha256:77b6dd5cd633f4ae87ee393f7701f617736815499407376e78f3d16467523afe"},
 ]
 
 [[package]]
 name = "validators"
 version = "0.20.0"
 description = "Python Data Validation for Humans™."
-category = "main"
 optional = false
 python-versions = ">=3.4"
 files = [
@@ -4705,21 +4595,19 @@ test = ["flake8 (>=2.4.0)", "isort (>=4.2.2)", "pytest (>=2.2.3)"]
 
 [[package]]
 name = "wcwidth"
-version = "0.2.12"
+version = "0.2.13"
 description = "Measures the displayed width of unicode strings in a terminal"
-category = "main"
 optional = false
 python-versions = "*"
 files = [
-    {file = "wcwidth-0.2.12-py2.py3-none-any.whl", hash = "sha256:f26ec43d96c8cbfed76a5075dac87680124fa84e0855195a6184da9c187f133c"},
-    {file = "wcwidth-0.2.12.tar.gz", hash = "sha256:f01c104efdf57971bcb756f054dd58ddec5204dd15fa31d6503ea57947d97c02"},
+    {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"},
+    {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"},
 ]
 
 [[package]]
 name = "webcolors"
 version = "1.13"
 description = "A library for working with the color formats defined by HTML and CSS."
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -4735,7 +4623,6 @@ tests = ["pytest", "pytest-cov"]
 name = "webencodings"
 version = "0.5.1"
 description = "Character encoding aliases for legacy web content"
-category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -4745,14 +4632,13 @@ files = [
 
 [[package]]
 name = "websocket-client"
-version = "1.6.4"
+version = "1.7.0"
 description = "WebSocket client for Python with low level API options"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "websocket-client-1.6.4.tar.gz", hash = "sha256:b3324019b3c28572086c4a319f91d1dcd44e6e11cd340232978c684a7650d0df"},
-    {file = "websocket_client-1.6.4-py3-none-any.whl", hash = "sha256:084072e0a7f5f347ef2ac3d8698a5e0b4ffbfcab607628cadabc650fc9a83a24"},
+    {file = "websocket-client-1.7.0.tar.gz", hash = "sha256:10e511ea3a8c744631d3bd77e61eb17ed09304c413ad42cf6ddfa4c7787e8fe6"},
+    {file = "websocket_client-1.7.0-py3-none-any.whl", hash = "sha256:f4c3d22fec12a2461427a29957ff07d35098ee2d976d3ba244e688b8b4057588"},
 ]
 
 [package.extras]
@@ -4764,8 +4650,7 @@ test = ["websockets"]
 name = "werkzeug"
 version = "2.1.2"
 description = "The comprehensive WSGI web application library."
-category = "main"
-optional = false
+optional = true
 python-versions = ">=3.7"
 files = [
     {file = "Werkzeug-2.1.2-py3-none-any.whl", hash = "sha256:72a4b735692dd3135217911cbeaa1be5fa3f62bffb8745c5215420a03dc55255"},
@@ -4777,21 +4662,19 @@ watchdog = ["watchdog"]
 
 [[package]]
 name = "widgetsnbextension"
-version = "4.0.9"
+version = "4.0.10"
 description = "Jupyter interactive widgets for Jupyter Notebook"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "widgetsnbextension-4.0.9-py3-none-any.whl", hash = "sha256:91452ca8445beb805792f206e560c1769284267a30ceb1cec9f5bcc887d15175"},
-    {file = "widgetsnbextension-4.0.9.tar.gz", hash = "sha256:3c1f5e46dc1166dfd40a42d685e6a51396fd34ff878742a3e47c6f0cc4a2a385"},
+    {file = "widgetsnbextension-4.0.10-py3-none-any.whl", hash = "sha256:d37c3724ec32d8c48400a435ecfa7d3e259995201fbefa37163124a9fcb393cc"},
+    {file = "widgetsnbextension-4.0.10.tar.gz", hash = "sha256:64196c5ff3b9a9183a8e699a4227fb0b7002f252c814098e66c4d1cd0644688f"},
 ]
 
 [[package]]
 name = "wrapt"
 version = "1.16.0"
 description = "Module for decorators, wrappers and monkey patching."
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -4871,7 +4754,6 @@ files = [
 name = "zipp"
 version = "3.17.0"
 description = "Backport of pathlib-compatible object wrapper for zip files"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -4883,7 +4765,11 @@ files = [
 docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
 testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
 
+[extras]
+api = ["Flask", "Flask-Cors", "Jinja2", "connexion"]
+aws = ["uWSGI"]
+
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9.0,<3.11"
-content-hash = "7123714075e813a493e59782fa8922650a7b44835cf5656d029a4130d139b636"
+content-hash = "fd6dbe19c700a80fedc739825f3c26d63476360d1a5f605f8abc2726ce9c3157"
diff --git a/pyproject.toml b/pyproject.toml
index 205030f32..90aa08de7 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -49,31 +49,37 @@ jsonschema = "^4.0.0"
 networkx = ">=2.2.8"
 numpy = "^1.21.1"
 oauth2client = "^4.1.0"  # Specified because of bug in version ^4.0.0
-pandas = "^1.3.1"
+pandas = "^2.0.0"
 pygsheets = "^2.0.4"
 PyYAML = "^6.0.0"
 rdflib = "^6.0.0"
 setuptools = "^66.0.0"
-synapseclient = "^3.1.1"
+synapseclient = "^3.2.0"
 tenacity = "^8.0.1"
 toml = "^0.10.2"
-Flask = "^2.0.0"
-connexion = {extras = ["swagger-ui"], version = "^2.8.0"}
 great-expectations = "^0.15.0"
 sphinx-click = "^4.0.0"
 MarkupSafe = "2.1.0"
 itsdangerous = "^2.0.0"
-Jinja2 = ">2.11.3"
 openpyxl = "^3.0.9"
 "backports.zoneinfo" = {markers = "python_version < \"3.9\"", version = "^0.2.1"}
-Flask-Cors = "^3.0.10"
 pdoc = "^12.2.0"
 dateparser = "^1.1.4"
 pandarallel = "^1.6.4"
-schematic-db = {version = "0.0.dev33", extras = ["synapse"]}
+schematic-db = {version = "0.0.34", extras = ["synapse"]}
 pyopenssl = "^23.0.0"
 typing-extensions = "<4.6.0"
 dataclasses-json = "^0.6.1"
+connexion = {extras = ["swagger-ui"], version = "^2.8.0", optional = true}
+Flask = {version = "^2.0.0", optional = true}
+Flask-Cors = {version = "^3.0.10", optional = true}
+uWSGI = {version = "^2.0.21", optional = true}
+Jinja2 = {version = ">2.11.3", optional = true}
+
+[tool.poetry.extras]
+api = ["connexion", "Flask", "Flask-Cors", "Jinja2"]
+aws = ["uWSGI"]
+
 
 [tool.poetry.group.dev.dependencies]
 pytest = "^7.0.0"
@@ -91,7 +97,7 @@ pytest-xdist = "^3.5.0"
 optional = true
 
 [tool.poetry.group.aws.dependencies]
-uWSGI = "^2.0.21"
+
 
 [tool.black]
 line-length = 88
diff --git a/schematic/__main__.py b/schematic/__main__.py
index c03219524..fa0ee9a23 100644
--- a/schematic/__main__.py
+++ b/schematic/__main__.py
@@ -22,6 +22,7 @@
 # dict() -> new empty dictionary
 CONTEXT_SETTINGS = dict(help_option_names=["--help", "-h"])  # help options
 
+
 # invoke_without_command=True -> forces the application not to show aids before losing them with a --h
 @click.group(context_settings=CONTEXT_SETTINGS, invoke_without_command=True)
 @click_log.simple_verbosity_option(logger)
@@ -40,6 +41,5 @@ def main():
 main.add_command(viz_cli)  # add viz commands
 
 
-
 if __name__ == "__main__":
     main()
diff --git a/schematic/configuration/configuration.py b/schematic/configuration/configuration.py
index c31007672..1bd3f1c40 100644
--- a/schematic/configuration/configuration.py
+++ b/schematic/configuration/configuration.py
@@ -83,13 +83,14 @@ def load_config(self, config_path: str) -> None:
         self._google_sheets_config = GoogleSheetsConfig(
             **config.get("google_sheets", {})
         )
-        self._set_asset_store(config.get("asset_store", {}))
+        asset_store_config = config.get("asset_store", None)
+        if asset_store_config:
+            self._set_asset_store(asset_store_config)
 
     def _set_asset_store(self, config: dict[str, Any]) -> None:
         allowed_config_fields = {"synapse"}
-        if not config:
-            pass
-        if not set(config.keys()).issubset(allowed_config_fields):
+        all_fields_are_valid = set(config.keys()).issubset(allowed_config_fields)
+        if not all_fields_are_valid:
             raise ConfigNonAllowedFieldError(
                 "Non allowed fields in asset_store of configuration file.",
                 list(config.keys()),
@@ -181,6 +182,15 @@ def service_account_credentials_path(self) -> str:
             self._google_sheets_config.service_acct_creds, self._parent_directory
         )
 
+    @service_account_credentials_path.setter
+    def service_account_credentials_path(self, path: str) -> None:
+        """Sets the path of the Google service account credentials.
+
+        Args:
+            path (str): The path of the Google service account credentials.
+        """
+        self._google_sheets_config.service_acct_creds = path
+
     @property
     def google_sheets_master_template_id(self) -> str:
         """
diff --git a/schematic/help.py b/schematic/help.py
index c243a10ab..a7adcfc77 100644
--- a/schematic/help.py
+++ b/schematic/help.py
@@ -54,6 +54,12 @@
                 "Specify to alphabetize valid attribute values either ascending (a) or descending (d)."
                 "Optional"
             ),
+            "data_model_labels": (
+                "Choose how to set the label in the data model. "
+                "display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label. "
+                "class_label, default, use standard class or property label. "
+                "Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly."
+            ),
         },
         "migrate": {
             "short_help": (
@@ -101,11 +107,6 @@
                 "The component or data type from the data model which you can use to validate the "
                 "data filled in your manifest template."
             ),
-            "use_schema_label": (
-                "Store attributes using the schema label (--use_schema_label, default) or store attributes using the display label "
-                "(--use_display_label). Attribute display names in the schema must not only include characters that are "
-                "not accepted by Synapse. Annotation names may only contain: letters, numbers, '_' and '.'"
-            ),
             "hide_blanks": (
                 "This is a boolean flag. If flag is provided when command line utility is executed, annotations with blank values will be hidden from a dataset's annotation list in Synaspe."
                 "If not, annotations with blank values will be displayed."
@@ -127,7 +128,22 @@
                 "'upsert' should be used for initial table uploads if users intend to upsert into them at a later time."
                 "Using 'upsert' at creation will generate the metadata necessary for upsert functionality."
                 "Upsert functionality requires primary keys to be specified in the data model and manfiest as <component>_id."
-                "Currently it is required to use -dl/--use_display_label with table upserts."
+                "Currently it is required to use --table_column_names = display_name with table upserts."
+            ),
+            "annotation_keys": (
+                "Store attributes using the class label (default) or store attributes using the display label. "
+                "Attribute display names in the schema must not only include characters that are "
+                "not accepted by Synapse. Annotation names may only contain: letters, numbers, '_' and '.'"
+            ),
+            "table_column_names": (
+                "class_label, display_label, display_name, default, class_label. When true annotations and table columns will be uploaded with the display name formatting with blacklisted characters removed. "
+                "To use for tables, use in conjunction with the use_schema_label flag."
+            ),
+            "data_model_labels": (
+                "Choose how to set the label in the data model. "
+                "display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label. "
+                "class_label, default, use standard class or property label. "
+                "Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly."
             ),
         },
         "validate": {
@@ -154,6 +170,12 @@
             "project_scope": (
                 "Specify a comma-separated list of projects to search through for cross manifest validation."
             ),
+            "data_model_labels": (
+                "Choose how to set the label in the data model. "
+                "display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label. "
+                "class_label, default, use standard class or property label. "
+                "Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly."
+            ),
         },
     }
 }
@@ -169,6 +191,12 @@
             "output_jsonld": (
                 "Path to where the generated JSON-LD file needs to be outputted."
             ),
+            "data_model_labels": (
+                "Choose how to set the label in the data model. "
+                "display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label. "
+                "class_label, default, use standard class or property label. "
+                "Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly."
+            ),
         }
     }
 }
@@ -196,6 +224,12 @@
             "text_format": (
                 "Specify the type of text to gather for tangled tree visualization, either 'plain' or 'highlighted'."
             ),
+            "data_model_labels": (
+                "Choose how to set the label in the data model. "
+                "display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label. "
+                "class_label, default, use standard class or property label. "
+                "Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly."
+            ),
         },
     }
 }
diff --git a/schematic/manifest/commands.py b/schematic/manifest/commands.py
index 1f916b05c..fcf0c1b4b 100644
--- a/schematic/manifest/commands.py
+++ b/schematic/manifest/commands.py
@@ -10,18 +10,19 @@
 from schematic.schemas.data_model_graph import DataModelGraph, DataModelGraphExplorer
 from schematic.manifest.generator import ManifestGenerator
 
-from schematic.utils.cli_utils import log_value_from_config, query_dict, parse_synIDs
+from schematic.utils.cli_utils import log_value_from_config, query_dict, parse_syn_ids
 from schematic.utils.google_api_utils import export_manifest_csv
 from schematic.help import manifest_commands
 
 from schematic.store.synapse import SynapseStorage
 from schematic.configuration.configuration import CONFIG
 
-logger = logging.getLogger('schematic')
+logger = logging.getLogger("schematic")
 click_log.basic_config(logger)
 
 CONTEXT_SETTINGS = dict(help_option_names=["--help", "-h"])  # help options
 
+
 # invoke_without_command=True -> forces the application not to show aids before losing them with a --h
 @click.group(context_settings=CONTEXT_SETTINGS, invoke_without_command=True)
 @click_log.simple_verbosity_option(logger)
@@ -62,7 +63,9 @@ def manifest(ctx, config):  # use as `schematic manifest ...`
     help=query_dict(manifest_commands, ("manifest", "get", "data_type")),
 )
 @click.option(
-    "-p", "--path_to_data_model", help=query_dict(manifest_commands, ("manifest", "get", "path_to_data_model"))
+    "-p",
+    "--path_to_data_model",
+    help=query_dict(manifest_commands, ("manifest", "get", "path_to_data_model")),
 )
 @click.option(
     "-d",
@@ -99,9 +102,16 @@ def manifest(ctx, config):  # use as `schematic manifest ...`
 @click.option(
     "-av",
     "--alphabetize_valid_values",
-    default = 'ascending',
+    default="ascending",
     help=query_dict(manifest_commands, ("manifest", "get", "alphabetize_valid_values")),
 )
+@click.option(
+    "--data_model_labels",
+    "-dml",
+    default="class_label",
+    type=click.Choice(["display_label", "class_label"], case_sensitive=True),
+    help=query_dict(manifest_commands, ("manifest", "get", "data_model_labels")),
+)
 @click.pass_obj
 def get_manifest(
     ctx,
@@ -115,6 +125,7 @@ def get_manifest(
     json_schema,
     output_xlsx,
     alphabetize_valid_values,
+    data_model_labels,
 ):
     """
     Running CLI with manifest generation options.
@@ -122,23 +133,23 @@ def get_manifest(
     # Optional parameters that need to be passed to ManifestGenerator()
     # If CLI parameters are None they are gotten from the CONFIG object and logged
     if data_type is None:
-        data_type =  CONFIG.manifest_data_type
+        data_type = CONFIG.manifest_data_type
         log_value_from_config("data_type", data_type)
     if path_to_data_model is None:
-        path_to_data_model =  CONFIG.model_location
+        path_to_data_model = CONFIG.model_location
         log_value_from_config("path_to_data_model", path_to_data_model)
     if title is None:
-        title =  CONFIG.manifest_title
+        title = CONFIG.manifest_title
         log_value_from_config("title", title)
 
-    data_model_parser = DataModelParser(path_to_data_model = path_to_data_model)
+    data_model_parser = DataModelParser(path_to_data_model=path_to_data_model)
 
-    #Parse Model
+    # Parse Model
     logger.info("Parsing data model.")
     parsed_data_model = data_model_parser.parse_model()
 
     # Instantiate DataModelGraph
-    data_model_grapher = DataModelGraph(parsed_data_model)
+    data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
     # Generate graph
     logger.info("Generating data model graph.")
@@ -148,7 +159,7 @@ def create_single_manifest(data_type, output_csv=None, output_xlsx=None):
         # create object of type ManifestGenerator
         manifest_generator = ManifestGenerator(
             path_to_data_model=path_to_data_model,
-            graph = graph_data_model,
+            graph=graph_data_model,
             title=t,
             root=data_type,
             use_annotations=use_annotations,
@@ -157,7 +168,7 @@ def create_single_manifest(data_type, output_csv=None, output_xlsx=None):
 
         # call get_manifest() on manifest_generator
         # if output_xlsx gets specified, output_format = "excel"
-        if output_xlsx: 
+        if output_xlsx:
             output_format = "excel"
             # if file name is in the path, and that file does not exist
             if not os.path.exists(output_xlsx):
@@ -170,27 +181,31 @@ def create_single_manifest(data_type, output_csv=None, output_xlsx=None):
                         )
                 else:
                     raise ValueError(
-                            f"{output_xlsx} does not exists. Please try a valid file path"
-                        )
+                        f"{output_xlsx} does not exists. Please try a valid file path"
+                    )
             else:
                 # Check if base path itself exists.
                 if not os.path.exists(os.path.dirname(output_xlsx)):
                     raise ValueError(
-                    f"{output_xlsx} does not exists. Please try a valid file path"
+                        f"{output_xlsx} does not exists. Please try a valid file path"
                     )
                 output_path = output_xlsx
-        else: 
+        else:
             output_format = None
             output_path = None
 
         result = manifest_generator.get_manifest(
-            dataset_id=dataset_id, sheet_url=sheet_url, json_schema=json_schema, output_format = output_format, output_path = output_path
+            dataset_id=dataset_id,
+            sheet_url=sheet_url,
+            json_schema=json_schema,
+            output_format=output_format,
+            output_path=output_path,
         )
 
         if sheet_url:
             logger.info("Find the manifest template using this Google Sheet URL:")
             click.echo(result)
-        if output_csv is None and output_xlsx is None: 
+        if output_csv is None and output_xlsx is None:
             prefix, _ = os.path.splitext(path_to_data_model)
             prefix_root, prefix_ext = os.path.splitext(prefix)
             if prefix_ext == ".model":
@@ -204,37 +219,41 @@ def create_single_manifest(data_type, output_csv=None, output_xlsx=None):
             return result
         export_manifest_csv(file_path=output_csv, manifest=result)
         logger.info(
-                f"Find the manifest template using this CSV file path: {output_csv}"
-            )
+            f"Find the manifest template using this CSV file path: {output_csv}"
+        )
         return result
 
     if type(data_type) is str:
         data_type = [data_type]
 
-    if data_type[0] == 'all manifests':      
+    if data_type[0] == "all manifests":
         # Feed graph into the data model graph explorer
         dmge = DataModelGraphExplorer(graph_data_model)
-        component_digraph = dmge.get_digraph_by_edge_type('requiresComponent')
+        component_digraph = dmge.get_digraph_by_edge_type("requiresComponent")
         components = component_digraph.nodes()
         for component in components:
-            t = f'{title}.{component}.manifest'
-            result = create_single_manifest(data_type = component)
+            t = f"{title}.{component}.manifest"
+            result = create_single_manifest(data_type=component)
     else:
         for dt in data_type:
             if len(data_type) > 1 and not output_xlsx:
-                t = f'{title}.{dt}.manifest'
-            elif output_xlsx: 
+                t = f"{title}.{dt}.manifest"
+            elif output_xlsx:
                 if ".xlsx" or ".xls" in output_xlsx:
                     title_with_extension = os.path.basename(output_xlsx)
-                    t = title_with_extension.split('.')[0]
+                    t = title_with_extension.split(".")[0]
             else:
                 t = title
-            result = create_single_manifest(data_type = dt, output_csv=output_csv, output_xlsx=output_xlsx)
+            result = create_single_manifest(
+                data_type=dt, output_csv=output_csv, output_xlsx=output_xlsx
+            )
 
     return result
 
+
 @manifest.command(
-    "migrate", short_help=query_dict(manifest_commands, ("manifest", "migrate", "short_help"))
+    "migrate",
+    short_help=query_dict(manifest_commands, ("manifest", "migrate", "short_help")),
 )
 @click_log.simple_verbosity_option(logger)
 # define the optional arguments
@@ -242,7 +261,7 @@ def create_single_manifest(data_type, output_csv=None, output_xlsx=None):
     "-ps",
     "--project_scope",
     default=None,
-    callback=parse_synIDs,
+    callback=parse_syn_ids,
     help=query_dict(manifest_commands, ("manifest", "migrate", "project_scope")),
 )
 @click.option(
@@ -281,18 +300,22 @@ def migrate_manifests(
     Running CLI with manifest migration options.
     """
     if jsonld is None:
-        jsonld =  CONFIG.model_location
+        jsonld = CONFIG.model_location
         log_value_from_config("jsonld", jsonld)
 
     full_scope = project_scope + [archive_project]
-    synStore = SynapseStorage(project_scope = full_scope)  
+    synStore = SynapseStorage(project_scope=full_scope)
 
     for project in project_scope:
         if not return_entities:
             logging.info("Re-uploading manifests as tables")
-            synStore.upload_annotated_project_manifests_to_synapse(project, jsonld, dry_run)
+            synStore.upload_annotated_project_manifests_to_synapse(
+                project, jsonld, dry_run
+            )
         if archive_project:
             logging.info("Migrating entitites")
-            synStore.move_entities_to_new_project(project, archive_project, return_entities, dry_run)
-        
-    return 
+            synStore.move_entities_to_new_project(
+                project, archive_project, return_entities, dry_run
+            )
+
+    return
diff --git a/schematic/manifest/generator.py b/schematic/manifest/generator.py
index 049941ff2..dea6a44d6 100644
--- a/schematic/manifest/generator.py
+++ b/schematic/manifest/generator.py
@@ -10,8 +10,7 @@
 from pathlib import Path
 import pygsheets as ps
 from tempfile import NamedTemporaryFile
-from typing import Dict, List, Optional, Tuple, Union, BinaryIO, Literal
-from flask import send_from_directory
+from typing import Any, Dict, List, Optional, Tuple, Union, BinaryIO, Literal
 
 from schematic.schemas.data_model_graph import DataModelGraph, DataModelGraphExplorer
 from schematic.schemas.data_model_parser import DataModelParser
@@ -22,9 +21,11 @@
     build_service_account_creds,
 )
 from schematic.utils.df_utils import update_df, load_df
+from schematic.utils.schema_utils import extract_component_validation_rules
 from schematic.utils.validate_utils import rule_in_rule_list
+from schematic.utils.schema_utils import DisplayLabelType
 
-#TODO: This module should only be aware of the store interface
+# TODO: This module should only be aware of the store interface
 # we shouldn't need to expose Synapse functionality explicitly
 from schematic.store.synapse import SynapseStorage
 
@@ -35,13 +36,12 @@
 logger = logging.getLogger(__name__)
 
 
-
 class ManifestGenerator(object):
     def __init__(
         self,
         path_to_data_model: str,  # JSON-LD file to be used for generating the manifest
-        graph: nx.MultiDiGraph, # At this point, the graph is fully formed.
-        alphabetize_valid_values: str = 'ascending',
+        graph: nx.MultiDiGraph,  # At this point, the graph is fully formed.
+        alphabetize_valid_values: str = "ascending",
         title: str = None,  # manifest sheet title
         root: str = None,
         additional_metadata: Dict = None,
@@ -95,15 +95,17 @@ def __init__(
 
         # additional metadata to add to manifest
         self.additional_metadata = additional_metadata
-   
+
         # Check if the class is in the schema
         root_in_schema = self.dmge.is_class_in_schema(self.root)
-        
+
         # If the class could not be found, give a notification
         if not root_in_schema:
-            exception_message = f"The DataType entered ({self.root}) could not be found in the data model schema. " + \
-                                "Please confirm that the datatype is in the data model and that the spelling matches the class label in the .jsonld file."
-            raise LookupError(exception_message) 
+            exception_message = (
+                f"The DataType entered ({self.root}) could not be found in the data model schema. "
+                + "Please confirm that the datatype is in the data model and that the spelling matches the class label in the .jsonld file."
+            )
+            raise LookupError(exception_message)
 
         # Determine whether current data type is file-based
         self.is_file_based = "Filename" in self.dmge.get_node_dependencies(self.root)
@@ -192,7 +194,7 @@ def _gdrive_copy_file(self, origin_file_id, copy_title):
             .execute()["id"]
         )
 
-    def _create_empty_manifest_spreadsheet(self, title:str) -> str:
+    def _create_empty_manifest_spreadsheet(self, title: str) -> str:
         """
         Creates an empty google spreadsheet returning the id.
         If the configuration has a template id it will be used
@@ -209,21 +211,18 @@ def _create_empty_manifest_spreadsheet(self, title:str) -> str:
             spreadsheet_id = self._gdrive_copy_file(template_id, title)
 
         else:
-            spreadsheet_body = {
-                'properties': {
-                    'title': title
-                }
-            }
+            spreadsheet_body = {"properties": {"title": title}}
 
-            spreadsheet_id = self.sheet_service.spreadsheets().create(
-                body=spreadsheet_body,
-                fields="spreadsheetId").execute().get("spreadsheetId"
+            spreadsheet_id = (
+                self.sheet_service.spreadsheets()
+                .create(body=spreadsheet_body, fields="spreadsheetId")
+                .execute()
+                .get("spreadsheetId")
             )
 
         return spreadsheet_id
 
     def _get_cell_borders(self, cell_range):
-
         # set border style request
         color = {
             "red": 226.0 / 255.0,
@@ -259,26 +258,30 @@ def callback(request_id, response, exception):
 
         batch.add(
             self.drive_service.permissions().create(
-                fileId=fileId, body=worldPermission, fields="id",
+                fileId=fileId,
+                body=worldPermission,
+                fields="id",
             )
         )
         batch.execute()
 
-    def _store_valid_values_as_data_dictionary(self, column_id:int, valid_values:list, spreadsheet_id:str) -> list:
-        '''store valid values in google sheet (sheet 2). This step is required for "ONE OF RANGE" validation
+    def _store_valid_values_as_data_dictionary(
+        self, column_id: int, valid_values: list, spreadsheet_id: str
+    ) -> list:
+        """store valid values in google sheet (sheet 2). This step is required for "ONE OF RANGE" validation
         Args:
             column_id: id of column
             valid_values: a list of valid values for a given attribute (i.e. for diagnosis, this looks like: [{'userEnteredValue': 'Cancer'}, {'userEnteredValue': 'Healthy'}])
             spreadsheet_id: google spreadsheet id
-        
+
         return: range of valid values (i.e. for diagnosis, [{'userEnteredValue': '=Sheet2!D2:D3'}])
-        '''
+        """
         # get valid values w/o google sheet header
         values = [valid_value["userEnteredValue"] for valid_value in valid_values]
-        
-        if self.alphabetize and self.alphabetize.lower().startswith('a'):
+
+        if self.alphabetize and self.alphabetize.lower().startswith("a"):
             values.sort(reverse=False, key=str.lower)
-        elif self.alphabetize and self.alphabetize.lower().startswith('d'):
+        elif self.alphabetize and self.alphabetize.lower().startswith("d"):
             values.sort(reverse=True, key=str.lower)
 
         # store valid values explicitly in workbook at the provided range to use as validation values
@@ -310,18 +313,19 @@ def _get_column_data_validation_values(
         spreadsheet_id,
         valid_values,
         column_id,
-        strict:Optional[bool],
+        strict: Optional[bool],
         validation_type="ONE_OF_LIST",
         custom_ui=True,
         input_message="Choose one from dropdown",
     ):
-
         # set validation strictness to config file default if None indicated.
         if strict == None:
             strict = CONFIG.google_sheets_strict_validation
-        #store valid values explicitly in workbook at the provided range to use as validation values
+        # store valid values explicitly in workbook at the provided range to use as validation values
         if validation_type == "ONE_OF_RANGE":
-            valid_values=self._store_valid_values_as_data_dictionary(column_id, valid_values, spreadsheet_id)
+            valid_values = self._store_valid_values_as_data_dictionary(
+                column_id, valid_values, spreadsheet_id
+            )
 
         # setup validation data request body
         validation_body = {
@@ -367,7 +371,6 @@ def _get_valid_values_from_jsonschema_property(self, prop: dict) -> List[str]:
         else:
             return []
 
-
     def _get_json_schema(self, json_schema_filepath: str) -> Dict:
         """Open json schema as a dictionary.
         Args:
@@ -378,8 +381,12 @@ def _get_json_schema(self, json_schema_filepath: str) -> Dict:
         """
         if not json_schema_filepath:
             # TODO Catch error if no JSONLD or JSON path provided.
-            data_model_js = DataModelJSONSchema(jsonld_path=self.model_path, graph=self.graph)
-            json_schema = data_model_js.get_json_validation_schema(source_node=self.root, schema_name=self.title)
+            data_model_js = DataModelJSONSchema(
+                jsonld_path=self.model_path, graph=self.graph
+            )
+            json_schema = data_model_js.get_json_validation_schema(
+                source_node=self.root, schema_name=self.title
+            )
         else:
             with open(json_schema_filepath) as jsonfile:
                 json_schema = json.load(jsonfile)
@@ -477,7 +484,7 @@ def _add_root_to_component(self, required_metadata_fields: Dict[str, List]):
             # constructor (it's optional) if not, instantiate it
             if not self.additional_metadata:
                 self.additional_metadata = {}
-            if self.is_file_based and 'Filename' in self.additional_metadata:
+            if self.is_file_based and "Filename" in self.additional_metadata:
                 self.additional_metadata["Component"] = [self.root] * max(
                     1, len(self.additional_metadata["Filename"])
                 )
@@ -691,7 +698,7 @@ def _request_update_base_color(self, i: int, color={"red": 1.0}):
         }
         return vr_format_body
 
-    def _request_regex_vr(self, gs_formula, i:int, text_color={"red": 1}):
+    def _request_regex_vr(self, gs_formula, i: int, text_color={"red": 1}):
         """
         Generate request to change font color to black upon corretly formatted
         user entry.
@@ -712,9 +719,7 @@ def _request_regex_vr(self, gs_formula, i:int, text_color={"red": 1}):
                                     "values": gs_formula,
                                 },
                                 "format": {
-                                    "textFormat": {
-                                        "foregroundColor": text_color
-                                    }
+                                    "textFormat": {"foregroundColor": text_color}
                                 },
                             },
                         },
@@ -725,9 +730,14 @@ def _request_regex_vr(self, gs_formula, i:int, text_color={"red": 1}):
         }
         return requests_vr
 
-    def _request_regex_match_vr_formatting(self, validation_rules: List[str], i: int,
-        spreadsheet_id: str, requests_body: dict, strict: Optional[bool],
-        ):
+    def _request_regex_match_vr_formatting(
+        self,
+        validation_rules: List[str],
+        i: int,
+        spreadsheet_id: str,
+        requests_body: dict,
+        strict: Optional[bool],
+    ):
         """
         Purpose:
             - Apply regular expression validaiton rules to google sheets.
@@ -785,7 +795,7 @@ def _request_regex_match_vr_formatting(self, validation_rules: List[str], i: int
                     "red": 232.0 / 255.0,
                     "green": 80.0 / 255.0,
                     "blue": 70.0 / 255.0,
-                }
+                },
             )
 
             ## Create request to for conditionally formatting user input.
@@ -802,16 +812,11 @@ def _request_regex_match_vr_formatting(self, validation_rules: List[str], i: int
                 validation_type="CUSTOM_FORMULA",
             )
 
-            requests_body["requests"].append(
-                requests_vr_format_body["requests"]
-            )
+            requests_body["requests"].append(requests_vr_format_body["requests"])
             requests_body["requests"].append(requests_vr["requests"])
-            requests_body["requests"].append(
-                requests_data_validation_vr["requests"]
-            )
+            requests_body["requests"].append(requests_data_validation_vr["requests"])
         return requests_body
 
-
     def _request_row_format(self, i, req):
         """Adding description to headers, this is not executed if
         only JSON schema is defined. Also formatting required columns.
@@ -824,7 +829,7 @@ def _request_row_format(self, i, req):
         """
         if self.dmge:
             # get node definition
-            note = self.dmge.get_node_comment(node_display_name = req)
+            note = self.dmge.get_node_comment(node_display_name=req)
 
             notes_body = {
                 "requests": [
@@ -866,7 +871,7 @@ def _request_note_valid_values(self, i, req, validation_rules, valid_values):
             notes_body["requests"] (dict): with information on note
                 to add to the column header, about using multiselect.
                 This notes body will be added to a request.
-        """            
+        """
         if rule_in_rule_list("list", validation_rules) and valid_values:
             note = "Please enter applicable comma-separated items selected from the set of allowable terms for this attribute. See our data standards for allowable terms"
             notes_body = {
@@ -886,7 +891,9 @@ def _request_note_valid_values(self, i, req, validation_rules, valid_values):
             }
             return notes_body["requests"]
         elif rule_in_rule_list("list", validation_rules) and not valid_values:
-            note = "Please enter values as a comma separated list. For example: XX, YY, ZZ"
+            note = (
+                "Please enter values as a comma separated list. For example: XX, YY, ZZ"
+            )
             notes_body = {
                 "requests": [
                     {
@@ -989,8 +996,12 @@ def _request_dropdown(
         return validation_body["requests"]
 
     def _dependency_formatting(
-        self, i, req_val, ordered_metadata_fields, val_dependencies,
-        dependency_formatting_body
+        self,
+        i,
+        req_val,
+        ordered_metadata_fields,
+        val_dependencies,
+        dependency_formatting_body,
     ):
         """If there are additional attribute dependencies find the corresponding
         fields that need to be filled in and construct conditional formatting rules
@@ -1043,9 +1054,7 @@ def _dependency_formatting(
                     "index": 0,
                 }
             }
-            dependency_formatting_body["requests"].append(
-                            conditional_format_rule
-                        )
+            dependency_formatting_body["requests"].append(conditional_format_rule)
         return dependency_formatting_body["requests"]
 
     def _request_dependency_formatting(
@@ -1082,14 +1091,15 @@ def _request_dependency_formatting(
             # set conditiaon formatting for dependencies.
             if val_dependencies:
                 dependency_formatting_body["requests"] = self._dependency_formatting(
-                    i, req_val, ordered_metadata_fields, val_dependencies,
-                    dependency_formatting_body
+                    i,
+                    req_val,
+                    ordered_metadata_fields,
+                    val_dependencies,
+                    dependency_formatting_body,
                 )
 
             if dependency_formatting_body["requests"]:
-                requests_body["requests"].append(
-                    dependency_formatting_body["requests"]
-                )
+                requests_body["requests"].append(dependency_formatting_body["requests"])
         return requests_body
 
     def _create_requests_body(
@@ -1125,13 +1135,19 @@ def _create_requests_body(
         requests_body["requests"] = []
         for i, req in enumerate(ordered_metadata_fields[0]):
             # Gather validation rules and valid values for attribute.
-            validation_rules = self.dmge.get_node_validation_rules(node_display_name=req)
-            
+            validation_rules = self.dmge.get_node_validation_rules(
+                node_display_name=req
+            )
+            if isinstance(validation_rules, dict):
+                validation_rules = extract_component_validation_rules(
+                    validation_rules=validation_rules, manifest_component=self.root
+                )
+
             # Add regex match validaiton rule to Google Sheets.
             if validation_rules and sheet_url:
-                requests_body =self._request_regex_match_vr_formatting(
-                        validation_rules, i, spreadsheet_id, requests_body, strict
-                        )
+                requests_body = self._request_regex_match_vr_formatting(
+                    validation_rules, i, spreadsheet_id, requests_body, strict
+                )
 
             if req in json_schema["properties"].keys():
                 valid_values = self._get_valid_values_from_jsonschema_property(
@@ -1146,7 +1162,9 @@ def _create_requests_body(
                 requests_body["requests"].append(get_row_formatting)
 
             # set color of required columns to blue
-            required_columns_color = self._set_required_columns_color(i, req, json_schema)
+            required_columns_color = self._set_required_columns_color(
+                i, req, json_schema
+            )
             if required_columns_color:
                 requests_body["requests"].append(required_columns_color)
             # Add note on how to use multi-select, when appropriate
@@ -1165,28 +1183,37 @@ def _create_requests_body(
             # for attributes that don't require "list", create dropdown options and set up data validation rules
             if not rule_in_rule_list("list", validation_rules):
                 create_dropdown = self._request_dropdown(
-                i, req_vals, spreadsheet_id, validation_rules, valid_values
-            )
+                    i, req_vals, spreadsheet_id, validation_rules, valid_values
+                )
                 if create_dropdown:
                     requests_body["requests"].append(create_dropdown)
 
             # for attributes that require "list", simply store valid values (if any) in second sheet
-            elif len(req_vals)>0 and rule_in_rule_list("list", validation_rules):
+            elif len(req_vals) > 0 and rule_in_rule_list("list", validation_rules):
                 self._store_valid_values_as_data_dictionary(i, req_vals, spreadsheet_id)
 
             # generate a conditional format rule for each required value (i.e. valid value)
             # for this field (i.e. if this field is set to a valid value that may require additional
             # fields to be filled in, these additional fields will be formatted in a custom style (e.g. red background)
 
-            requests_body = self._request_dependency_formatting(i, req_vals, ordered_metadata_fields, requests_body)
-           
+            requests_body = self._request_dependency_formatting(
+                i, req_vals, ordered_metadata_fields, requests_body
+            )
+
         # Set borders formatting
         borders_formatting = self._request_cell_borders()
         if borders_formatting:
             requests_body["requests"].append(borders_formatting)
         return requests_body
 
-    def _create_empty_gs(self, required_metadata_fields, json_schema, spreadsheet_id, sheet_url, strict: Optional[bool]):
+    def _create_empty_gs(
+        self,
+        required_metadata_fields,
+        json_schema,
+        spreadsheet_id,
+        sheet_url,
+        strict: Optional[bool],
+    ):
         """Generate requests to add columns and format the google sheet.
         Args:
             required_metadata_fields(dict):
@@ -1262,7 +1289,12 @@ def _gather_all_fields(self, fields, json_schema):
         )
         return required_metadata_fields
 
-    def get_empty_manifest(self, strict: Optional[bool], json_schema_filepath: str=None, sheet_url: Optional[bool]=None):
+    def get_empty_manifest(
+        self,
+        strict: Optional[bool],
+        json_schema_filepath: str = None,
+        sheet_url: Optional[bool] = None,
+    ):
         """Create an empty manifest using specifications from the
         json schema.
         Args:
@@ -1283,23 +1315,30 @@ def get_empty_manifest(self, strict: Optional[bool], json_schema_filepath: str=N
         )
 
         manifest_url = self._create_empty_gs(
-            required_metadata_fields, json_schema, spreadsheet_id, sheet_url=sheet_url, strict=strict,
+            required_metadata_fields,
+            json_schema,
+            spreadsheet_id,
+            sheet_url=sheet_url,
+            strict=strict,
         )
         return manifest_url
 
-    def _get_missing_columns(self, headers_1:list , headers_2:list) -> list:
+    def _get_missing_columns(self, headers_1: list, headers_2: list) -> list:
         """Compare two colunm sets and get cols that are in headers_1, but not headers_2
         Args:
             headers_1 (list): list of column headers
             headers_2 (list): list of column headers
-        Returns: 
+        Returns:
             list: column headers in headers_1 but not headers_2
 
         """
         return set(headers_1) - set(headers_2)
 
     def set_dataframe_by_url(
-        self, manifest_url: str, manifest_df: pd.DataFrame, out_of_schema_columns: set =None,
+        self,
+        manifest_url: str,
+        manifest_df: pd.DataFrame,
+        out_of_schema_columns: set = None,
     ) -> ps.Spreadsheet:
         """Update Google Sheets using given pandas DataFrame.
         Args:
@@ -1324,10 +1363,13 @@ def set_dataframe_by_url(
         # TODO: similarly clear formatting for out of schema columns, if any
         if out_of_schema_columns:
             num_out_of_schema_columns = len(out_of_schema_columns)
-            start_col = self._column_to_letter(len(manifest_df.columns) - num_out_of_schema_columns) # find start of out of schema columns
-            end_col = self._column_to_letter(len(manifest_df.columns) + 1) # find end of out of schema columns
-            wb.set_data_validation(start = start_col, end = end_col, condition_type = None)
-        
+            start_col = self._column_to_letter(
+                len(manifest_df.columns) - num_out_of_schema_columns
+            )  # find start of out of schema columns
+            end_col = self._column_to_letter(
+                len(manifest_df.columns) + 1
+            )  # find end of out of schema columns
+            wb.set_data_validation(start=start_col, end=end_col, condition_type=None)
 
         # set permissions so that anyone with the link can edit
         sh.share("", role="writer", type="anyone")
@@ -1384,7 +1426,7 @@ def map_annotation_names_to_display_names(
         return annotations.rename(columns=label_map)
 
     def get_manifest_with_annotations(
-        self, annotations: pd.DataFrame, strict: Optional[bool]=None
+        self, annotations: pd.DataFrame, strict: Optional[bool] = None
     ) -> Tuple[ps.Spreadsheet, pd.DataFrame]:
         """Generate manifest, optionally with annotations (if requested).
         Args:
@@ -1423,98 +1465,137 @@ def get_manifest_with_annotations(
 
         return manifest_url, manifest_df
 
-    def export_sheet_to_excel(self, title: str = None, manifest_url : str = None, output_location: str = None) -> str:
+    def export_sheet_to_excel(
+        self, title: str = None, manifest_url: str = None, output_location: str = None
+    ) -> str:
         """
         export manifest as an Excel spreadsheet and return local file path
         Args:
             title: title of the exported excel spreadsheet
-            manifest_url: manifest google sheet url 
+            manifest_url: manifest google sheet url
             output_location: the location where the exported excel file would live
-        return: 
-            Export manifest to a desired location. 
+        return:
+            Export manifest to a desired location.
         """
         # construct file name
         file_name = title + ".xlsx"
-        #if file path exists and it contains a file name: 
-        if output_location: 
+        # if file path exists and it contains a file name:
+        if output_location:
             if os.path.exists(output_location):
-                if Path(output_location).suffix == '.xlsx' or Path(output_location).suffix == '.xls':
+                if (
+                    Path(output_location).suffix == ".xlsx"
+                    or Path(output_location).suffix == ".xls"
+                ):
                     output_excel_file_path = output_location
                 # if users define the location but it doesn't contain a file name, we should add the file name:
                 else:
                     output_excel_file_path = os.path.join(output_location, file_name)
-    
+
         # trigger a warning if file path is provided but does not exist
         elif output_location and not os.path.exists(output_location):
-            output_excel_file_path = os.path.abspath(os.path.join(os.getcwd(), file_name))
-            logger.warning(f'{output_location} does not exist. Using current working directory {output_excel_file_path}')
+            output_excel_file_path = os.path.abspath(
+                os.path.join(os.getcwd(), file_name)
+            )
+            logger.warning(
+                f"{output_location} does not exist. Using current working directory {output_excel_file_path}"
+            )
         # otherwise, use the default location
         else:
-            output_excel_file_path = os.path.abspath(os.path.join(os.getcwd(), file_name))
-        
+            output_excel_file_path = os.path.abspath(
+                os.path.join(os.getcwd(), file_name)
+            )
+
         # export the manifest to excel
-        export_manifest_drive_service(manifest_url, file_path=output_excel_file_path, mimeType = 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet')
-        
+        export_manifest_drive_service(
+            manifest_url,
+            file_path=output_excel_file_path,
+            mime_type="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
+        )
+
         return output_excel_file_path
 
-    def _handle_output_format_logic(self, output_format: str = None, output_path: str = None, sheet_url: bool = None, empty_manifest_url: str = None, dataframe: pd.DataFrame = None, out_of_schema_columns: set =None):
+    def _handle_output_format_logic(
+        self,
+        output_format: str = None,
+        output_path: str = None,
+        sheet_url: bool = None,
+        empty_manifest_url: str = None,
+        dataframe: pd.DataFrame = None,
+        out_of_schema_columns: set = None,
+    ):
         """
         Handle the logic between sheet_url parameter and output_format parameter to determine the type of output to return
-        Args: 
+        Args:
             output_format: Determines if Google sheet URL, pandas dataframe, or Excel spreadsheet gets returned.
             sheet_url (Will be deprecated): a boolean ; determine if a pandas dataframe or a google sheet url gets return
-            empty_manifest_url: Google sheet URL that leads to an empty manifest 
+            empty_manifest_url: Google sheet URL that leads to an empty manifest
             dataframe: the pandas dataframe that contains the metadata that needs to be populated to an empty manifest
             output_path: Determines the output path of the exported manifest (only relevant if returning an excel spreadsheet)
             out_of_schema_columns (set): Columns that are in downloaded manifest, but not in current schema.
-        Return: 
-            a pandas dataframe, file path of an excel spreadsheet, or a google sheet URL 
+        Return:
+            a pandas dataframe, file path of an excel spreadsheet, or a google sheet URL
         TODO:
             Depreciate sheet URL and add google_sheet as an output_format choice.
         """
 
-        # if the output type gets set to "dataframe", return a data frame 
+        # if the output type gets set to "dataframe", return a data frame
         if output_format == "dataframe":
             return dataframe
-        
+
         # if the output type gets set to "excel", return an excel spreadsheet
-        elif output_format == "excel":              
+        elif output_format == "excel":
             # export manifest url that only contains column headers to Excel
-            output_file_path = self.export_sheet_to_excel(title = self.title,
-                                                          manifest_url = empty_manifest_url,
-                                                          output_location = output_path,
-                                                          )
+            output_file_path = self.export_sheet_to_excel(
+                title=self.title,
+                manifest_url=empty_manifest_url,
+                output_location=output_path,
+            )
 
             # populate an excel spreadsheet with the existing dataframe
             self.populate_existing_excel_spreadsheet(output_file_path, dataframe)
 
             return output_file_path
-        
+
         # Return google sheet if sheet_url flag is raised.
         elif sheet_url:
-            manifest_sh = self.set_dataframe_by_url(manifest_url=empty_manifest_url, manifest_df=dataframe, out_of_schema_columns=out_of_schema_columns)
+            manifest_sh = self.set_dataframe_by_url(
+                manifest_url=empty_manifest_url,
+                manifest_df=dataframe,
+                out_of_schema_columns=out_of_schema_columns,
+            )
             return manifest_sh.url
-        
+
         # Default return a DataFrame
         else:
             return dataframe
-    
+
     @staticmethod
-    def create_single_manifest(path_to_data_model: str, graph_data_model: nx.MultiDiGraph, data_type: str, access_token:Optional[str]=None, dataset_id:Optional[str]=None, strict:Optional[bool]=True, title:Optional[str]=None, output_format:Literal["google_sheet", "excel", "dataframe"]="google_sheet", use_annotations:Optional[bool]=False) -> Union[str, pd.DataFrame, BinaryIO]:
+    def create_single_manifest(
+        path_to_data_model: str,
+        graph_data_model: nx.MultiDiGraph,
+        data_type: str,
+        access_token: Optional[str] = None,
+        dataset_id: Optional[str] = None,
+        strict: Optional[bool] = True,
+        title: Optional[str] = None,
+        output_format: Literal["google_sheet", "excel", "dataframe"] = "google_sheet",
+        use_annotations: Optional[bool] = False,
+    ) -> Union[str, pd.DataFrame]:
         """Create a single manifest
 
         Args:
-            jsonld (str): jsonld schema 
+            path_to_data_model (str): data model schema
+            graph_data_model (nx.MultiDiGraph): graph data model
             data_type (str): data type of a manifest
-            access_token (str, optional): synapse access token. Required when getting an existing manifest. Defaults to None.
-            dataset_id (str, optional): dataset id when generating an existing manifest. Defaults to None.
-            strict (bool, optional): strictness with which to apply validation rules to google sheets. Defaults to True.
-            title (str, optional): title of a given manifest. Defaults to None.
-            output_format (str, optional): format of manifest. It has three options: google sheet, excel or dataframe. Defaults to None.
-            use_annotations (bool, optional): whether to use annotations. Defaults to False.
+            access_token (Optional[str], optional): synapse access token. Required when getting an existing manifest. Defaults to None.
+            dataset_id (Optional[str], optional):dataset id when generating an existing manifest. Defaults to None. Defaults to None.
+            strict (Optional[bool], optional): strictness with which to apply validation rules to google sheets. Defaults to True.
+            title (Optional[str], optional):title of a given manifest. Defaults to None.
+            output_format (Literal['google_sheet', 'excel', 'dataframe'], optional): format of manifest. Defaults to "google_sheet".
+            use_annotations (Optional[bool], optional):whether to use annotations. Defaults to False.
 
         Returns:
-            Union[str, pd.DataFrame, BinaryIO]: Googlesheet URL or pandas dataframe or Excel.
+            Union[str, pd.DataFrame]: Googlesheet URL or pandas dataframe or an excel file path
         """
         # create object of type ManifestGenerator
         manifest_generator = ManifestGenerator(
@@ -1523,7 +1604,7 @@ def create_single_manifest(path_to_data_model: str, graph_data_model: nx.MultiDi
             title=title,
             root=data_type,
             use_annotations=use_annotations,
-            alphabetize_valid_values = 'ascending',
+            alphabetize_valid_values="ascending",
         )
 
         # if returning a dataframe
@@ -1532,90 +1613,153 @@ def create_single_manifest(path_to_data_model: str, graph_data_model: nx.MultiDi
                 output_format = "dataframe"
 
         result = manifest_generator.get_manifest(
-            dataset_id=dataset_id, sheet_url=True, output_format=output_format, access_token=access_token, strict=strict,
+            dataset_id=dataset_id,
+            sheet_url=True,
+            output_format=output_format,
+            access_token=access_token,
+            strict=strict,
         )
 
-        # return an excel file if output_format is set to "excel"
-        if output_format == "excel":
-            dir_name = os.path.dirname(result)
-            file_name = os.path.basename(result)
-            mimetype='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'
-            return send_from_directory(directory=dir_name, path=file_name, as_attachment=True, mimetype=mimetype, max_age=0)
-               
         return result
-    
+
     @staticmethod
-    def create_manifests(path_to_data_model:str, data_types:list, access_token:Optional[str]=None, dataset_ids:Optional[list]=None, output_format:Literal["google_sheet", "excel", "dataframe"]="google_sheet", title:Optional[str]=None, strict:Optional[bool]=True, use_annotations:Optional[bool]=False) -> Union[List[str], List[pd.DataFrame], BinaryIO]:
+    def create_manifests(
+        path_to_data_model: str,
+        data_types: list,
+        data_model_labels: DisplayLabelType = "class_label",
+        access_token: Optional[str] = None,
+        dataset_ids: Optional[list] = None,
+        output_format: Literal["google_sheet", "excel", "dataframe"] = "google_sheet",
+        title: Optional[str] = None,
+        strict: Optional[bool] = True,
+        use_annotations: Optional[bool] = False,
+    ) -> Union[List[str], List[pd.DataFrame]]:
         """Create multiple manifests
 
         Args:
             path_to_data_model (str): str path to data model
-            data_type (list): a list of data types 
+            data_types (list): a list of data types
             access_token (str, optional): synapse access token. Required when getting an existing manifest. Defaults to None.
-            dataset_id (list, optional): a list of dataset ids when generating an existing manifest. Defaults to None.
+            dataset_ids (list, optional): a list of dataset ids when generating an existing manifest. Defaults to None.
             output_format (str, optional):format of manifest. It has three options: google sheet, excel or dataframe. Defaults to None.
             title (str, optional): title of a given manifest. Defaults to None.
             strict (bool, optional): strictness with which to apply validation rules to google sheets. Defaults to None.
             use_annotations (bool, optional): whether to use annotations. Defaults to False.
 
         Returns:
-            Union[List[str], List[pd.DataFrame], BinaryIO]: a list of Googlesheet URLs, a list of pandas dataframes or an Excel file.
+            Union[List[str], List[pd.DataFrame]]: a list of Googlesheet URLs, a list of pandas dataframes or excel file paths
         """
-        data_model_parser = DataModelParser(path_to_data_model = path_to_data_model)
+        if dataset_ids:
+            # Check that the number of submitted data_types matches
+            # the number of dataset_ids (if applicable)
+            len_data_types = len(data_types)
+            len_dataset_ids = len(dataset_ids)
 
-        #Parse Model
+            if len_data_types != len_dataset_ids:
+                raise ValueError(
+                    f"There is a mismatch in the number of data_types and dataset_id's that "
+                    f"submitted. Please check your submission and try again."
+                )
+
+            # Raise an error if used in conjunction with datatype = 'all_manifests'
+            if data_types[0] == "all manifests":
+                raise ValueError(
+                    "When submitting 'all manifests' as the data_type cannot also submit dataset_id. "
+                    "Please check your submission and try again."
+                )
+
+        data_model_parser = DataModelParser(path_to_data_model=path_to_data_model)
+
+        # Parse Model
         parsed_data_model = data_model_parser.parse_model()
 
         # Instantiate DataModelGraph
-        data_model_grapher = DataModelGraph(parsed_data_model)
+        data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
         # Generate graph
         graph_data_model = data_model_grapher.generate_data_model_graph()
 
         # Gather all returned result urls
         all_results = []
-        if data_types[0] == 'all manifests':
+        if data_types[0] == "all manifests":
             dmge = DataModelGraphExplorer(graph_data_model)
-            component_digraph = dmge.get_digraph_by_edge_type('requiresComponent')
+            component_digraph = dmge.get_digraph_by_edge_type("requiresComponent")
             components = component_digraph.nodes()
             for component in components:
                 if title:
-                    t = f'{title}.{component}.manifest'
-                else: 
-                    t = f'Example.{component}.manifest'
+                    t = f"{title}.{component}.manifest"
+                else:
+                    t = f"Example.{component}.manifest"
                 if output_format != "excel":
-                    result = ManifestGenerator.create_single_manifest(path_to_data_model=path_to_data_model, data_type=component, graph_data_model=graph_data_model, output_format=output_format, title=t, access_token=access_token)
+                    result = ManifestGenerator.create_single_manifest(
+                        path_to_data_model=path_to_data_model,
+                        data_type=component,
+                        graph_data_model=graph_data_model,
+                        output_format=output_format,
+                        title=t,
+                        strict=strict,
+                        access_token=access_token,
+                    )
                     all_results.append(result)
-                else: 
-                    logger.error('Currently we do not support returning multiple files as Excel format at once. Please choose a different output format. ')
+                else:
+                    logger.error(
+                        "Currently we do not support returning multiple files as Excel format at once. Please choose a different output format. "
+                    )
         else:
             for i, dt in enumerate(data_types):
-                if not title: 
-                    t = f'Example.{dt}.manifest'
-                else: 
+                if not title:
+                    t = f"Example.{dt}.manifest"
+                else:
                     if len(data_types) > 1:
-                        t = f'{title}.{dt}.manifest'
-                    else: 
+                        t = f"{title}.{dt}.manifest"
+                    else:
                         t = title
                 if dataset_ids:
                     # if a dataset_id is provided add this to the function call.
-                    result = ManifestGenerator.create_single_manifest(path_to_data_model=path_to_data_model, data_type=dt, graph_data_model=graph_data_model, dataset_id=dataset_ids[i], output_format=output_format, title=t, access_token=access_token, use_annotations=use_annotations)
+                    result = ManifestGenerator.create_single_manifest(
+                        path_to_data_model=path_to_data_model,
+                        data_type=dt,
+                        graph_data_model=graph_data_model,
+                        dataset_id=dataset_ids[i],
+                        output_format=output_format,
+                        title=t,
+                        strict=strict,
+                        access_token=access_token,
+                        use_annotations=use_annotations,
+                    )
                 else:
-                    result = ManifestGenerator.create_single_manifest(path_to_data_model=path_to_data_model, data_type=dt, graph_data_model=graph_data_model, output_format=output_format, title=t, access_token=access_token, use_annotations=use_annotations)
+                    result = ManifestGenerator.create_single_manifest(
+                        path_to_data_model=path_to_data_model,
+                        data_type=dt,
+                        graph_data_model=graph_data_model,
+                        output_format=output_format,
+                        title=t,
+                        strict=strict,
+                        access_token=access_token,
+                        use_annotations=use_annotations,
+                    )
 
                 # if output is pandas dataframe or google sheet url
                 if isinstance(result, str) or isinstance(result, pd.DataFrame):
                     all_results.append(result)
-                else: 
+                else:
                     if len(data_types) > 1:
-                        logger.warning(f'Currently we do not support returning multiple files as Excel format at once. Only {t} would get returned. ')
+                        logger.warning(
+                            f"Currently we do not support returning multiple files as Excel format at once. Only {t} would get returned. "
+                        )
                     return result
 
         return all_results
-        
 
     def get_manifest(
-        self, dataset_id: str = None, sheet_url: bool = None, json_schema: str = None, output_format: str = None, output_path: str = None, access_token: str = None, strict: Optional[bool]=None,
+        self,
+        dataset_id: str = None,
+        sheet_url: bool = None,
+        json_schema: str = None,
+        output_format: str = None,
+        output_path: str = None,
+        access_token: str = None,
+        strict: Optional[bool] = None,
     ) -> Union[str, pd.DataFrame]:
         """Gets manifest for a given dataset on Synapse.
            TODO: move this function to class MetadatModel (after MetadataModel is refactored)
@@ -1625,36 +1769,44 @@ def get_manifest(
             sheet_url (Will be deprecated): a boolean ; determine if a pandas dataframe or a google sheet url gets return
             output_format: Determines if Google sheet URL, pandas dataframe, or Excel spreadsheet gets returned.
             output_path: Determines the output path of the exported manifest
-            access_token: Token in .synapseConfig. Since we could not pre-load access_token as an environment variable on AWS, we have to add this variable. 
+            access_token: Token in .synapseConfig. Since we could not pre-load access_token as an environment variable on AWS, we have to add this variable.
 
         Returns:
-            Googlesheet URL, pandas dataframe, or an Excel spreadsheet 
+            Googlesheet URL, pandas dataframe, or an Excel spreadsheet
         """
         # Handle case when no dataset ID is provided
         if not dataset_id:
-            manifest_url = self.get_empty_manifest(json_schema_filepath=json_schema, strict=strict, sheet_url=sheet_url)
+            manifest_url = self.get_empty_manifest(
+                json_schema_filepath=json_schema, strict=strict, sheet_url=sheet_url
+            )
 
             # if output_form parameter is set to "excel", return an excel spreadsheet
-            if output_format == "excel": 
-                output_file_path = self.export_sheet_to_excel(title = self.title, manifest_url = manifest_url, output_location = output_path)
+            if output_format == "excel":
+                output_file_path = self.export_sheet_to_excel(
+                    title=self.title,
+                    manifest_url=manifest_url,
+                    output_location=output_path,
+                )
                 return output_file_path
             # since we are not going to return an empty dataframe for an empty manifest, here we will just return a google sheet url for all other cases
-            else: 
+            else:
                 return manifest_url
 
         # Otherwise, create manifest using the given dataset
-        #TODO: avoid explicitly exposing Synapse store functionality
+        # TODO: avoid explicitly exposing Synapse store functionality
         # just instantiate a Store class and let it decide at runtime/config
         # the store type
-        if access_token: 
+        if access_token:
             # for getting an existing manifest on AWS
             store = SynapseStorage(access_token=access_token)
-        else: 
+        else:
             store = SynapseStorage()
 
         # Get manifest file associated with given dataset (if applicable)
         # populate manifest with set of new files (if applicable)
-        manifest_record = store.updateDatasetManifestFiles(self.dmge, datasetId = dataset_id, store = False)
+        manifest_record = store.updateDatasetManifestFiles(
+            self.dmge, datasetId=dataset_id, store=False
+        )
 
         # get URL of an empty manifest file created based on schema component
         empty_manifest_url = self.get_empty_manifest(strict=strict, sheet_url=True)
@@ -1664,20 +1816,23 @@ def get_manifest(
             # TODO: Update or remove the warning in self.__init__() if
             # you change the behavior here based on self.use_annotations
             # Update df with existing manifest. Agnostic to output format
-            updated_df, out_of_schema_columns = self._update_dataframe_with_existing_df(empty_manifest_url=empty_manifest_url, existing_df=manifest_record[1])
+            updated_df, out_of_schema_columns = self._update_dataframe_with_existing_df(
+                empty_manifest_url=empty_manifest_url, existing_df=manifest_record[1]
+            )
 
             # determine the format of manifest
-            result = self._handle_output_format_logic(output_format = output_format,
-                                                      output_path = output_path,
-                                                      sheet_url = sheet_url,
-                                                      empty_manifest_url=empty_manifest_url,
-                                                      dataframe = updated_df,
-                                                      out_of_schema_columns=out_of_schema_columns,
-                                                      )
+            result = self._handle_output_format_logic(
+                output_format=output_format,
+                output_path=output_path,
+                sheet_url=sheet_url,
+                empty_manifest_url=empty_manifest_url,
+                dataframe=updated_df,
+                out_of_schema_columns=out_of_schema_columns,
+            )
             return result
 
         # Generate empty template and optionally fill in with annotations
-        # if there is no existing manifest and use annotations is set to True, 
+        # if there is no existing manifest and use annotations is set to True,
         # pull annotations (in reality, annotations should be empty when there is no existing manifest)
         else:
             # Using getDatasetAnnotations() to retrieve file names and subset
@@ -1687,39 +1842,50 @@ def get_manifest(
                 if self.is_file_based:
                     annotations = store.getDatasetAnnotations(dataset_id)
                     # Update `additional_metadata` and generate manifest
-                    manifest_url, manifest_df = self.get_manifest_with_annotations(annotations,strict=strict)
-                
-                # If the annotations are empty, 
-                # ie if there are no annotations to pull or annotations were unable to be pulled because the metadata is not file based, 
+                    manifest_url, manifest_df = self.get_manifest_with_annotations(
+                        annotations, strict=strict
+                    )
+
+                # If the annotations are empty,
+                # ie if there are no annotations to pull or annotations were unable to be pulled because the metadata is not file based,
                 # then create manifest from an empty manifest
                 if annotations.empty:
                     empty_manifest_df = self.get_dataframe_by_url(empty_manifest_url)
                     manifest_df = empty_manifest_df
 
-                    logger.warning(f"Annotations were not able to be gathered for the given parameters. This manifest will be generated from an empty manifest.")
-                    
+                    logger.warning(
+                        f"Annotations were not able to be gathered for the given parameters. This manifest will be generated from an empty manifest."
+                    )
+
             else:
                 empty_manifest_df = self.get_dataframe_by_url(empty_manifest_url)
                 if self.is_file_based:
                     # for file-based manifest, make sure that entityId column and Filename column still gets filled even though use_annotations gets set to False
-                    manifest_df = store.add_entity_id_and_filename(dataset_id,empty_manifest_df)
+                    manifest_df = store.add_entity_id_and_filename(
+                        dataset_id, empty_manifest_df
+                    )
                 else:
                     manifest_df = empty_manifest_df
 
             # Update df with existing manifest. Agnostic to output format
-            updated_df, out_of_schema_columns = self._update_dataframe_with_existing_df(empty_manifest_url=empty_manifest_url, existing_df=manifest_df)
-
-            # determine the format of manifest that gets return 
-            result = self._handle_output_format_logic(output_format = output_format,
-                                                      output_path = output_path,
-                                                      sheet_url = sheet_url,
-                                                      empty_manifest_url=empty_manifest_url,
-                                                      dataframe = updated_df,
-                                                      out_of_schema_columns = out_of_schema_columns,
-                                                      )
+            updated_df, out_of_schema_columns = self._update_dataframe_with_existing_df(
+                empty_manifest_url=empty_manifest_url, existing_df=manifest_df
+            )
+
+            # determine the format of manifest that gets return
+            result = self._handle_output_format_logic(
+                output_format=output_format,
+                output_path=output_path,
+                sheet_url=sheet_url,
+                empty_manifest_url=empty_manifest_url,
+                dataframe=updated_df,
+                out_of_schema_columns=out_of_schema_columns,
+            )
             return result
 
-    def _get_end_columns(self, current_schema_headers, existing_manifest_headers, out_of_schema_columns):
+    def _get_end_columns(
+        self, current_schema_headers, existing_manifest_headers, out_of_schema_columns
+    ):
         """
         Gather columns to be added to the end of the manifest, and ensure entityId is at the end.
         Args:
@@ -1731,19 +1897,24 @@ def _get_end_columns(self, current_schema_headers, existing_manifest_headers, ou
         """
         # Identify columns to add to the end of the manifest
         end_columns = list(out_of_schema_columns)
-        
+
         # Make sure want Ids are placed at end of manifest, in given order.
-        for id_name in ['Uuid', 'Id', 'entityId']:
+        for id_name in ["Uuid", "Id", "entityId"]:
             if id_name in end_columns:
                 end_columns.remove(id_name)
                 end_columns.append(id_name)
-        
+
         # Add entity_id to the end columns if it should be there but isn't
-        if 'entityId' in (current_schema_headers or existing_manifest_headers) and 'entityId' not in end_columns:
-            end_columns.append('entityId')
+        if (
+            "entityId" in (current_schema_headers or existing_manifest_headers)
+            and "entityId" not in end_columns
+        ):
+            end_columns.append("entityId")
         return end_columns
 
-    def _update_dataframe_with_existing_df(self, empty_manifest_url: str, existing_df: pd.DataFrame) -> pd.DataFrame:
+    def _update_dataframe_with_existing_df(
+        self, empty_manifest_url: str, existing_df: pd.DataFrame
+    ) -> pd.DataFrame:
         """
         Handle scenario when existing manifest does not match new manifest template due to changes in the data model:
             the sheet column header reflect the latest schema the existing manifest column-set may be outdated
@@ -1759,40 +1930,50 @@ def _update_dataframe_with_existing_df(self, empty_manifest_url: str, existing_d
         """
 
         # Get headers for the current schema and existing manifest df.
-        current_schema_headers = list(self.get_dataframe_by_url(manifest_url=empty_manifest_url).columns)
+        current_schema_headers = list(
+            self.get_dataframe_by_url(manifest_url=empty_manifest_url).columns
+        )
         existing_manifest_headers = list(existing_df.columns)
 
         # Find columns that exist in the current schema, but are not in the manifest being downloaded.
-        new_columns = self._get_missing_columns(current_schema_headers, existing_manifest_headers)
+        new_columns = self._get_missing_columns(
+            current_schema_headers, existing_manifest_headers
+        )
 
         # Find columns that exist in the manifest being downloaded, but not in the current schema.
-        out_of_schema_columns = self._get_missing_columns(existing_manifest_headers, current_schema_headers)
+        out_of_schema_columns = self._get_missing_columns(
+            existing_manifest_headers, current_schema_headers
+        )
 
         # clean empty columns if any are present (there should be none)
         # TODO: Remove this line once we start preventing empty column names
-        if '' in new_columns:
-            new_columns = new_columns.remove('')
+        if "" in new_columns:
+            new_columns = new_columns.remove("")
 
         # Copy the df for updating.
         updated_df = existing_df.copy(deep=True)
-        
+
         # update existing manifest w/ missing columns, if any
         if new_columns:
             updated_df = updated_df.assign(
                 **dict(zip(new_columns, len(new_columns) * [""]))
             )
 
-        end_columns = self._get_end_columns(current_schema_headers=current_schema_headers,
-                                           existing_manifest_headers=existing_manifest_headers,
-                                           out_of_schema_columns=out_of_schema_columns)
-        
+        end_columns = self._get_end_columns(
+            current_schema_headers=current_schema_headers,
+            existing_manifest_headers=existing_manifest_headers,
+            out_of_schema_columns=out_of_schema_columns,
+        )
+
         # sort columns in the updated manifest:
         # match latest schema order
         # move obsolete columns at the end
         updated_df = updated_df[self.sort_manifest_fields(updated_df.columns)]
 
         # move obsolete columns at the end with entityId at the very end
-        updated_df = updated_df[[c for c in updated_df if c not in end_columns] + list(end_columns)]
+        updated_df = updated_df[
+            [c for c in updated_df if c not in end_columns] + list(end_columns)
+        ]
         return updated_df, out_of_schema_columns
 
     def _format_new_excel_column(self, worksheet, new_column_index: int, col: str):
@@ -1804,78 +1985,106 @@ def _format_new_excel_column(self, worksheet, new_column_index: int, col: str):
             modified worksheet
         """
         # Add column header
-        worksheet.cell(row=1, column=new_column_index+1).value = col
-        # Format new column header 
-        worksheet.cell(row=1, column=new_column_index+1).font = Font(size=8, bold=True, color="FF000000")
-        worksheet.cell(row=1, column=new_column_index+1).alignment = Alignment(horizontal="center", vertical="bottom")
-        worksheet.cell(row=1, column=new_column_index+1).fill = PatternFill(start_color='FFE0E0E0', end_color='FFE0E0E0', fill_type='solid')
+        worksheet.cell(row=1, column=new_column_index + 1).value = col
+        # Format new column header
+        worksheet.cell(row=1, column=new_column_index + 1).font = Font(
+            size=8, bold=True, color="FF000000"
+        )
+        worksheet.cell(row=1, column=new_column_index + 1).alignment = Alignment(
+            horizontal="center", vertical="bottom"
+        )
+        worksheet.cell(row=1, column=new_column_index + 1).fill = PatternFill(
+            start_color="FFE0E0E0", end_color="FFE0E0E0", fill_type="solid"
+        )
         return worksheet
 
-    def populate_existing_excel_spreadsheet(self, existing_excel_path: str = None, additional_df: pd.DataFrame = None):
-        '''Populate an existing excel spreadsheet by using an additional dataframe (to avoid sending metadata directly to Google APIs)
+    def populate_existing_excel_spreadsheet(
+        self, existing_excel_path: str = None, additional_df: pd.DataFrame = None
+    ):
+        """Populate an existing excel spreadsheet by using an additional dataframe (to avoid sending metadata directly to Google APIs)
         New columns will be placed at the end of the spreadsheet.
         Args:
             existing_excel_path: path of an existing excel spreadsheet
             additional_df: additional dataframe
-        Return: 
+        Return:
             added new dataframe to the existing excel path.
         Note:
-            - Done by rows and column as a way to preserve formatting. 
+            - Done by rows and column as a way to preserve formatting.
             Doing a complete replacement will remove all conditional formatting and dropdowns.
-        '''
+        """
         # load workbook
         workbook = load_workbook(existing_excel_path)
         worksheet = workbook.active
 
         # Add new data to existing excel
         if not additional_df.empty:
-            existing_excel_headers = [cell.value for cell in worksheet[1] if cell.value != None]
+            existing_excel_headers = [
+                cell.value for cell in worksheet[1] if cell.value != None
+            ]
 
             new_column_index = len(existing_excel_headers)
             df_columns = additional_df.columns
 
             # Iteratively fill workbook with contents of additional_df
-            for row_num, row_contents in enumerate(dataframe_to_rows(additional_df, index=False, header=False), 2):
+            for row_num, row_contents in enumerate(
+                dataframe_to_rows(additional_df, index=False, header=False), 2
+            ):
                 for index, col in enumerate(df_columns):
                     if col in existing_excel_headers:
                         # Get index of column header in existing excel to ensure no values are placed in incorrect spot.
                         existing_column_index = existing_excel_headers.index(col)
-                        worksheet.cell(row=row_num, column=existing_column_index+1).value = row_contents[index]
+                        worksheet.cell(
+                            row=row_num, column=existing_column_index + 1
+                        ).value = row_contents[index]
                     else:
                         # Add new col to excel worksheet and format.
-                        worksheet = self._format_new_excel_column(worksheet=worksheet, new_column_index=new_column_index, col=col)
+                        worksheet = self._format_new_excel_column(
+                            worksheet=worksheet,
+                            new_column_index=new_column_index,
+                            col=col,
+                        )
                         # Add data to column
-                        worksheet.cell(row=row_num, column=new_column_index+1).value = row_contents[index]
+                        worksheet.cell(
+                            row=row_num, column=new_column_index + 1
+                        ).value = row_contents[index]
                         # Add new column to headers so it can be accounted for.
                         existing_excel_headers.append(col)
                         # Update index for adding new columns.
-                        new_column_index+=1                   
+                        new_column_index += 1
         workbook.save(existing_excel_path)
 
-    def populate_manifest_spreadsheet(self, existing_manifest_path: str = None, empty_manifest_url: str = None, return_excel: bool = False, title: str = None):
+    def populate_manifest_spreadsheet(
+        self,
+        existing_manifest_path: str = None,
+        empty_manifest_url: str = None,
+        return_excel: bool = False,
+        title: str = None,
+    ):
         """Creates a google sheet manifest based on existing manifest.
         Args:
             existing_manifest_path: the location of the manifest containing metadata presently stored
             empty_manifest_url: the path to a manifest template to be prepopulated with existing's manifest metadata
             return_excel: if true, return an Excel spreadsheet instead of Google sheet
-            title: title of output manifest 
+            title: title of output manifest
         """
 
         # read existing manifest
         manifest = load_df(existing_manifest_path)
-        
-        if return_excel: 
-            '''if we are returning an Excel spreadsheet, do not populate dataframe to google'''
-            # get an empty manifest 
+
+        if return_excel:
+            """if we are returning an Excel spreadsheet, do not populate dataframe to google"""
+            # get an empty manifest
             manifest_url = empty_manifest_url
 
             # export the manifest to excel
-            output_excel_file_path = self.export_sheet_to_excel(manifest_url = manifest_url, title=title)
-            
-            # populate exported sheet 
+            output_excel_file_path = self.export_sheet_to_excel(
+                manifest_url=manifest_url, title=title
+            )
+
+            # populate exported sheet
             self.populate_existing_excel_spreadsheet(output_excel_file_path, manifest)
             return output_excel_file_path
-        else: 
+        else:
             manifest_sh = self.set_dataframe_by_url(empty_manifest_url, manifest)
             return manifest_sh.url
 
diff --git a/schematic/models/GE_Helpers.py b/schematic/models/GE_Helpers.py
index 521d75157..5b356999e 100644
--- a/schematic/models/GE_Helpers.py
+++ b/schematic/models/GE_Helpers.py
@@ -1,4 +1,3 @@
-
 from statistics import mode
 from tabnanny import check
 import logging
@@ -19,60 +18,69 @@
 import great_expectations as ge
 from great_expectations.core.expectation_configuration import ExpectationConfiguration
 from great_expectations.data_context import BaseDataContext
-from great_expectations.data_context.types.base import DataContextConfig, DatasourceConfig, FilesystemStoreBackendDefaults
-from great_expectations.data_context.types.resource_identifiers import ExpectationSuiteIdentifier
+from great_expectations.data_context.types.base import (
+    DataContextConfig,
+    DatasourceConfig,
+    FilesystemStoreBackendDefaults,
+)
+from great_expectations.data_context.types.resource_identifiers import (
+    ExpectationSuiteIdentifier,
+)
 from great_expectations.exceptions.exceptions import GreatExpectationsError
 
 
 from schematic.models.validate_attribute import GenerateError
 from schematic.schemas.data_model_graph import DataModelGraphExplorer
 
-from schematic.utils.validate_utils import rule_in_rule_list, np_array_to_str_list, iterable_to_str_list
+from schematic.utils.schema_utils import extract_component_validation_rules
+
+from schematic.utils.validate_utils import (
+    rule_in_rule_list,
+    np_array_to_str_list,
+    iterable_to_str_list,
+)
 
 logger = logging.getLogger(__name__)
 
+
 class GreatExpectationsHelpers(object):
     """
-        Great Expectations helper class
+    Great Expectations helper class
 
-        Provides basic utilities to:
-            1) Create GE workflow specific to manifest according to validation rules
-            2) Parse results dict to generate appropriate errors
+    Provides basic utilities to:
+        1) Create GE workflow specific to manifest according to validation rules
+        2) Parse results dict to generate appropriate errors
     """
-    def __init__(self,
-        dmge,
-        unimplemented_expectations,
-        manifest,
-        manifestPath
-        ):
+
+    def __init__(self, dmge, unimplemented_expectations, manifest, manifestPath):
         """
-            Purpose:
-                Instantiate a great expectations helpers object
-            Args:
-                dmge: 
-                    DataModelGraphExplorer Object
-                unimplemented_expectations:
-                    dictionary of validation rules that currently do not have expectations developed
-                manifest:
-                    manifest being validated
-                manifestPath:
-                    path to manifest being validated            
+        Purpose:
+            Instantiate a great expectations helpers object
+        Args:
+            dmge:
+                DataModelGraphExplorer Object
+            unimplemented_expectations:
+                dictionary of validation rules that currently do not have expectations developed
+            manifest:
+                manifest being validated
+            manifestPath:
+                path to manifest being validated
         """
         self.unimplemented_expectations = unimplemented_expectations
         self.dmge = dmge
         self.manifest = manifest
         self.manifestPath = manifestPath
 
-    def  build_context(self):
+    def build_context(self):
         """
-            Purpose:
-                Create a dataContext and datasource and add to object 
-            Returns:
-                saves dataContext and datasource to self
+        Purpose:
+            Create a dataContext and datasource and add to object
+        Returns:
+            saves dataContext and datasource to self
         """
-        self.context=ge.get_context()
+        self.context = ge.get_context()
 
-        #create datasource configuration
+        # create datasource configuration
         datasource_config = {
             "name": "example_datasource",
             "class_name": "Datasource",
@@ -89,14 +97,12 @@ def  build_context(self):
             },
         }
 
-        #create data context configuration
+        # create data context configuration
         data_context_config = DataContextConfig(
             datasources={
                 "pandas": DatasourceConfig(
                     class_name="Datasource",
-                    execution_engine={
-                        "class_name": "PandasExecutionEngine"
-                    },
+                    execution_engine={"class_name": "PandasExecutionEngine"},
                     data_connectors={
                         "default_runtime_data_connector_name": {
                             "class_name": "RuntimeDataConnector",
@@ -105,25 +111,28 @@ def  build_context(self):
                     },
                 )
             },
-            store_backend_defaults=FilesystemStoreBackendDefaults(root_directory=os.path.join(os.getcwd(),'great_expectations')),
+            store_backend_defaults=FilesystemStoreBackendDefaults(
+                root_directory=os.path.join(os.getcwd(), "great_expectations")
+            ),
         )
 
-        #build context and add data source
-        self.context=BaseDataContext(project_config=data_context_config)
-        #self.context.test_yaml_config(yaml.dump(datasource_config))
+        # build context and add data source
+        self.context = BaseDataContext(project_config=data_context_config)
+        # self.context.test_yaml_config(yaml.dump(datasource_config))
         self.context.add_datasource(**datasource_config)
 
-        
-    def build_expectation_suite(self,):
+    def build_expectation_suite(
+        self,
+    ):
         """
-            Purpose:
-                Construct an expectation suite to validate columns with rules that have expectations
-                Add suite to object
-            Input:
-                
-            Returns:
-                saves expectation suite and identifier to self
-            
+        Purpose:
+            Construct an expectation suite to validate columns with rules that have expectations
+            Add suite to object
+        Input:
+
+        Returns:
+            saves expectation suite and identifier to self
+
         """
         validation_expectation = {
             "int": "expect_column_values_to_be_in_type_list",
@@ -136,97 +145,103 @@ def build_expectation_suite(self,):
             "unique": "expect_column_values_to_be_unique",
             "inRange": "expect_column_values_to_be_between",
             "IsNA": "expect_column_values_to_match_regex_list",
-
             # To be implemented rules with possible expectations
-            #"list": "expect_column_values_to_not_match_regex_list",
-            #"regex": "expect_column_values_to_match_regex",
-            #"url": "expect_column_values_to_be_valid_urls",
-            #"matchAtLeastOne": "expect_foreign_keys_in_column_a_to_exist_in_column_b",
-            #"matchExactlyOne": "expect_foreign_keys_in_column_a_to_exist_in_column_b",
+            # "list": "expect_column_values_to_not_match_regex_list",
+            # "regex": "expect_column_values_to_match_regex",
+            # "url": "expect_column_values_to_be_valid_urls",
+            # "matchAtLeastOne": "expect_foreign_keys_in_column_a_to_exist_in_column_b",
+            # "matchExactlyOne": "expect_foreign_keys_in_column_a_to_exist_in_column_b",
         }
-        
-        #create blank expectation suite
-        self.expectation_suite_name = "Manifest_test_suite"       
+
+        # create blank expectation suite
+        self.expectation_suite_name = "Manifest_test_suite"
         self.suite = self.context.add_expectation_suite(
             expectation_suite_name=self.expectation_suite_name,
-        )    
+        )
 
-        #build expectation configurations for each expectation
+        # build expectation configurations for each expectation
         for col in self.manifest.columns:
-            args={}
-            meta={}
-            
+            args = {}
+            meta = {}
+
             # remove trailing/leading whitespaces from manifest
-            self.manifest.applymap(lambda x: x.strip() if isinstance(x, str) else x)
-            validation_rules = self.dmge.get_node_validation_rules(node_display_name=col)
+            self.manifest.map(lambda x: x.strip() if isinstance(x, str) else x)
+
+            validation_rules = self.dmge.get_node_validation_rules(
+                node_display_name=col
+            )
 
-            #check if attribute has any rules associated with it
+            # check if attribute has any rules associated with it
             if validation_rules:
-                #iterate through all validation rules for an attribute
+                # Check if the validation rule applies to this manifest
+                if isinstance(validation_rules, dict):
+                    validation_rules = extract_component_validation_rules(
+                        manifest_component=self.manifest["Component"][0],
+                        validation_rules=validation_rules,
+                    )
+                # iterate through all validation rules for an attribute
                 for rule in validation_rules:
                     base_rule = rule.split(" ")[0]
-            
-                    #check if rule has an implemented expectation
-                    if rule_in_rule_list(rule,self.unimplemented_expectations):
+
+                    # check if rule has an implemented expectation
+                    if rule_in_rule_list(rule, self.unimplemented_expectations):
                         continue
 
-                
                     args["column"] = col
                     args["result_format"] = "COMPLETE"
 
-
-                    #Validate num
-                    if base_rule=='num':
-                        args["mostly"]=1.0
-                        args["type_list"]=['int','int64', 'float', 'float64']
-                        meta={
+                    # Validate num
+                    if base_rule == "num":
+                        args["mostly"] = 1.0
+                        args["type_list"] = ["int", "int64", "float", "float64"]
+                        meta = {
                             "notes": {
                                 "format": "markdown",
-                                "content": "Expect column values to be of int or float type. **Markdown** `Supported`"
+                                "content": "Expect column values to be of int or float type. **Markdown** `Supported`",
                             },
-                            "validation_rule": rule
+                            "validation_rule": rule,
                         }
-                
-                    #Validate float
-                    elif base_rule=='float':
-                        args["mostly"]=1.0
-                        args["type_list"]=['float', 'float64']
-                        meta={
+
+                    # Validate float
+                    elif base_rule == "float":
+                        args["mostly"] = 1.0
+                        args["type_list"] = ["float", "float64"]
+                        meta = {
                             "notes": {
                                 "format": "markdown",
                                 "content": "Expect column values to be of float type. **Markdown** `Supported`",
                             },
-                            "validation_rule": rule
+                            "validation_rule": rule,
                         }
-                
-                    #Validate int
-                    elif base_rule=='int':
-                        args["mostly"]=1.0
-                        args["type_list"]=['int','int64']
-                        meta={
+
+                    # Validate int
+                    elif base_rule == "int":
+                        args["mostly"] = 1.0
+                        args["type_list"] = ["int", "int64"]
+                        meta = {
                             "notes": {
                                 "format": "markdown",
                                 "content": "Expect column values to be of int type. **Markdown** `Supported`",
                             },
-                            "validation_rule": rule
+                            "validation_rule": rule,
                         }
-                
-                    #Validate string
-                    elif base_rule=='str':
-                        args["mostly"]=1.0
-                        args["type_"]='str'
-                        meta={
+
+                    # Validate string
+                    elif base_rule == "str":
+                        args["mostly"] = 1.0
+                        args["type_"] = "str"
+                        meta = {
                             "notes": {
                                 "format": "markdown",
                                 "content": "Expect column values to be of string type. **Markdown** `Supported`",
                             },
-                            "validation_rule": rule
+                            "validation_rule": rule,
                         }
 
-                    #Validate date
-                    elif base_rule=='date':
-                        args["mostly"]=1.0
-                        meta={
+                    # Validate date
+                    elif base_rule == "date":
+                        args["mostly"] = 1.0
+                        meta = {
                             "notes": {
                                 "format": "markdown",
                                 "content": (
@@ -234,85 +249,98 @@ def build_expectation_suite(self,):
                                     "**Markdown** `Supported`"
                                 ),
                             },
-                            "validation_rule": rule
+                            "validation_rule": rule,
                         }
 
-                    elif base_rule==("recommended"):
-                        args["mostly"]=0.0000000001
-                        args["regex_list"]=['^$']
-                        meta={
+                    elif base_rule == ("recommended"):
+                        args["mostly"] = 0.0000000001
+                        args["regex_list"] = ["^$"]
+                        meta = {
                             "notes": {
                                 "format": "markdown",
                                 "content": "Expect column to not be empty. **Markdown** `Supported`",
                             },
-                            "validation_rule": rule
+                            "validation_rule": rule,
                         }
 
-                    elif base_rule==("protectAges"):
-                        #Function to convert to different age limit formats
+                    elif base_rule == ("protectAges"):
+                        # Function to convert to different age limit formats
                         min_age, max_age = self.get_age_limits()
 
-                        args["mostly"]=1.0
-                        args["min_value"]=min_age
-                        args["max_value"]=max_age
-                        #args['allow_cross_type_comparisons']=True # TODO Can allow after issue #980 is completed
-                        meta={
+                        args["mostly"] = 1.0
+                        args["min_value"] = min_age
+                        args["max_value"] = max_age
+                        # args['allow_cross_type_comparisons']=True # TODO Can allow after issue #980 is completed
+                        meta = {
                             "notes": {
                                 "format": "markdown",
                                 "content": "Expect ages to be between 18 years (6,570 days) and 90 years (32,850 days) of age. **Markdown** `Supported`",
                             },
-                            "validation_rule": rule
+                            "validation_rule": rule,
                         }
 
-                    elif base_rule==("unique"):
-                        args["mostly"]=1.0
-                        meta={
+                    elif base_rule == ("unique"):
+                        args["mostly"] = 1.0
+                        meta = {
                             "notes": {
                                 "format": "markdown",
                                 "content": "Expect column values to be Unique. **Markdown** `Supported`",
                             },
-                            "validation_rule": rule
+                            "validation_rule": rule,
                         }
-                    
-                    elif base_rule==("inRange"):
-                        args["mostly"]=1.0
-                        args["min_value"]=float(rule.split(" ")[1]) if rule.split(" ")[1].lower() != 'none' else None
-                        args["max_value"]=float(rule.split(" ")[2]) if rule.split(" ")[2].lower() != 'none' else None
-                        args['allow_cross_type_comparisons']=True # TODO Should follow up with issue #980
-                        meta={
+
+                    elif base_rule == ("inRange"):
+                        args["mostly"] = 1.0
+                        args["min_value"] = (
+                            float(rule.split(" ")[1])
+                            if rule.split(" ")[1].lower() != "none"
+                            else None
+                        )
+                        args["max_value"] = (
+                            float(rule.split(" ")[2])
+                            if rule.split(" ")[2].lower() != "none"
+                            else None
+                        )
+                        args[
+                            "allow_cross_type_comparisons"
+                        ] = True  # TODO Should follow up with issue #980
+                        meta = {
                             "notes": {
                                 "format": "markdown",
                                 "content": "Expect column values to be within a specified range. **Markdown** `Supported`",
                             },
-                            "validation_rule": rule
+                            "validation_rule": rule,
                         }
-                        
-                    elif base_rule==("IsNA"):
-                        args["mostly"]=1.0
-                        args["regex_list"]=['Not Applicable']
-                        meta={
+
+                    elif base_rule == ("IsNA"):
+                        args["mostly"] = 1.0
+                        args["regex_list"] = ["Not Applicable"]
+                        meta = {
                             "notes": {
                                 "format": "markdown",
                                 "content": "Expect column values to be marked Not Applicable. **Markdown** `Supported`",
                             },
-                            "validation_rule": rule
+                            "validation_rule": rule,
                         }
-                                        
-                    #add expectation for attribute to suite        
+
+                    # add expectation for attribute to suite
                     self.add_expectation(
                         rule=rule,
                         args=args,
                         meta=meta,
                         validation_expectation=validation_expectation,
                     )
-        
-            
-        self.context.update_expectation_suite(expectation_suite=self.suite,)
 
-        suite_identifier = ExpectationSuiteIdentifier(expectation_suite_name=self.expectation_suite_name)
+        self.context.update_expectation_suite(
+            expectation_suite=self.suite,
+        )
+
+        suite_identifier = ExpectationSuiteIdentifier(
+            expectation_suite_name=self.expectation_suite_name
+        )
         self.context.build_data_docs(resource_identifiers=[suite_identifier])
         ##Webpage DataDocs opened here:
-        #self.context.open_data_docs(resource_identifier=suite_identifier) 
+        # self.context.open_data_docs(resource_identifier=suite_identifier)
 
     def add_expectation(
         self,
@@ -320,46 +348,45 @@ def add_expectation(
         args: Dict,
         meta: Dict,
         validation_expectation: Dict,
-        ):
+    ):
         """
-            Purpose:
-                Add individual expectation for a rule to the suite
-            Input:
-                rule: 
-                    validation rule
-                args: 
-                    dict of arguments specifying expectation behavior
-                meta:
-                    dict of additional information for each expectation
-                validation_expectation:
-                    dictionary to map between rules and expectations
-            Returns:
-                adds expectation to self.suite
-            
+        Purpose:
+            Add individual expectation for a rule to the suite
+        Input:
+            rule:
+                validation rule
+            args:
+                dict of arguments specifying expectation behavior
+            meta:
+                dict of additional information for each expectation
+            validation_expectation:
+                dictionary to map between rules and expectations
+        Returns:
+            adds expectation to self.suite
+
         """
         # Create an Expectation
         expectation_configuration = ExpectationConfiguration(
             # Name of expectation type being added
             expectation_type=validation_expectation[rule.split(" ")[0]],
-
-            #add arguments and meta message
+            # add arguments and meta message
             kwargs={**args},
-            meta={**meta}
+            meta={**meta},
         )
         # Add the Expectation to the suite
         self.suite.add_expectation(expectation_configuration=expectation_configuration)
 
     def build_checkpoint(self):
         """
-            Purpose:
-                Build checkpoint to validate manifest
-            Input:
-            Returns:
-                adds checkpoint to self 
+        Purpose:
+            Build checkpoint to validate manifest
+        Input:
+        Returns:
+            adds checkpoint to self
         """
-        #create manifest checkpoint
-        self.checkpoint_name = "manifest_checkpoint"  
-        checkpoint_config={
+        # create manifest checkpoint
+        self.checkpoint_name = "manifest_checkpoint"
+        checkpoint_config = {
             "name": self.checkpoint_name,
             "config_version": 1,
             "class_name": "SimpleCheckpoint",
@@ -375,9 +402,9 @@ def build_checkpoint(self):
             ],
         }
 
-        #self.context.test_yaml_config(yaml.dump(checkpoint_config),return_mode="report_object")        
+        # self.context.test_yaml_config(yaml.dump(checkpoint_config),return_mode="report_object")
         self.context.add_checkpoint(**checkpoint_config)
-    
+
     def generate_errors(
         self,
         validation_results: Dict,
@@ -385,130 +412,137 @@ def generate_errors(
         errors: List,
         warnings: List,
         dmge: DataModelGraphExplorer,
-        ):
+    ):
         """
-            Purpose:
-                Parse results dictionary and generate errors for expectations
-            Input:
-                validation_results:
-                    dictionary of results for each expectation
-                validation_types:
-                    dict of types of errors to generate for each validation rule
-                errors:
-                    list of errors
-                warnings:
-                    list of warnings    
-            Returns:
-                errors:
-                    list of errors
-                warnings:
-                    list of warnings
-                self.manifest:
-                    manifest, possibly updated (censored ages)
+        Purpose:
+            Parse results dictionary and generate errors for expectations
+        Input:
+            validation_results:
+                dictionary of results for each expectation
+            validation_types:
+                dict of types of errors to generate for each validation rule
+            errors:
+                list of errors
+            warnings:
+                list of warnings
+        Returns:
+            errors:
+                list of errors
+            warnings:
+                list of warnings
+            self.manifest:
+                manifest, possibly updated (censored ages)
         """
 
-        type_dict={
+        type_dict = {
             "float64": float,
             "int64": int,
             "str": str,
         }
-        for result_dict in validation_results[0]['results']:
-
-            
+        for result_dict in validation_results[0]["results"]:
             indices = []
             values = []
-            
-            #if the expectaion failed, get infromation to generate error message
-            if not result_dict['success']:
-                errColumn   = result_dict['expectation_config']['kwargs']['column']               
-                rule        = result_dict['expectation_config']['meta']['validation_rule']
 
+            # if the expectaion failed, get infromation to generate error message
+            if not result_dict["success"]:
+                errColumn = result_dict["expectation_config"]["kwargs"]["column"]
+                rule = result_dict["expectation_config"]["meta"]["validation_rule"]
+
+                if (
+                    "exception_info" in result_dict.keys()
+                    and result_dict["exception_info"]["exception_message"]
+                ):
+                    raise GreatExpectationsError(
+                        result_dict["exception_info"]["exception_traceback"]
+                    )
 
-                if 'exception_info' in result_dict.keys() and result_dict['exception_info']['exception_message']:
-                    raise GreatExpectationsError(result_dict['exception_info']['exception_traceback'])
-                
-                #only some expectations explicitly list unexpected values and indices, read or find if not present
-                elif 'unexpected_index_list' in result_dict['result']:
-                    indices = result_dict['result']['unexpected_index_list']
-                    values  = result_dict['result']['unexpected_list']
+                # only some expectations explicitly list unexpected values and indices, read or find if not present
+                elif "unexpected_index_list" in result_dict["result"]:
+                    indices = result_dict["result"]["unexpected_index_list"]
+                    values = result_dict["result"]["unexpected_list"]
 
                 # Technically, this shouldn't ever happen, but will keep as a failsafe in case many things go wrong
-                # because type validation is column aggregate expectation and not column map expectation when columns are not of object type, 
+                # because type validation is column aggregate expectation and not column map expectation when columns are not of object type,
                 # indices and values cannot be returned
                 else:
                     for i, item in enumerate(self.manifest[errColumn]):
-                        observed_type=result_dict['result']['observed_value']
-                        indices.append(i)   if isinstance(item,type_dict[observed_type]) else indices
-                        values.append(item) if isinstance(item,type_dict[observed_type]) else values
-
-                #call functions to generate error messages and add to error list
-                if validation_types[rule.split(" ")[0]]['type']=='type_validation':
-                    for row, value in zip(indices,values):
+                        observed_type = result_dict["result"]["observed_value"]
+                        indices.append(i) if isinstance(
+                            item, type_dict[observed_type]
+                        ) else indices
+                        values.append(item) if isinstance(
+                            item, type_dict[observed_type]
+                        ) else values
+
+                # call functions to generate error messages and add to error list
+                if validation_types[rule.split(" ")[0]]["type"] == "type_validation":
+                    for row, value in zip(indices, values):
                         vr_errors, vr_warnings = GenerateError.generate_type_error(
-                                val_rule = rule,
-                                row_num = str(row+2),
-                                attribute_name = errColumn,
-                                invalid_entry = str(value),
-                                dmge = dmge,
-                            )
+                            val_rule=rule,
+                            row_num=str(row + 2),
+                            attribute_name=errColumn,
+                            invalid_entry=str(value),
+                            dmge=dmge,
+                        )
                         if vr_errors:
-                            errors.append(vr_errors)  
+                            errors.append(vr_errors)
                         if vr_warnings:
-                            warnings.append(vr_warnings) 
-                elif validation_types[rule.split(" ")[0]]['type']=='regex_validation':
-                    expression=result_dict['expectation_config']['kwargs']['regex']
-                    for row, value in zip(indices,values):   
+                            warnings.append(vr_warnings)
+                elif validation_types[rule.split(" ")[0]]["type"] == "regex_validation":
+                    expression = result_dict["expectation_config"]["kwargs"]["regex"]
+                    for row, value in zip(indices, values):
                         vr_errors, vr_warnings = GenerateError.generate_regex_error(
-                                val_rule= rule,
-                                reg_expression = expression,
-                                row_num = str(row+2),
-                                module_to_call = 'match',
-                                attribute_name = errColumn,
-                                invalid_entry = value,
-                                dmge = dmge,
-                            )
+                            val_rule=rule,
+                            reg_expression=expression,
+                            row_num=str(row + 2),
+                            module_to_call="match",
+                            attribute_name=errColumn,
+                            invalid_entry=value,
+                            dmge=dmge,
+                        )
                         if vr_errors:
-                            errors.append(vr_errors)  
+                            errors.append(vr_errors)
                         if vr_warnings:
-                            warnings.append(vr_warnings)                          
-                elif validation_types[rule.split(" ")[0]]['type']=='content_validation':     
+                            warnings.append(vr_warnings)
+                elif (
+                    validation_types[rule.split(" ")[0]]["type"] == "content_validation"
+                ):
                     vr_errors, vr_warnings = GenerateError.generate_content_error(
-                                                            val_rule = rule, 
-                                                            attribute_name = errColumn,
-                                                            row_num = np_array_to_str_list(np.array(indices)+2),
-                                                            error_val = iterable_to_str_list(values),  
-                                                            dmge = self.dmge
-                                                        )       
+                        val_rule=rule,
+                        attribute_name=errColumn,
+                        row_num=np_array_to_str_list(np.array(indices) + 2),
+                        error_val=iterable_to_str_list(values),
+                        dmge=self.dmge,
+                    )
                     if vr_errors:
-                        errors.append(vr_errors)  
-                        if rule.startswith('protectAges'):
-                            self.censor_ages(vr_errors,errColumn)
-                            
+                        errors.append(vr_errors)
+                        if rule.startswith("protectAges"):
+                            self.censor_ages(vr_errors, errColumn)
+
                     if vr_warnings:
-                        warnings.append(vr_warnings)  
-                        if rule.startswith('protectAges'):
-                            self.censor_ages(vr_warnings,errColumn)
-                            
+                        warnings.append(vr_warnings)
+                        if rule.startswith("protectAges"):
+                            self.censor_ages(vr_warnings, errColumn)
 
         return errors, warnings
 
     def get_age_limits(
         self,
-        ):
+    ):
         """
-            Purpose:
-                Get boundaries of ages that need to be censored for different age formats
-            Input:
-            Returns:
-                min_age:
-                    minimum age that will not be censored
-                max age:
-                    maximum age that will not be censored
-            
-        """        
-
-        min_age = 6550      #days
-        max_age = 32849     #days
+        Purpose:
+            Get boundaries of ages that need to be censored for different age formats
+        Input:
+        Returns:
+            min_age:
+                minimum age that will not be censored
+            max age:
+                maximum age that will not be censored
+
+        """
+
+        min_age = 6550  # days
+        max_age = 32849  # days
 
         return min_age, max_age
 
@@ -516,28 +550,30 @@ def censor_ages(
         self,
         message: List,
         col: str,
-        ):
+    ):
         """
-            Purpose:
-                Censor ages in manifest as appropriate
-            Input:
-                message: 
-                    error or warning message for age validation rule
-                col:
-                    name of column containing ages
-            Returns:
-                updates self.manifest with censored ages
-            TODO: Speed up conversion from str list to int list
+        Purpose:
+            Censor ages in manifest as appropriate
+        Input:
+            message:
+                error or warning message for age validation rule
+            col:
+                name of column containing ages
+        Returns:
+            updates self.manifest with censored ages
+        TODO: Speed up conversion from str list to int list
         """
         censor_rows = []
-        
+
         for row in message[0]:
             censor_rows.append(int(row) - 2)
 
-        self.manifest.loc[censor_rows,(col)] = 'age censored'
+        self.manifest.loc[censor_rows, (col)] = "age censored"
 
         # update the manifest file, so that ages are censored
-        self.manifest.to_csv(self.manifestPath.replace('.csv','_censored.csv'), index=False)
+        self.manifest.to_csv(
+            self.manifestPath.replace(".csv", "_censored.csv"), index=False
+        )
         logging.info("Sensitive ages have been censored.")
 
         return
diff --git a/schematic/models/commands.py b/schematic/models/commands.py
index eeeb7c809..f7af66456 100644
--- a/schematic/models/commands.py
+++ b/schematic/models/commands.py
@@ -11,16 +11,22 @@
 from jsonschema import ValidationError
 
 from schematic.models.metadata import MetadataModel
-from schematic.utils.cli_utils import log_value_from_config, query_dict, parse_synIDs, parse_comma_str_to_list
+from schematic.utils.cli_utils import (
+    log_value_from_config,
+    query_dict,
+    parse_syn_ids,
+    parse_comma_str_to_list,
+)
 from schematic.help import model_commands
 from schematic.exceptions import MissingConfigValueError
 from schematic.configuration.configuration import CONFIG
 
-logger = logging.getLogger('schematic')
+logger = logging.getLogger("schematic")
 click_log.basic_config(logger)
 
 CONTEXT_SETTINGS = dict(help_option_names=["--help", "-h"])  # help options
 
+
 # invoke_without_command=True -> forces the application not to show aids before losing them with a --h
 @click.group(context_settings=CONTEXT_SETTINGS, invoke_without_command=True)
 @click_log.simple_verbosity_option(logger)
@@ -39,7 +45,7 @@ def model(ctx, config):  # use as `schematic model ...`
     try:
         logger.debug(f"Loading config file contents in '{config}'")
         CONFIG.load_config(config)
-        ctx.obj =  CONFIG
+        ctx.obj = CONFIG
     except ValueError as e:
         logger.error("'--config' not provided or environment variable not set.")
         logger.exception(e)
@@ -66,72 +72,107 @@ def model(ctx, config):  # use as `schematic model ...`
     "--validate_component",
     help=query_dict(model_commands, ("model", "submit", "validate_component")),
 )
-@click.option(
-    "--use_schema_label/--use_display_label",
-    "-sl/-dl",
-    default=True,
-    help=query_dict(model_commands, ("model", "submit", "use_schema_label")),
-)
 @click.option(
     "--hide_blanks",
     "-hb",
     is_flag=True,
-    help=query_dict(model_commands,("model","submit","hide_blanks")),
+    help=query_dict(model_commands, ("model", "submit", "hide_blanks")),
 )
 @click.option(
     "--manifest_record_type",
     "-mrt",
-    default='table_file_and_entities',
-    type=click.Choice(['table_and_file', 'file_only', 'file_and_entities', 'table_file_and_entities'], case_sensitive=True),
-    help=query_dict(model_commands, ("model", "submit", "manifest_record_type")))
+    default="table_file_and_entities",
+    type=click.Choice(
+        ["table_and_file", "file_only", "file_and_entities", "table_file_and_entities"],
+        case_sensitive=True,
+    ),
+    help=query_dict(model_commands, ("model", "submit", "manifest_record_type")),
+)
 @click.option(
     "-rr",
     "--restrict_rules",
     is_flag=True,
-    help=query_dict(model_commands,("model","validate","restrict_rules")),
+    help=query_dict(model_commands, ("model", "validate", "restrict_rules")),
 )
 @click.option(
     "-ps",
     "--project_scope",
     default=None,
-    callback=parse_synIDs,
+    callback=parse_syn_ids,
     help=query_dict(model_commands, ("model", "validate", "project_scope")),
 )
 @click.option(
     "--table_manipulation",
     "-tm",
-    default='replace',
-    type=click.Choice(['replace', 'upsert'], case_sensitive=True),
-    help=query_dict(model_commands, ("model", "submit", "table_manipulation")))
+    default="replace",
+    type=click.Choice(["replace", "upsert"], case_sensitive=True),
+    help=query_dict(model_commands, ("model", "submit", "table_manipulation")),
+)
+@click.option(
+    "--data_model_labels",
+    "-dml",
+    default="class_label",
+    type=click.Choice(["display_label", "class_label"], case_sensitive=True),
+    help=query_dict(model_commands, ("model", "submit", "data_model_labels")),
+)
+@click.option(
+    "--table_column_names",
+    "-tcn",
+    default="class_label",
+    type=click.Choice(
+        ["class_label", "display_label", "display_name"], case_sensitive=True
+    ),
+    help=query_dict(model_commands, ("model", "submit", "table_column_names")),
+)
+@click.option(
+    "--annotation_keys",
+    "-ak",
+    default="class_label",
+    type=click.Choice(["class_label", "display_label"], case_sensitive=True),
+    help=query_dict(model_commands, ("model", "submit", "annotation_keys")),
+)
 @click.pass_obj
 def submit_manifest(
-    ctx, manifest_path, dataset_id, validate_component, manifest_record_type, use_schema_label, hide_blanks, restrict_rules, project_scope, table_manipulation,
+    ctx,
+    manifest_path,
+    dataset_id,
+    validate_component,
+    manifest_record_type,
+    hide_blanks,
+    restrict_rules,
+    project_scope,
+    table_manipulation,
+    data_model_labels,
+    table_column_names,
+    annotation_keys,
 ):
     """
     Running CLI with manifest validation (optional) and submission options.
     """
-    
-    jsonld =  CONFIG.model_location
+
+    jsonld = CONFIG.model_location
     log_value_from_config("jsonld", jsonld)
 
     metadata_model = MetadataModel(
-        inputMModelLocation=jsonld, inputMModelLocationType="local"
+        inputMModelLocation=jsonld,
+        inputMModelLocationType="local",
+        data_model_labels=data_model_labels,
     )
 
-
     manifest_id = metadata_model.submit_metadata_manifest(
-        path_to_json_ld = jsonld,
+        path_to_json_ld=jsonld,
         manifest_path=manifest_path,
         dataset_id=dataset_id,
         validate_component=validate_component,
         manifest_record_type=manifest_record_type,
         restrict_rules=restrict_rules,
-        use_schema_label=use_schema_label,
         hide_blanks=hide_blanks,
         project_scope=project_scope,
         table_manipulation=table_manipulation,
+        table_column_names=table_column_names,
+        annotation_keys=annotation_keys,
     )
-    
+
     if manifest_id:
         logger.info(
             f"File at '{manifest_path}' was successfully associated "
@@ -167,24 +208,38 @@ def submit_manifest(
     "-rr",
     "--restrict_rules",
     is_flag=True,
-    help=query_dict(model_commands,("model","validate","restrict_rules")),
+    help=query_dict(model_commands, ("model", "validate", "restrict_rules")),
 )
 @click.option(
     "-ps",
     "--project_scope",
     default=None,
-    callback=parse_synIDs,
+    callback=parse_syn_ids,
     help=query_dict(model_commands, ("model", "validate", "project_scope")),
 )
+@click.option(
+    "--data_model_labels",
+    "-dml",
+    is_flag=True,
+    help=query_dict(model_commands, ("model", "validate", "data_model_labels")),
+)
 @click.pass_obj
-def validate_manifest(ctx, manifest_path, data_type, json_schema, restrict_rules,project_scope):
+def validate_manifest(
+    ctx,
+    manifest_path,
+    data_type,
+    json_schema,
+    restrict_rules,
+    project_scope,
+    data_model_labels,
+):
     """
     Running CLI for manifest validation.
     """
     if data_type is None:
-        data_type =  CONFIG.manifest_data_type
+        data_type = CONFIG.manifest_data_type
         log_value_from_config("data_type", data_type)
- 
+
     try:
         len(data_type) == 1
     except:
@@ -196,15 +251,21 @@ def validate_manifest(ctx, manifest_path, data_type, json_schema, restrict_rules
 
     t_validate = perf_counter()
 
-    jsonld =  CONFIG.model_location
+    jsonld = CONFIG.model_location
     log_value_from_config("jsonld", jsonld)
 
     metadata_model = MetadataModel(
-        inputMModelLocation=jsonld, inputMModelLocationType="local"
+        inputMModelLocation=jsonld,
+        inputMModelLocationType="local",
+        data_model_labels=data_model_labels,
     )
 
     errors, warnings = metadata_model.validateModelManifest(
-        manifestPath=manifest_path, rootNode=data_type, jsonSchema=json_schema, restrict_rules=restrict_rules, project_scope=project_scope,
+        manifestPath=manifest_path,
+        rootNode=data_type,
+        jsonSchema=json_schema,
+        restrict_rules=restrict_rules,
+        project_scope=project_scope,
     )
 
     if not errors:
@@ -216,6 +277,4 @@ def validate_manifest(ctx, manifest_path, data_type, json_schema, restrict_rules
     else:
         click.echo(errors)
 
-    logger.debug(
-        f"Total elapsed time {perf_counter()-t_validate} seconds"
-    )
+    logger.debug(f"Total elapsed time {perf_counter()-t_validate} seconds")
diff --git a/schematic/models/metadata.py b/schematic/models/metadata.py
index 50e718014..c57e9d79f 100644
--- a/schematic/models/metadata.py
+++ b/schematic/models/metadata.py
@@ -1,6 +1,7 @@
 import os
 import logging
 import networkx as nx
+from os.path import exists
 from jsonschema import ValidationError
 
 # allows specifying explicit variable types
@@ -11,8 +12,7 @@
 from schematic.schemas.data_model_parser import DataModelParser
 from schematic.schemas.data_model_json_schema import DataModelJSONSchema
 
-
-#TODO: This module should only be aware of the store interface
+# TODO: This module should only be aware of the store interface
 # we shouldn't need to expose Synapse functionality explicitly
 from schematic.store.synapse import SynapseStorage
 
@@ -34,8 +34,12 @@ class MetadataModel(object):
         - generate validation schema view of the metadata model
     """
 
-    def __init__(self, inputMModelLocation: str, inputMModelLocationType: str,) -> None:
-
+    def __init__(
+        self,
+        inputMModelLocation: str,
+        inputMModelLocationType: str,
+        data_model_labels: str,
+    ) -> None:
         """Instantiates a MetadataModel object.
 
         Args:
@@ -51,12 +55,12 @@ def __init__(self, inputMModelLocation: str, inputMModelLocationType: str,) -> N
 
         self.inputMModelLocation = inputMModelLocation
 
-        data_model_parser = DataModelParser(path_to_data_model = self.inputMModelLocation)
-        #Parse Model
+        data_model_parser = DataModelParser(path_to_data_model=self.inputMModelLocation)
+        # Parse Model
         parsed_data_model = data_model_parser.parse_model()
 
         # Instantiate DataModelGraph
-        data_model_grapher = DataModelGraph(parsed_data_model)
+        data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
         # Generate graph
         self.graph_data_model = data_model_grapher.generate_data_model_graph()
@@ -138,7 +142,7 @@ def getModelManifest(
 
         mg = ManifestGenerator(
             path_to_json_ld=self.inputMModelLocation,
-            graph = self.graph_data_model,
+            graph=self.graph_data_model,
             title=title,
             root=rootNode,
             additional_metadata=additionalMetadata,
@@ -208,12 +212,13 @@ def validateModelManifest(
             ValueError: rootNode not found in metadata model.
         """
         # get validation schema for a given node in the data model, if the user has not provided input validation schema
-        
+
         if not jsonSchema:
-            
             # Instantiate Data Model Json Schema
-            self.data_model_js = DataModelJSONSchema(jsonld_path=self.inputMModelLocation, graph=self.graph_data_model)
-            
+            self.data_model_js = DataModelJSONSchema(
+                jsonld_path=self.inputMModelLocation, graph=self.graph_data_model
+            )
+
             jsonSchema = self.data_model_js.get_json_validation_schema(
                 rootNode, rootNode + "_validation"
             )
@@ -221,12 +226,14 @@ def validateModelManifest(
         errors = []
         warnings = []
 
-        load_args={
-            "dtype":"string",
-            }
+        load_args = {
+            "dtype": "string",
+        }
         # get annotations from manifest (array of json annotations corresponding to manifest rows)
         manifest = load_df(
-            manifestPath, preserve_raw_input=False, **load_args,
+            manifestPath,
+            preserve_raw_input=False,
+            **load_args,
         )  # read manifest csv file as is from manifest path
 
         # handler for mismatched components/data types
@@ -259,24 +266,28 @@ def validateModelManifest(
                 )
 
             return errors, warnings
-        
+
         # check if suite has been created. If so, delete it
         if os.path.exists("great_expectations/expectations/Manifest_test_suite.json"):
             os.remove("great_expectations/expectations/Manifest_test_suite.json")
-            
-        errors, warnings, manifest = validate_all(self, 
-                                                  errors=errors,
-                                                  warnings=warnings,
-                                                  manifest=manifest,
-                                                  manifestPath=manifestPath,
-                                                  dmge=self.dmge,
-                                                  jsonSchema=jsonSchema,
-                                                  restrict_rules=restrict_rules,
-                                                  project_scope=project_scope,
-                                                  access_token=access_token)
+
+        errors, warnings, manifest = validate_all(
+            self,
+            errors=errors,
+            warnings=warnings,
+            manifest=manifest,
+            manifestPath=manifestPath,
+            dmge=self.dmge,
+            jsonSchema=jsonSchema,
+            restrict_rules=restrict_rules,
+            project_scope=project_scope,
+            access_token=access_token,
+        )
         return errors, warnings
 
-    def populateModelManifest(self, title, manifestPath: str, rootNode: str, return_excel = False) -> str:
+    def populateModelManifest(
+        self, title, manifestPath: str, rootNode: str, return_excel=False
+    ) -> str:
         """Populate an existing annotations manifest based on a dataframe.
             TODO: Remove this method; always use getModelManifest instead
 
@@ -291,12 +302,17 @@ def populateModelManifest(self, title, manifestPath: str, rootNode: str, return_
             ValueError: rootNode not found in metadata model.
         """
         mg = ManifestGenerator(
-            path_to_data_model=self.inputMModelLocation, graph = self.graph_data_model, title=title, root=rootNode
+            path_to_data_model=self.inputMModelLocation,
+            graph=self.graph_data_model,
+            title=title,
+            root=rootNode,
         )
 
         emptyManifestURL = mg.get_manifest()
 
-        return mg.populate_manifest_spreadsheet(manifestPath, emptyManifestURL, return_excel = return_excel, title=title)
+        return mg.populate_manifest_spreadsheet(
+            manifestPath, emptyManifestURL, return_excel=return_excel, title=title
+        )
 
     def submit_metadata_manifest(
         self,
@@ -307,10 +323,11 @@ def submit_metadata_manifest(
         restrict_rules: bool,
         access_token: Optional[str] = None,
         validate_component: Optional[str] = None,
-        use_schema_label: bool = True,
         hide_blanks: bool = False,
         project_scope: List = None,
-        table_manipulation: str = 'replace'
+        table_manipulation: str = "replace",
+        table_column_names: str = "class_label",
+        annotation_keys: str = "class_label",
     ) -> str:
         """Wrap methods that are responsible for validation of manifests for a given component, and association of the
         same manifest file with a specified dataset.
@@ -325,17 +342,18 @@ def submit_metadata_manifest(
             ValidationError: If validation against data model was not successful.
         """
 
-        #TODO: avoid explicitly exposing Synapse store functionality
+        # TODO: avoid explicitly exposing Synapse store functionality
         # just instantiate a Store class and let it decide at runtime/config
         # the store type
-        syn_store = SynapseStorage(access_token = access_token, project_scope = project_scope)
-        manifest_id=None
-        censored_manifest_id=None
-        restrict_maniest=False
-        censored_manifest_path=manifest_path.replace('.csv','_censored.csv')
+        syn_store = SynapseStorage(
+            access_token=access_token, project_scope=project_scope
+        )
+        manifest_id = None
+        censored_manifest_id = None
+        restrict_maniest = False
+        censored_manifest_path = manifest_path.replace(".csv", "_censored.csv")
         # check if user wants to perform validation or not
         if validate_component is not None:
-
             try:
                 # check if the component ("class" in schema) passed as argument is valid (present in schema) or not
                 self.dmge.is_class_in_schema(validate_component)
@@ -350,38 +368,44 @@ def submit_metadata_manifest(
 
             # automatic JSON schema generation and validation with that JSON schema
             val_errors, val_warnings = self.validateModelManifest(
-                manifestPath=manifest_path, rootNode=validate_component, restrict_rules=restrict_rules, project_scope=project_scope, access_token=access_token
+                manifestPath=manifest_path,
+                rootNode=validate_component,
+                restrict_rules=restrict_rules,
+                project_scope=project_scope,
+                access_token=access_token,
             )
 
             # if there are no errors in validation process
-            if val_errors == []:                
+            if val_errors == []:
                 # upload manifest file from `manifest_path` path to entity with Syn ID `dataset_id`
                 if os.path.exists(censored_manifest_path):
                     censored_manifest_id = syn_store.associateMetadataWithFiles(
-                        dmge = self.dmge,
-                        metadataManifestPath = censored_manifest_path,
-                        datasetId = dataset_id, 
-                        manifest_record_type = manifest_record_type,
-                        useSchemaLabel = use_schema_label,
-                        hideBlanks = hide_blanks,
+                        dmge=self.dmge,
+                        metadataManifestPath=censored_manifest_path,
+                        datasetId=dataset_id,
+                        manifest_record_type=manifest_record_type,
+                        hideBlanks=hide_blanks,
                         table_manipulation=table_manipulation,
+                        table_column_names=table_column_names,
+                        annotation_keys=annotation_keys,
                     )
                     restrict_maniest = True
-                
+
                 manifest_id = syn_store.associateMetadataWithFiles(
-                    dmge = self.dmge,
-                    metadataManifestPath = manifest_path, 
-                    datasetId = dataset_id, 
-                    manifest_record_type = manifest_record_type,
-                    useSchemaLabel = use_schema_label, 
-                    hideBlanks = hide_blanks,
+                    dmge=self.dmge,
+                    metadataManifestPath=manifest_path,
+                    datasetId=dataset_id,
+                    manifest_record_type=manifest_record_type,
+                    hideBlanks=hide_blanks,
                     restrict_manifest=restrict_maniest,
                     table_manipulation=table_manipulation,
+                    table_column_names=table_column_names,
+                    annotation_keys=annotation_keys,
                 )
 
                 logger.info(f"No validation errors occured during validation.")
                 return manifest_id
-                
+
             else:
                 raise ValidationError(
                     "Manifest could not be validated under provided data model. "
@@ -391,25 +415,27 @@ def submit_metadata_manifest(
         # no need to perform validation, just submit/associate the metadata manifest file
         if os.path.exists(censored_manifest_path):
             censored_manifest_id = syn_store.associateMetadataWithFiles(
-                dmge = self.dmge,
+                dmge=self.dmge,
                 metadataManifestPath=censored_manifest_path,
                 datasetId=dataset_id,
                 manifest_record_type=manifest_record_type,
-                useSchemaLabel=use_schema_label,
                 hideBlanks=hide_blanks,
                 table_manipulation=table_manipulation,
+                table_column_names=table_column_names,
+                annotation_keys=annotation_keys,
             )
             restrict_maniest = True
-        
+
         manifest_id = syn_store.associateMetadataWithFiles(
-            dmge = self.dmge,
+            dmge=self.dmge,
             metadataManifestPath=manifest_path,
             datasetId=dataset_id,
             manifest_record_type=manifest_record_type,
-            useSchemaLabel=use_schema_label,
             hideBlanks=hide_blanks,
             restrict_manifest=restrict_maniest,
             table_manipulation=table_manipulation,
+            table_column_names=table_column_names,
+            annotation_keys=annotation_keys,
         )
 
         logger.debug(
diff --git a/schematic/models/validate_attribute.py b/schematic/models/validate_attribute.py
index f923891ba..693309118 100644
--- a/schematic/models/validate_attribute.py
+++ b/schematic/models/validate_attribute.py
@@ -5,12 +5,12 @@
 import time
 from time import perf_counter
 from os import getenv
+
 # allows specifying explicit variable types
 from typing import Any, Dict, List, Optional, Text
 from urllib import error
 from urllib.parse import urlparse
-from urllib.request import (HTTPDefaultErrorHandler, OpenerDirector, Request,
-                            urlopen)
+from urllib.request import HTTPDefaultErrorHandler, OpenerDirector, Request, urlopen
 
 import numpy as np
 import pandas as pd
@@ -21,93 +21,105 @@
 from schematic.store.base import BaseStorage
 from schematic.store.synapse import SynapseStorage
 from schematic.utils.validate_rules_utils import validation_rule_info
-from schematic.utils.validate_utils import (comma_separated_list_regex,
-                                            parse_str_series_to_list,
-                                            np_array_to_str_list,
-                                            iterable_to_str_list,
-                                            rule_in_rule_list,
-                                            )
+from schematic.utils.validate_utils import (
+    comma_separated_list_regex,
+    parse_str_series_to_list,
+    np_array_to_str_list,
+    iterable_to_str_list,
+    rule_in_rule_list,
+)
 
 from synapseclient.core.exceptions import SynapseNoCredentialsError
 
 logger = logging.getLogger(__name__)
 
+
 class GenerateError:
-    def generate_schema_error(row_num: str, attribute_name: str, error_msg: str, invalid_entry: str, dmge: DataModelGraphExplorer,)-> List[str]:
-        '''
+    def generate_schema_error(
+        row_num: str,
+        attribute_name: str,
+        error_msg: str,
+        invalid_entry: str,
+        dmge: DataModelGraphExplorer,
+    ) -> List[str]:
+        """
         Purpose: Process error messages generated from schema
         Input:
             - row_num: the row the error occurred on.
             - attribute_name: the attribute the error occurred on.
             - error_msg: Error message
-        '''
+        """
         error_list = []
         warning_list = []
-        
-        #Determine which, if any, message to raise
-        if attribute_name.lower() == 'wrong schema':
-            raises = 'error'
-        else:    
+
+        # Determine which, if any, message to raise
+        if attribute_name.lower() == "wrong schema":
+            raises = "error"
+        else:
             raises = GenerateError.get_message_level(
-                val_rule = 'schema',
-                attribute_name = attribute_name,
-                dmge = dmge,
-                )
+                val_rule="schema",
+                attribute_name=attribute_name,
+                dmge=dmge,
+            )
 
-        #if a message needs to be raised, get the approrpiate function to do so
+        # if a message needs to be raised, get the approrpiate function to do so
         if raises:
-            logLevel = getattr(logger,raises)  
+            logLevel = getattr(logger, raises)
         else:
             return error_list, warning_list
 
-
         error_col = attribute_name  # Attribute name
         error_row = row_num  # index row of the manifest where the error presented.
         error_message = error_msg
 
         arg_error_string = (
-                f"For the attribute '{error_col}', on row {error_row}, {error_message}."
+            f"For the attribute '{error_col}', on row {error_row}, {error_message}."
         )
         logLevel(arg_error_string)
 
-        if raises == 'error':
+        if raises == "error":
             error_list = [error_row, error_col, error_message, invalid_entry]
-        elif raises == 'warning':
+        elif raises == "warning":
             warning_list = [error_row, error_col, error_message, invalid_entry]
 
-        return error_list, warning_list 
+        return error_list, warning_list
 
     def generate_list_error(
-        list_string: str, row_num: str, attribute_name: str, list_error: str,
-        invalid_entry:str, dmge: DataModelGraphExplorer, val_rule: str,
+        list_string: str,
+        row_num: str,
+        attribute_name: str,
+        list_error: str,
+        invalid_entry: str,
+        dmge: DataModelGraphExplorer,
+        val_rule: str,
     ) -> List[str]:
         """
-            Purpose:
-                If an error is found in the string formatting, detect and record
-                an error message.
-            Input:
-                - list_string: the user input list, that is represented as a string.
-                - row_num: the row the error occurred on.
-                - attribute_name: the attribute the error occurred on.
-            Returns:
-            logger.error or logger.warning.
-            Errors: List[str] Error details for further storage.
-            warnings: List[str] Warning details for further storage.
-            """
+        Purpose:
+            If an error is found in the string formatting, detect and record
+            an error message.
+        Input:
+            - list_string: the user input list, that is represented as a string.
+            - row_num: the row the error occurred on.
+            - attribute_name: the attribute the error occurred on.
+        Returns:
+        logger.error or logger.warning.
+        Errors: List[str] Error details for further storage.
+        warnings: List[str] Warning details for further storage.
+        """
 
         error_list = []
         warning_list = []
-        
-        #Determine which, if any, message to raise
+
+        # Determine which, if any, message to raise
         raises = GenerateError.get_message_level(
-            val_rule = val_rule,
-            attribute_name = attribute_name,
-            dmge = dmge,
-            )
+            val_rule=val_rule,
+            attribute_name=attribute_name,
+            dmge=dmge,
+        )
 
-        #if a message needs to be raised, get the approrpiate function to do so
+        # if a message needs to be raised, get the approrpiate function to do so
         if raises:
-            logLevel = getattr(logger,raises)  
+            logLevel = getattr(logger, raises)
         else:
             return error_list, warning_list
 
@@ -122,15 +134,15 @@ def generate_list_error(
             error_col = attribute_name  # Attribute name
             error_message = error_str
             error_val = invalid_entry
-                #return error and empty list for warnings
-        
-        if raises == 'error':
+            # return error and empty list for warnings
+
+        if raises == "error":
             error_list = [error_row, error_col, error_message, error_val]
-        #return warning and empty list for errors
-        elif raises == 'warning':
+        # return warning and empty list for errors
+        elif raises == "warning":
             warning_list = [error_row, error_col, error_message, error_val]
-        
-        return error_list, warning_list 
+
+        return error_list, warning_list
 
     def generate_regex_error(
         val_rule: str,
@@ -142,33 +154,33 @@ def generate_regex_error(
         dmge: DataModelGraphExplorer,
     ) -> List[str]:
         """
-            Purpose:
-                Generate an logging error as well as a stored error message, when
-                a regex error is encountered.
-            Input:
-                val_rule: str, defined in the schema.
-                reg_expression: str, defined in the schema
-                row_num: str, row where the error was detected
-                module_to_call: re module specified in the schema
-                attribute_name: str, attribute being validated
-            Returns:
-            logger.error or logger.warning.
-            Errors: List[str] Error details for further storage.
-            warnings: List[str] Warning details for further storage.
-            """
+        Purpose:
+            Generate an logging error as well as a stored error message, when
+            a regex error is encountered.
+        Input:
+            val_rule: str, defined in the schema.
+            reg_expression: str, defined in the schema
+            row_num: str, row where the error was detected
+            module_to_call: re module specified in the schema
+            attribute_name: str, attribute being validated
+        Returns:
+        logger.error or logger.warning.
+        Errors: List[str] Error details for further storage.
+        warnings: List[str] Warning details for further storage.
+        """
         error_list = []
         warning_list = []
-        
-        #Determine which, if any, message to raise
+
+        # Determine which, if any, message to raise
         raises = GenerateError.get_message_level(
-            val_rule = val_rule,
-            attribute_name = attribute_name,
-            dmge = dmge,
-            )
+            val_rule=val_rule,
+            attribute_name=attribute_name,
+            dmge=dmge,
+        )
 
-        #if a message needs to be raised, get the approrpiate function to do so
+        # if a message needs to be raised, get the approrpiate function to do so
         if raises:
-            logLevel = getattr(logger,raises)  
+            logLevel = getattr(logger, raises)
         else:
             return error_list, warning_list
 
@@ -182,45 +194,49 @@ def generate_regex_error(
         error_message = regex_error_string
         error_val = invalid_entry
 
-        #return error and empty list for warnings
-        if raises == 'error':
+        # return error and empty list for warnings
+        if raises == "error":
             error_list = [error_row, error_col, error_message, error_val]
-        #return warning and empty list for errors
-        elif raises == 'warning':
+        # return warning and empty list for errors
+        elif raises == "warning":
             warning_list = [error_row, error_col, error_message, error_val]
-        
-        return error_list, warning_list       
+
+        return error_list, warning_list
 
     def generate_type_error(
-        val_rule: str, row_num: str, attribute_name: str, invalid_entry:str, dmge: DataModelGraphExplorer,
+        val_rule: str,
+        row_num: str,
+        attribute_name: str,
+        invalid_entry: str,
+        dmge: DataModelGraphExplorer,
     ) -> List[str]:
         """
-            Purpose:
-                Generate an logging error as well as a stored error message, when
-                a type error is encountered.
-            Input:
-                val_rule: str, defined in the schema.
-                row_num: str, row where the error was detected
-                attribute_name: str, attribute being validated
-            Returns:
-            logger.error or logger.warning.
-            Errors: List[str] Error details for further storage.
-            warnings: List[str] Warning details for further storage.
-            """
+        Purpose:
+            Generate an logging error as well as a stored error message, when
+            a type error is encountered.
+        Input:
+            val_rule: str, defined in the schema.
+            row_num: str, row where the error was detected
+            attribute_name: str, attribute being validated
+        Returns:
+        logger.error or logger.warning.
+        Errors: List[str] Error details for further storage.
+        warnings: List[str] Warning details for further storage.
+        """
 
         error_list = []
         warning_list = []
 
-        #Determine which, if any, message to raise
+        # Determine which, if any, message to raise
         raises = GenerateError.get_message_level(
-            dmge = dmge,
-            attribute_name = attribute_name,
-            val_rule = val_rule,
-            )
+            dmge=dmge,
+            attribute_name=attribute_name,
+            val_rule=val_rule,
+        )
 
-        #if a message needs to be raised, get the approrpiate function to do so
+        # if a message needs to be raised, get the approrpiate function to do so
         if raises:
-            logLevel = getattr(logger,raises)  
+            logLevel = getattr(logger, raises)
         else:
             return error_list, warning_list
 
@@ -233,73 +249,78 @@ def generate_type_error(
         error_message = type_error_str
         error_val = invalid_entry
 
-        #TODO: not sure if this i needed (to split)
-        validation_rules=dmge.get_node_validation_rules(node_display_name=attribute_name)
-
-        #TODO: Can remove when handling updated so split within graph
-        if validation_rules and '::' in validation_rules[0]:
-                validation_rules = validation_rules[0].split("::")
+        # TODO: not sure if this i needed (to split)
+        validation_rules = dmge.get_node_validation_rules(
+            node_display_name=attribute_name
+        )
 
         # If IsNA rule is being used to allow `Not Applicable` entries, do not log a message
-        if error_val.lower() == 'not applicable' and rule_in_rule_list('IsNA', validation_rules):
-          pass  
+        if error_val.lower() == "not applicable" and rule_in_rule_list(
+            "IsNA", validation_rules
+        ):
+            pass
         else:
             logLevel(type_error_str)
-            #return error and empty list for warnings
-            if raises == 'error':
+            # return error and empty list for warnings
+            if raises == "error":
                 error_list = [error_row, error_col, error_message, error_val]
-            #return warning and empty list for errors
-            elif raises == 'warning':
+            # return warning and empty list for errors
+            elif raises == "warning":
                 warning_list = [error_row, error_col, error_message, error_val]
-        
-        return error_list, warning_list              
+
+        return error_list, warning_list
 
     def generate_url_error(
-        url: str, url_error: str, row_num: str, attribute_name: str, argument: str,
-        invalid_entry:str, dmge: DataModelGraphExplorer, val_rule: str,
+        url: str,
+        url_error: str,
+        row_num: str,
+        attribute_name: str,
+        argument: str,
+        invalid_entry: str,
+        dmge: DataModelGraphExplorer,
+        val_rule: str,
     ) -> List[str]:
         """
-            Purpose:
-                Generate an logging error as well as a stored error message, when
-                a URL error is encountered.
-
-                Types of errors included:
-                    - Invalid URL: Refers to a URL that brings up an error when 
-                        attempted to be accessed such as a HTTPError 404 Webpage Not Found.
-                    - Argument Error: this refers to a valid URL that does not 
-                        contain within it the arguments specified by the schema,
-                        such as 'protocols.io' or 'dox.doi.org'
-                    - Random Entry: this refers to an entry try that is not 
-                        validated to be a URL.
-                        e.g. 'lkejrlei', '0', 'not applicable'
-            Input:
-                url: str, that was input by the user.
-                url_error: str, error detected in url_validation()
-                attribute_name: str, attribute being validated
-                argument: str, argument being validated.
-            Returns:
-            logger.error or logger.warning.
-            Errors: List[str] Error details for further storage.
-            warnings: List[str] Warning details for further storage.
-            """
+        Purpose:
+            Generate an logging error as well as a stored error message, when
+            a URL error is encountered.
+
+            Types of errors included:
+                - Invalid URL: Refers to a URL that brings up an error when
+                    attempted to be accessed such as a HTTPError 404 Webpage Not Found.
+                - Argument Error: this refers to a valid URL that does not
+                    contain within it the arguments specified by the schema,
+                    such as 'protocols.io' or 'dox.doi.org'
+                - Random Entry: this refers to an entry try that is not
+                    validated to be a URL.
+                    e.g. 'lkejrlei', '0', 'not applicable'
+        Input:
+            url: str, that was input by the user.
+            url_error: str, error detected in url_validation()
+            attribute_name: str, attribute being validated
+            argument: str, argument being validated.
+        Returns:
+        logger.error or logger.warning.
+        Errors: List[str] Error details for further storage.
+        warnings: List[str] Warning details for further storage.
+        """
 
         error_list = []
         warning_list = []
-        
-        #Determine which, if any, message to raise
+
+        # Determine which, if any, message to raise
         raises = GenerateError.get_message_level(
-            val_rule = val_rule,
-            attribute_name = attribute_name,
-            dmge = dmge,
-            )
+            val_rule=val_rule,
+            attribute_name=attribute_name,
+            dmge=dmge,
+        )
 
-        #if a message needs to be raised, get the approrpiate function to do so
+        # if a message needs to be raised, get the approrpiate function to do so
         if raises:
-            logLevel = getattr(logger,raises)  
+            logLevel = getattr(logger, raises)
         else:
             return error_list, warning_list
 
-
         error_row = row_num  # index row of the manifest where the error presented.
         error_col = attribute_name  # Attribute name
         if url_error == "invalid_url":
@@ -328,99 +349,99 @@ def generate_url_error(
             error_message = random_entry_error_str
             error_val = f"URL Error: Random Entry"
 
-        #return error and empty list for warnings
-        if raises == 'error':
+        # return error and empty list for warnings
+        if raises == "error":
             error_list = [error_row, error_col, error_message, error_val]
-        #return warning and empty list for errors
-        elif raises == 'warning':
+        # return warning and empty list for errors
+        elif raises == "warning":
             warning_list = [error_row, error_col, error_message, error_val]
-        
-        return error_list, warning_list        
+
+        return error_list, warning_list
 
     def generate_cross_warning(
         val_rule: str,
         attribute_name: str,
         dmge: DataModelGraphExplorer,
-        matching_manifests = [],
-        missing_manifest_ID = None,
-        invalid_entry = None,
-        row_num = None,
-        
+        matching_manifests=[],
+        missing_manifest_ID=None,
+        invalid_entry=None,
+        row_num=None,
     ) -> List[str]:
         """
-            Purpose:
-                Generate an logging error as well as a stored error message, when
-                a cross validation error is encountered.
-            Input:
-                val_rule: str, defined in the schema.
-                matching_manifests: list of manifests with all values in the target attribute present
-                manifest_ID: str, synID of the target manifest missing the source value
-                attribute_name: str, attribute being validated
-                invalid_entry: str, value present in source manifest that is missing in the target
-                row_num: row in source manifest with value missing in target manifests             
-            Returns:
-            logger.error or logger.warning.
-            Errors: List[str] Error details for further storage.
-            warnings: List[str] Warning details for further storage.
-            """
+        Purpose:
+            Generate an logging error as well as a stored error message, when
+            a cross validation error is encountered.
+        Input:
+            val_rule: str, defined in the schema.
+            matching_manifests: list of manifests with all values in the target attribute present
+            manifest_ID: str, synID of the target manifest missing the source value
+            attribute_name: str, attribute being validated
+            invalid_entry: str, value present in source manifest that is missing in the target
+            row_num: row in source manifest with value missing in target manifests
+        Returns:
+        logger.error or logger.warning.
+        Errors: List[str] Error details for further storage.
+        warnings: List[str] Warning details for further storage.
+        """
         error_list = []
         warning_list = []
-        
-        #Determine which, if any, message to raise
+
+        # Determine which, if any, message to raise
         raises = GenerateError.get_message_level(
-            val_rule = val_rule,
-            attribute_name = attribute_name,
-            dmge = dmge,
-            )
+            val_rule=val_rule,
+            attribute_name=attribute_name,
+            dmge=dmge,
+        )
 
-        #if a message needs to be raised, get the approrpiate function to do so
+        # if a message needs to be raised, get the approrpiate function to do so
         if raises:
-            logLevel = getattr(logger,raises)  
+            logLevel = getattr(logger, raises)
         else:
             return error_list, warning_list
 
-        if val_rule.__contains__('matchAtLeast'):
-            cross_error_str = (
-                f"Value(s) {invalid_entry} from row(s) {row_num} of the attribute {attribute_name} in the source manifest are missing." )
-            cross_error_str += f" Manifest(s) {missing_manifest_ID} are missing the value(s)." if missing_manifest_ID else ""
-            
-        elif val_rule.__contains__('matchExactly'):
+        if val_rule.__contains__("matchAtLeast"):
+            cross_error_str = f"Value(s) {invalid_entry} from row(s) {row_num} of the attribute {attribute_name} in the source manifest are missing."
+            cross_error_str += (
+                f" Manifest(s) {missing_manifest_ID} are missing the value(s)."
+                if missing_manifest_ID
+                else ""
+            )
+
+        elif val_rule.__contains__("matchExactly"):
             if matching_manifests != []:
-                cross_error_str = (
-                    f"All values from attribute {attribute_name} in the source manifest are present in {len(matching_manifests)} manifests instead of only 1.")
-                cross_error_str += f" Manifests {matching_manifests} match the values in the source attribute." if matching_manifests else ""
-                    
-            elif val_rule.__contains__('set'):
-                cross_error_str = (
-                    f"No matches for the values from attribute {attribute_name} in the source manifest are present in any other manifests instead of being present in exactly 1. "
+                cross_error_str = f"All values from attribute {attribute_name} in the source manifest are present in {len(matching_manifests)} manifests instead of only 1."
+                cross_error_str += (
+                    f" Manifests {matching_manifests} match the values in the source attribute."
+                    if matching_manifests
+                    else ""
                 )
-            elif val_rule.__contains__('value'):
-                cross_error_str = (
-                    f"Value(s) {invalid_entry} from row(s) {row_num} of the attribute {attribute_name} in the source manifest are not present in only one other manifest. " 
-                )            
+
+            elif val_rule.__contains__("set"):
+                cross_error_str = f"No matches for the values from attribute {attribute_name} in the source manifest are present in any other manifests instead of being present in exactly 1. "
+            elif val_rule.__contains__("value"):
+                cross_error_str = f"Value(s) {invalid_entry} from row(s) {row_num} of the attribute {attribute_name} in the source manifest are not present in only one other manifest. "
 
         logLevel(cross_error_str)
         error_row = row_num  # index row of the manifest where the error presented.
         error_col = attribute_name  # Attribute name
         error_message = cross_error_str
-        error_val = invalid_entry #Value from source manifest missing from targets
-        
-        #return error and empty list for warnings
-        if raises == 'error':
+        error_val = invalid_entry  # Value from source manifest missing from targets
+
+        # return error and empty list for warnings
+        if raises == "error":
             error_list = [error_row, error_col, error_message, error_val]
-        #return warning and empty list for errors
-        elif raises == 'warning':
+        # return warning and empty list for errors
+        elif raises == "warning":
             warning_list = [error_row, error_col, error_message, error_val]
-        
-        return error_list, warning_list        
 
+        return error_list, warning_list
 
     def generate_content_error(
         val_rule: str,
         attribute_name: str,
         dmge: DataModelGraphExplorer,
-        row_num = None,
-        error_val = None,    
+        row_num=None,
+        error_val=None,
     ) -> (List[str], List[str]):
         """
         Purpose:
@@ -448,84 +469,74 @@ def generate_content_error(
         if error_val:
             error_val = iterable_to_str_list(set(error_val))
 
-        #Determine which, if any, message to raise
+        # Determine which, if any, message to raise
         raises = GenerateError.get_message_level(
             val_rule=val_rule,
-            attribute_name = attribute_name,
-            dmge = dmge,
-            )
+            attribute_name=attribute_name,
+            dmge=dmge,
+        )
 
-        #if a message needs to be raised, get the approrpiate function to do so
+        # if a message needs to be raised, get the approrpiate function to do so
         if raises:
-            logLevel = getattr(logger,raises)  
+            logLevel = getattr(logger, raises)
         else:
             return error_list, warning_list
-        
-        #log warning or error message
-        if val_rule.startswith('recommended'):
-            content_error_str = (
-                f"Column {attribute_name} is recommended but empty."
-            )
+
+        # log warning or error message
+        if val_rule.startswith("recommended"):
+            content_error_str = f"Column {attribute_name} is recommended but empty."
             logLevel(content_error_str)
             error_message = content_error_str
 
-            if raises == 'error':
+            if raises == "error":
                 error_list = [error_col, error_message]
-            #return warning and empty list for errors
-            elif raises == 'warning':
+            # return warning and empty list for errors
+            elif raises == "warning":
                 warning_list = [error_col, error_message]
 
             return error_list, warning_list
 
-        elif val_rule.startswith('unique'):    
-            content_error_str = (
-                f"Column {attribute_name} has the duplicate value(s) {error_val} in rows: {row_num}."
-            )
+        elif val_rule.startswith("unique"):
+            content_error_str = f"Column {attribute_name} has the duplicate value(s) {error_val} in rows: {row_num}."
 
-        elif val_rule.startswith('protectAges'):
-            content_error_str = (
-                f"Column {attribute_name} contains ages that should be censored in rows: {row_num}."
-            )           
+        elif val_rule.startswith("protectAges"):
+            content_error_str = f"Column {attribute_name} contains ages that should be censored in rows: {row_num}."
 
-        elif val_rule.startswith('inRange'):
-            content_error_str = (
-                f"{attribute_name} values in rows {row_num} are out of the specified range."
-            )
-        elif val_rule.startswith('date'):
+        elif val_rule.startswith("inRange"):
+            content_error_str = f"{attribute_name} values in rows {row_num} are out of the specified range."
+        elif val_rule.startswith("date"):
             content_error_str = (
                 f"{attribute_name} values in rows {row_num} are not parsable as dates."
-            )  
-        elif val_rule.startswith('IsNA'):
-            content_error_str = (
-                f"{attribute_name} values in rows {row_num} are not marked as 'Not Applicable'."
-            )  
+            )
+        elif val_rule.startswith("IsNA"):
+            content_error_str = f"{attribute_name} values in rows {row_num} are not marked as 'Not Applicable'."
 
         if val_rule != "IsNA":
             logLevel(content_error_str)
-            error_row = row_num 
+            error_row = row_num
             error_message = content_error_str
-            #return error and empty list for warnings
-            if raises == 'error':
+            # return error and empty list for warnings
+            if raises == "error":
                 error_list = [error_row, error_col, error_message, error_val]
-            #return warning and empty list for errors
-            elif raises == 'warning':
+            # return warning and empty list for errors
+            elif raises == "warning":
                 warning_list = [error_row, error_col, error_message, error_val]
-        
+
         return error_list, warning_list
 
     def get_message_level(
         dmge: DataModelGraphExplorer,
         attribute_name: str,
         val_rule: str,
-        ) -> str:
+    ) -> str:
         """
         Purpose:
             Determine whether an error or warning message should be logged and displayed
-            
-            if node is not required, 
+
+            if node is not required,
                 return warning
-            if node is recommended and requried, 
-                return None    
+            if node is recommended and requried,
+                return None
             for other rules, parse possible, if not use default specified in validation_rule_info
 
         Input:
@@ -541,22 +552,26 @@ def get_message_level(
         rule_parts = val_rule.split(" ")
         rule_info = validation_rule_info()
 
-        #set message level to default and change after
-        if rule_parts[0] != 'schema':
-            level = rule_info[rule_parts[0]]['default_message_level']
+        # set message level to default and change after
+        if rule_parts[0] != "schema":
+            level = rule_info[rule_parts[0]]["default_message_level"]
         # Parse rule for level, set to default if not specified
-        if rule_parts[-1].lower() == 'error' or rule_parts[0] == 'schema':
-            level = 'error'
-        elif rule_parts[-1].lower() == 'warning':
-            level = 'warning'        
+        if rule_parts[-1].lower() == "error" or rule_parts[0] == "schema":
+            level = "error"
+        elif rule_parts[-1].lower() == "warning":
+            level = "warning"
         elif not dmge.get_node_required(node_display_name=attribute_name):
             # If not required raise warnings to notify
-            level = 'warning' 
-        elif dmge.get_node_required(node_display_name=attribute_name) and 'recommended' in val_rule:
+            level = "warning"
+        elif (
+            dmge.get_node_required(node_display_name=attribute_name)
+            and "recommended" in val_rule
+        ):
             level = None
-            
+
         return level
 
+
 class ValidateAttribute(object):
     """
     A collection of functions to validate manifest attributes.
@@ -572,37 +587,48 @@ class ValidateAttribute(object):
         - Add string length validator
     """
 
-    def get_target_manifests(target_component, project_scope: List, access_token: str = None):
+    def get_target_manifests(
+        target_component, project_scope: List, access_token: str = None
+    ):
         t_manifest_search = perf_counter()
-        target_manifest_IDs=[]
-        target_dataset_IDs=[]
-        
-        #login
+        target_manifest_IDs = []
+        target_dataset_IDs = []
+
+        # login
         try:
-            synStore = SynapseStorage(access_token=access_token, project_scope=project_scope)        
+            synStore = SynapseStorage(
+                access_token=access_token, project_scope=project_scope
+            )
         except SynapseNoCredentialsError as e:
             raise ValueError(
                 "No Synapse credentials were provided. Credentials must be provided to utilize cross-manfiest validation functionality."
-                ) from e
+            ) from e
 
-        #Get list of all projects user has access to
+        # Get list of all projects user has access to
         projects = synStore.getStorageProjects(project_scope=project_scope)
         for project in projects:
-            
-            #get all manifests associated with datasets in the projects
-            target_datasets=synStore.getProjectManifests(projectId=project[0])
+            # get all manifests associated with datasets in the projects
+            target_datasets = synStore.getProjectManifests(projectId=project[0])
 
-            #If the manifest includes the target component, include synID in list
+            # If the manifest includes the target component, include synID in list
             for target_dataset in target_datasets:
-                if target_component == target_dataset[-1][0].replace(" ","").lower() and target_dataset[1][0] != "":
+                if (
+                    target_component == target_dataset[-1][0].replace(" ", "").lower()
+                    and target_dataset[1][0] != ""
+                ):
                     target_manifest_IDs.append(target_dataset[1][0])
                     target_dataset_IDs.append(target_dataset[0][0])
 
-        logger.debug(f"Cross manifest gathering elapsed time {perf_counter()-t_manifest_search}")
-        return synStore, target_manifest_IDs, target_dataset_IDs    
+        logger.debug(
+            f"Cross manifest gathering elapsed time {perf_counter()-t_manifest_search}"
+        )
+        return synStore, target_manifest_IDs, target_dataset_IDs
 
     def list_validation(
-        self, val_rule: str, manifest_col: pd.core.series.Series, dmge: DataModelGraphExplorer,
+        self,
+        val_rule: str,
+        manifest_col: pd.core.series.Series,
+        dmge: DataModelGraphExplorer,
     ) -> (List[List[str]], List[List[str]], pd.core.series.Series):
         """
         Purpose:
@@ -625,32 +651,30 @@ def list_validation(
         manifest_col = manifest_col.astype(str)
         csv_re = comma_separated_list_regex()
 
-        rule_parts=val_rule.lower().split(" ")
+        rule_parts = val_rule.lower().split(" ")
         if len(rule_parts) > 1:
-            list_robustness=rule_parts[1]
+            list_robustness = rule_parts[1]
         else:
-            list_robustness = 'strict'
-
+            list_robustness = "strict"
 
-        if list_robustness == 'strict':
-        # This will capture any if an entry is not formatted properly. Only for strict lists
+        if list_robustness == "strict":
+            # This will capture any if an entry is not formatted properly. Only for strict lists
             for i, list_string in enumerate(manifest_col):
-                if not re.fullmatch(csv_re,list_string):
+                if not re.fullmatch(csv_re, list_string):
                     list_error = "not_comma_delimited"
                     vr_errors, vr_warnings = GenerateError.generate_list_error(
-                            list_string,
-                            row_num=str(i + 2),
-                            attribute_name=manifest_col.name,
-                            list_error=list_error,
-                            invalid_entry=manifest_col[i],
-                            dmge = dmge,
-                            val_rule = val_rule, 
-                        )
+                        list_string,
+                        row_num=str(i + 2),
+                        attribute_name=manifest_col.name,
+                        list_error=list_error,
+                        invalid_entry=manifest_col[i],
+                        dmge=dmge,
+                        val_rule=val_rule,
+                    )
                     if vr_errors:
                         errors.append(vr_errors)
                     if vr_warnings:
                         warnings.append(vr_warnings)
-                
 
         # Convert string to list.
         manifest_col = parse_str_series_to_list(manifest_col)
@@ -658,7 +682,10 @@ def list_validation(
         return errors, warnings, manifest_col
 
     def regex_validation(
-        self, val_rule: str, manifest_col: pd.core.series.Series, dmge: DataModelGraphExplorer,
+        self,
+        val_rule: str,
+        manifest_col: pd.core.series.Series,
+        dmge: DataModelGraphExplorer,
     ) -> (List[List[str]], List[List[str]]):
         """
         Purpose:
@@ -671,9 +698,9 @@ def regex_validation(
             - dmge: DataModelGraphExplorer Object
             Using this module requres validation rules written in the following manner:
                 'regex module regular expression'
-                - regex: is an exact string specifying that the input is to be validated as a 
+                - regex: is an exact string specifying that the input is to be validated as a
                 regular expression.
-                - module: is the name of the module within re to run ie. search. 
+                - module: is the name of the module within re to run ie. search.
                 - regular_expression: is the regular expression with which to validate
                 the user input.
         Returns:
@@ -682,7 +709,7 @@ def regex_validation(
             logger.error or logger.warning.
             Errors: List[str] Error details for further storage.
             warnings: List[str] Warning details for further storage.
-        TODO: 
+        TODO:
             move validation to convert step.
         """
 
@@ -700,11 +727,13 @@ def regex_validation(
         errors = []
         warnings = []
 
-        validation_rules = dmge.get_node_validation_rules(node_display_name=manifest_col.name)
-        if validation_rules and '::' in validation_rules[0]:
-                validation_rules = validation_rules[0].split("::")
+        validation_rules = dmge.get_node_validation_rules(
+            node_display_name=manifest_col.name
+        )
+        if validation_rules and "::" in validation_rules[0]:
+            validation_rules = validation_rules[0].split("::")
         # Handle case where validating re's within a list.
-        if re.search('list',"|".join(validation_rules)):
+        if re.search("list", "|".join(validation_rules)):
             if type(manifest_col[0]) == str:
                 # Convert string to list.
                 manifest_col = parse_str_series_to_list(manifest_col)
@@ -716,14 +745,14 @@ def regex_validation(
                         re_to_check
                     ):
                         vr_errors, vr_warnings = GenerateError.generate_regex_error(
-                                val_rule = val_rule,
-                                reg_expression = reg_expression,
-                                row_num=str(i + 2),
-                                module_to_call=reg_exp_rules[1],
-                                attribute_name=manifest_col.name,
-                                invalid_entry=manifest_col[i],
-                                dmge = dmge,
-                            )
+                            val_rule=val_rule,
+                            reg_expression=reg_expression,
+                            row_num=str(i + 2),
+                            module_to_call=reg_exp_rules[1],
+                            attribute_name=manifest_col.name,
+                            invalid_entry=manifest_col[i],
+                            dmge=dmge,
+                        )
                         if vr_errors:
                             errors.append(vr_errors)
                         if vr_warnings:
@@ -737,14 +766,14 @@ def regex_validation(
                     re_to_check
                 ):
                     vr_errors, vr_warnings = GenerateError.generate_regex_error(
-                            val_rule = val_rule,
-                            reg_expression = reg_expression,
-                            row_num=str(i + 2),
-                            module_to_call=reg_exp_rules[1],
-                            attribute_name=manifest_col.name,
-                            invalid_entry=manifest_col[i],
-                            dmge = dmge,
-                        )
+                        val_rule=val_rule,
+                        reg_expression=reg_expression,
+                        row_num=str(i + 2),
+                        module_to_call=reg_exp_rules[1],
+                        attribute_name=manifest_col.name,
+                        invalid_entry=manifest_col[i],
+                        dmge=dmge,
+                    )
                     if vr_errors:
                         errors.append(vr_errors)
                     if vr_warnings:
@@ -753,7 +782,10 @@ def regex_validation(
         return errors, warnings
 
     def type_validation(
-        self, val_rule: str, manifest_col: pd.core.series.Series, dmge: DataModelGraphExplorer,
+        self,
+        val_rule: str,
+        manifest_col: pd.core.series.Series,
+        dmge: DataModelGraphExplorer,
     ) -> (List[List[str]], List[List[str]]):
         """
         Purpose:
@@ -775,10 +807,10 @@ def type_validation(
             Convert all inputs to .lower() just to prevent any entry errors.
         """
         specified_type = {
-            'num': (int, np.int64, float),
-            'int': (int, np.int64),
-            'float': (float),
-            'str': (str),
+            "num": (int, np.int64, float),
+            "int": (int, np.int64),
+            "float": (float),
+            "str": (str),
         }
 
         errors = []
@@ -788,12 +820,12 @@ def type_validation(
             for i, value in enumerate(manifest_col):
                 if bool(value) and not isinstance(value, specified_type[val_rule]):
                     vr_errors, vr_warnings = GenerateError.generate_type_error(
-                            val_rule = val_rule ,
-                            row_num=str(i + 2),
-                            attribute_name=manifest_col.name,
-                            invalid_entry=str(manifest_col[i]),
-                            dmge = dmge,
-                        )
+                        val_rule=val_rule,
+                        row_num=str(i + 2),
+                        attribute_name=manifest_col.name,
+                        invalid_entry=str(manifest_col[i]),
+                        dmge=dmge,
+                    )
                     if vr_errors:
                         errors.append(vr_errors)
                     if vr_warnings:
@@ -802,19 +834,21 @@ def type_validation(
             for i, value in enumerate(manifest_col):
                 if bool(value) and not isinstance(value, specified_type[val_rule]):
                     vr_errors, vr_warnings = GenerateError.generate_type_error(
-                            val_rule = val_rule,
-                            row_num=str(i + 2),
-                            attribute_name=manifest_col.name,
-                            invalid_entry=str(manifest_col[i]),
-                            dmge = dmge,
-                        )
+                        val_rule=val_rule,
+                        row_num=str(i + 2),
+                        attribute_name=manifest_col.name,
+                        invalid_entry=str(manifest_col[i]),
+                        dmge=dmge,
+                    )
                     if vr_errors:
                         errors.append(vr_errors)
                     if vr_warnings:
                         warnings.append(vr_warnings)
         return errors, warnings
 
-    def url_validation(self, val_rule: str, manifest_col: str, dmge: DataModelGraphExplorer) -> (List[List[str]], List[List[str]]):
+    def url_validation(
+        self, val_rule: str, manifest_col: str, dmge: DataModelGraphExplorer
+    ) -> (List[List[str]], List[List[str]]):
         """
         Purpose:
             Validate URL's submitted for a particular attribute in a manifest.
@@ -837,7 +871,7 @@ def url_validation(self, val_rule: str, manifest_col: str, dmge: DataModelGraphE
         for i, url in enumerate(manifest_col):
             # Check if a random phrase, string or number was added and
             # log the appropriate error.
-            if not isinstance(url,str) or not (
+            if not isinstance(url, str) or not (
                 urlparse(url).scheme
                 + urlparse(url).netloc
                 + urlparse(url).params
@@ -848,15 +882,15 @@ def url_validation(self, val_rule: str, manifest_col: str, dmge: DataModelGraphE
                 url_error = "random_entry"
                 valid_url = False
                 vr_errors, vr_warnings = GenerateError.generate_url_error(
-                        url,
-                        url_error=url_error,
-                        row_num=str(i + 2),
-                        attribute_name=manifest_col.name,
-                        argument=url_args,
-                        invalid_entry=manifest_col[i],
-                        dmge = dmge,
-                        val_rule = val_rule,
-                    )
+                    url,
+                    url_error=url_error,
+                    row_num=str(i + 2),
+                    attribute_name=manifest_col.name,
+                    argument=url_args,
+                    invalid_entry=manifest_col[i],
+                    dmge=dmge,
+                    val_rule=val_rule,
+                )
                 if vr_errors:
                     errors.append(vr_errors)
                 if vr_warnings:
@@ -876,15 +910,15 @@ def url_validation(self, val_rule: str, manifest_col: str, dmge: DataModelGraphE
                     valid_url = False
                     url_error = "invalid_url"
                     vr_errors, vr_warnings = GenerateError.generate_url_error(
-                            url,
-                            url_error=url_error,
-                            row_num=str(i + 2),
-                            attribute_name=manifest_col.name,
-                            argument=url_args,
-                            invalid_entry=manifest_col[i],
-                            dmge = dmge,
-                            val_rule = val_rule,
-                        )
+                        url,
+                        url_error=url_error,
+                        row_num=str(i + 2),
+                        attribute_name=manifest_col.name,
+                        argument=url_args,
+                        invalid_entry=manifest_col[i],
+                        dmge=dmge,
+                        val_rule=val_rule,
+                    )
                     if vr_errors:
                         errors.append(vr_errors)
                     if vr_warnings:
@@ -896,15 +930,15 @@ def url_validation(self, val_rule: str, manifest_col: str, dmge: DataModelGraphE
                         if arg not in url:
                             url_error = "arg_error"
                             vr_errors, vr_warnings = GenerateError.generate_url_error(
-                                    url,
-                                    url_error=url_error,
-                                    row_num=str(i + 2),
-                                    attribute_name=manifest_col.name,
-                                    argument=arg,
-                                    invalid_entry=manifest_col[i],
-                                    dmge = dmge,
-                                    val_rule = val_rule,
-                                )
+                                url,
+                                url_error=url_error,
+                                row_num=str(i + 2),
+                                attribute_name=manifest_col.name,
+                                argument=arg,
+                                invalid_entry=manifest_col[i],
+                                dmge=dmge,
+                                val_rule=val_rule,
+                            )
                             if vr_errors:
                                 errors.append(vr_errors)
                             if vr_warnings:
@@ -912,7 +946,12 @@ def url_validation(self, val_rule: str, manifest_col: str, dmge: DataModelGraphE
         return errors, warnings
 
     def cross_validation(
-        self, val_rule: str, manifest_col: pd.core.series.Series, project_scope: List, dmge: DataModelGraphExplorer, access_token: str,
+        self,
+        val_rule: str,
+        manifest_col: pd.core.series.Series,
+        project_scope: List,
+        dmge: DataModelGraphExplorer,
+        access_token: str,
     ) -> List[List[str]]:
         """
         Purpose:
@@ -924,45 +963,51 @@ def cross_validation(
                 attribute in the manifest
             - dmge: DataModelGraphExplorer Object
         Output:
-            This function will return errors when values in the current manifest's attribute 
+            This function will return errors when values in the current manifest's attribute
             are not fully present in the correct amount of other manifests.
         """
         errors = []
         warnings = []
         missing_values = {}
-        missing_manifest_log={}
-        present_manifest_log=[]
+        missing_manifest_log = {}
+        present_manifest_log = []
         target_column = pd.Series(dtype=object)
-        #parse sources and targets
-        source_attribute=manifest_col.name
+        # parse sources and targets
+        source_attribute = manifest_col.name
         [target_component, target_attribute] = val_rule.lower().split(" ")[1].split(".")
-        scope=val_rule.lower().split(" ")[2]
-        target_column.name=target_attribute
-
-        
-        #Get IDs of manifests with target component
-        synStore, target_manifest_IDs, target_dataset_IDs = ValidateAttribute.get_target_manifests(target_component, project_scope, access_token)
+        scope = val_rule.lower().split(" ")[2]
+        target_column.name = target_attribute
+
+        # Get IDs of manifests with target component
+        (
+            synStore,
+            target_manifest_IDs,
+            target_dataset_IDs,
+        ) = ValidateAttribute.get_target_manifests(
+            target_component, project_scope, access_token
+        )
 
         t_cross_manifest = perf_counter()
-        #Read each manifest
-        for target_manifest_ID, target_dataset_ID in zip(target_manifest_IDs,target_dataset_IDs):
+        # Read each manifest
+        for target_manifest_ID, target_dataset_ID in zip(
+            target_manifest_IDs, target_dataset_IDs
+        ):
             entity = synStore.getDatasetManifest(
-                datasetId = target_dataset_ID,
-                downloadFile = True
-                )
-            target_manifest=pd.read_csv(entity.path)
+                datasetId=target_dataset_ID, downloadFile=True
+            )
+            target_manifest = pd.read_csv(entity.path)
 
-            #convert manifest column names into validation rule input format - 
-            column_names={}
+            # convert manifest column names into validation rule input format -
+            column_names = {}
             for name in target_manifest.columns:
-                column_names[name.replace(" ","").lower()]=name
+                column_names[name.replace(" ", "").lower()] = name
 
-            if scope.__contains__('set'):
-                #If the manifest has the target attribute for the component do the cross validation
-                if target_attribute in column_names:                    
+            if scope.__contains__("set"):
+                # If the manifest has the target attribute for the component do the cross validation
+                if target_attribute in column_names:
                     target_column = target_manifest[column_names[target_attribute]]
 
-                    #Do the validation on both columns
+                    # Do the validation on both columns
                     missing_values = manifest_col[~manifest_col.isin(target_column)]
 
                     if missing_values.empty:
@@ -970,98 +1015,116 @@ def cross_validation(
                     else:
                         missing_manifest_log[target_manifest_ID] = missing_values
 
-            elif scope.__contains__('value'):
+            elif scope.__contains__("value"):
                 if target_attribute in column_names:
-                    target_manifest.rename(columns={column_names[target_attribute]: target_attribute}, inplace=True)
-                    
+                    target_manifest.rename(
+                        columns={column_names[target_attribute]: target_attribute},
+                        inplace=True,
+                    )
+
                     target_column = pd.concat(
-                        objs = [target_column, target_manifest[target_attribute]],
-                        join = 'outer',
-                        ignore_index= True,
-                    )                
-                    target_column = target_column.astype('object')
-                    #print(target_column)
-                    
-        
-        
-        missing_rows=[]
-        missing_values=[]  
-
-
-        if scope.__contains__('value'):
+                        objs=[target_column, target_manifest[target_attribute]],
+                        join="outer",
+                        ignore_index=True,
+                    )
+                    target_column = target_column.astype("object")
+                    # print(target_column)
+
+        missing_rows = []
+        missing_values = []
+
+        if scope.__contains__("value"):
             missing_values = manifest_col[~manifest_col.isin(target_column)]
-            duplicated_values = manifest_col[manifest_col.isin(target_column[target_column.duplicated()])]
-            
-            if val_rule.__contains__('matchAtLeastOne') and not missing_values.empty:
+            duplicated_values = manifest_col[
+                manifest_col.isin(target_column[target_column.duplicated()])
+            ]
+
+            if val_rule.__contains__("matchAtLeastOne") and not missing_values.empty:
                 missing_rows = missing_values.index.to_numpy() + 2
                 missing_rows = np_array_to_str_list(missing_rows)
                 vr_errors, vr_warnings = GenerateError.generate_cross_warning(
-                        val_rule = val_rule,
-                        row_num = missing_rows,
-                        attribute_name = source_attribute,
-                        invalid_entry = iterable_to_str_list(missing_values),
-                        dmge = dmge,
-                    )
+                    val_rule=val_rule,
+                    row_num=missing_rows,
+                    attribute_name=source_attribute,
+                    invalid_entry=iterable_to_str_list(missing_values),
+                    dmge=dmge,
+                )
                 if vr_errors:
                     errors.append(vr_errors)
                 if vr_warnings:
                     warnings.append(vr_warnings)
-            elif val_rule.__contains__('matchExactlyOne') and (duplicated_values.any() or missing_values.any()):
-                invalid_values  = pd.merge(duplicated_values,missing_values,how='outer')
-                invalid_rows    = pd.merge(duplicated_values,missing_values,how='outer',left_index=True,right_index=True).index.to_numpy() + 2
-                invalid_rows    = np_array_to_str_list(invalid_rows)
+            elif val_rule.__contains__("matchExactlyOne") and (
+                duplicated_values.any() or missing_values.any()
+            ):
+                invalid_values = pd.merge(
+                    duplicated_values, missing_values, how="outer"
+                )
+                invalid_rows = (
+                    pd.merge(
+                        duplicated_values,
+                        missing_values,
+                        how="outer",
+                        left_index=True,
+                        right_index=True,
+                    ).index.to_numpy()
+                    + 2
+                )
+                invalid_rows = np_array_to_str_list(invalid_rows)
                 vr_errors, vr_warnings = GenerateError.generate_cross_warning(
-                        val_rule = val_rule,
-                        row_num = invalid_rows,
-                        attribute_name = source_attribute, 
-                        invalid_entry = iterable_to_str_list(invalid_values.squeeze()),
-                        dmge = dmge,
-                    )
+                    val_rule=val_rule,
+                    row_num=invalid_rows,
+                    attribute_name=source_attribute,
+                    invalid_entry=iterable_to_str_list(invalid_values.squeeze()),
+                    dmge=dmge,
+                )
                 if vr_errors:
                     errors.append(vr_errors)
                 if vr_warnings:
                     warnings.append(vr_warnings)
-            
-
-            
-        #generate warnings if necessary
-        elif scope.__contains__('set'):
-            if val_rule.__contains__('matchAtLeastOne') and len(present_manifest_log) < 1:     
-                missing_entries = list(missing_manifest_log.values()) 
-                missing_manifest_IDs = list(missing_manifest_log.keys()) 
+
+        # generate warnings if necessary
+        elif scope.__contains__("set"):
+            if (
+                val_rule.__contains__("matchAtLeastOne")
+                and len(present_manifest_log) < 1
+            ):
+                missing_entries = list(missing_manifest_log.values())
+                missing_manifest_IDs = list(missing_manifest_log.keys())
                 for missing_entry in missing_entries:
-                    missing_rows.append(missing_entry.index[0]+2)
+                    missing_rows.append(missing_entry.index[0] + 2)
                     missing_values.append(missing_entry.values[0])
-                    
-                missing_rows=iterable_to_str_list(set(missing_rows))
-                missing_values=iterable_to_str_list(set(missing_values))
-                
+
+                missing_rows = iterable_to_str_list(set(missing_rows))
+                missing_values = iterable_to_str_list(set(missing_values))
+
                 vr_errors, vr_warnings = GenerateError.generate_cross_warning(
-                        val_rule = val_rule,
-                        row_num = missing_rows,
-                        attribute_name = source_attribute,
-                        invalid_entry = missing_values,
-                        missing_manifest_ID = missing_manifest_IDs,
-                        dmge = dmge,
-                    )
+                    val_rule=val_rule,
+                    row_num=missing_rows,
+                    attribute_name=source_attribute,
+                    invalid_entry=missing_values,
+                    missing_manifest_ID=missing_manifest_IDs,
+                    dmge=dmge,
+                )
                 if vr_errors:
                     errors.append(vr_errors)
                 if vr_warnings:
                     warnings.append(vr_warnings)
-            elif val_rule.__contains__('matchExactlyOne') and len(present_manifest_log) != 1:
+            elif (
+                val_rule.__contains__("matchExactlyOne")
+                and len(present_manifest_log) != 1
+            ):
                 vr_errors, vr_warnings = GenerateError.generate_cross_warning(
-                        val_rule = val_rule,
-                        attribute_name = source_attribute,
-                        matching_manifests = present_manifest_log,
-                        dmge = dmge,
-                    )
+                    val_rule=val_rule,
+                    attribute_name=source_attribute,
+                    matching_manifests=present_manifest_log,
+                    dmge=dmge,
+                )
                 if vr_errors:
                     errors.append(vr_errors)
                 if vr_warnings:
                     warnings.append(vr_warnings)
-                
 
-        logger.debug(f"cross manifest validation time {perf_counter()-t_cross_manifest}")
+        logger.debug(
+            f"cross manifest validation time {perf_counter()-t_cross_manifest}"
+        )
         return errors, warnings
-
-
diff --git a/schematic/models/validate_manifest.py b/schematic/models/validate_manifest.py
index ff180998a..b4e5f12f7 100644
--- a/schematic/models/validate_manifest.py
+++ b/schematic/models/validate_manifest.py
@@ -10,6 +10,7 @@
 import re
 import sys
 from time import perf_counter
+from numbers import Number
 
 # allows specifying explicit variable types
 from typing import Any, Dict, Optional, Text, List
@@ -19,29 +20,32 @@
 from urllib import error
 
 from schematic.models.validate_attribute import ValidateAttribute, GenerateError
+
 from schematic.schemas.data_model_graph import DataModelGraphExplorer
 from schematic.store.synapse import SynapseStorage
 from schematic.models.GE_Helpers import GreatExpectationsHelpers
 from schematic.utils.validate_rules_utils import validation_rule_info
 from schematic.utils.validate_utils import rule_in_rule_list
+from schematic.utils.schema_utils import extract_component_validation_rules
 
 logger = logging.getLogger(__name__)
 
+
 class ValidateManifest(object):
     def __init__(self, errors, manifest, manifestPath, dmge, jsonSchema):
         self.errors = errors
         self.manifest = manifest
         self.manifestPath = manifestPath
         self.dmge = dmge
-        self.jsonSchema = jsonSchema       
+        self.jsonSchema = jsonSchema
 
     def get_multiple_types_error(
         self, validation_rules: list, attribute_name: str, error_type: str
     ) -> List[str]:
         """
-            Generate error message for errors when trying to specify 
-            multiple validation rules.
-            """
+        Generate error message for errors when trying to specify
+        multiple validation rules.
+        """
         error_col = attribute_name  # Attribute name
         if error_type == "too_many_rules":
             error_str = (
@@ -62,7 +66,12 @@ def get_multiple_types_error(
         return ["NA", error_col, error_message, error_val]
 
     def validate_manifest_rules(
-        self, manifest: pd.core.frame.DataFrame, dmge: DataModelGraphExplorer, restrict_rules: bool, project_scope: List, access_token: Optional[str] = None,
+        self,
+        manifest: pd.core.frame.DataFrame,
+        dmge: DataModelGraphExplorer,
+        restrict_rules: bool,
+        project_scope: List,
+        access_token: Optional[str] = None,
     ) -> (pd.core.frame.DataFrame, List[List[str]]):
         """
         Purpose:
@@ -76,17 +85,17 @@ def validate_manifest_rules(
                 initialized within models/metadata.py
         Returns:
             manifest: pd.core.frame.DataFrame
-                If a 'list' validatior is run, the manifest needs to be 
+                If a 'list' validatior is run, the manifest needs to be
                 updated to change the attribute column values to a list.
                 In this case the manifest will be updated then exported.
             errors: List[List[str]]
                 If any errors are generated they will be added to an errors
                 list log recording the following information:
                 [error_row, error_col, error_message, error_val]
-        TODO: 
+        TODO:
             -Investigate why a :: delimiter is breaking up the
                 validation rules without me having to do anything...
-            - Move the rules formatting validation to the JSONLD 
+            - Move the rules formatting validation to the JSONLD
                 generation script.
         """
 
@@ -95,19 +104,19 @@ def validate_manifest_rules(
 
         validation_types = validation_rule_info()
 
-        type_dict={
+        type_dict = {
             "float64": float,
             "int64": int,
             "str": str,
         }
 
-        unimplemented_expectations=[
+        unimplemented_expectations = [
             "url",
             "list",
             "regex.*",
             "matchAtLeastOne.*",
             "matchExactlyOne.*",
-            ]
+        ]
 
         in_house_rules = [
             "int",
@@ -122,67 +131,69 @@ def validate_manifest_rules(
         ]
 
         # initialize error and warning handling lists.
-        errors = []   
-        warnings = [] 
+        errors = []
+        warnings = []
 
         if not restrict_rules:
             t_GE = perf_counter()
-            #operations necessary to set up and run ge suite validation
-            ge_helpers=GreatExpectationsHelpers(
+            # operations necessary to set up and run ge suite validation
+            ge_helpers = GreatExpectationsHelpers(
                 dmge=dmge,
                 unimplemented_expectations=unimplemented_expectations,
-                manifest = manifest,
-                manifestPath = self.manifestPath,
-                )
+                manifest=manifest,
+                manifestPath=self.manifestPath,
+            )
 
             ge_helpers.build_context()
             ge_helpers.build_expectation_suite()
             ge_helpers.build_checkpoint()
 
             try:
-                #run GE validation
+                # run GE validation
                 results = ge_helpers.context.run_checkpoint(
                     checkpoint_name=ge_helpers.checkpoint_name,
                     batch_request={
                         "runtime_parameters": {"batch_data": manifest},
-                        "batch_identifiers": {
-                            "default_identifier_name": "manifestID"
-                        },
+                        "batch_identifiers": {"default_identifier_name": "manifestID"},
                     },
-                    result_format={'result_format': 'COMPLETE'},
-                )       
+                    result_format={"result_format": "COMPLETE"},
+                )
             finally:
-                ge_helpers.context.delete_checkpoint(ge_helpers.checkpoint_name) 
-                ge_helpers.context.delete_expectation_suite(ge_helpers.expectation_suite_name)
-        
-            validation_results = results.list_validation_results()            
+                ge_helpers.context.delete_checkpoint(ge_helpers.checkpoint_name)
+                ge_helpers.context.delete_expectation_suite(
+                    ge_helpers.expectation_suite_name
+                )
+
+            validation_results = results.list_validation_results()
 
-            #parse validation results dict and generate errors
+            # parse validation results dict and generate errors
             errors, warnings = ge_helpers.generate_errors(
-                errors = errors,
-                warnings = warnings,
-                validation_results = validation_results,
-                validation_types = validation_types,
-                dmge = dmge,
-                )        
-            logger.debug(f"GE elapsed time {perf_counter()-t_GE}")       
-        else:             
-            logger.info("Great Expetations suite will not be utilized.")  
-
-        t_err=perf_counter()
-        regex_re=re.compile('regex.*')
+                errors=errors,
+                warnings=warnings,
+                validation_results=validation_results,
+                validation_types=validation_types,
+                dmge=dmge,
+            )
+            logger.debug(f"GE elapsed time {perf_counter()-t_GE}")
+        else:
+            logger.info("Great Expetations suite will not be utilized.")
+
+        t_err = perf_counter()
+        regex_re = re.compile("regex.*")
         for col in manifest.columns:
-            
             # remove trailing/leading whitespaces from manifest
-            manifest.applymap(lambda x: x.strip() if isinstance(x, str) else x)
+            manifest.map(lambda x: x.strip() if isinstance(x, str) else x)
             validation_rules = dmge.get_node_validation_rules(node_display_name=col)
 
-            #TODO: Can remove when handling updated so split within graph
-            if validation_rules and '::' in validation_rules[0]:
-                validation_rules = validation_rules[0].split("::")
+            # Parse the validation rules
+            if validation_rules and isinstance(validation_rules, dict):
+                validation_rules = extract_component_validation_rules(
+                    manifest_component=manifest["Component"][0],
+                    validation_rules=validation_rules,
+                )
 
             # Check that attribute rules conform to limits:
-            # no more than two rules for an attribute. 
+            # no more than two rules for an attribute.
             # As more combinations get added, may want to bring out into its own function / or use validate_rules_utils?
             if len(validation_rules) > 2:
                 errors.append(
@@ -194,20 +205,27 @@ def validate_manifest_rules(
             # Given a validation rule, run validation. Skip validations already performed by GE
             for rule in validation_rules:
                 validation_type = rule.split(" ")[0]
-                if rule_in_rule_list(rule,unimplemented_expectations) or (rule_in_rule_list(rule,in_house_rules) and restrict_rules):
-                    if not rule_in_rule_list(rule,in_house_rules):
-                        logger.warning(f"Validation rule {rule.split(' ')[0]} has not been implemented in house and cannnot be validated without Great Expectations.")
-                        continue  
+                if rule_in_rule_list(rule, unimplemented_expectations) or (
+                    rule_in_rule_list(rule, in_house_rules) and restrict_rules
+                ):
+                    if not rule_in_rule_list(rule, in_house_rules):
+                        logger.warning(
+                            f"Validation rule {rule.split(' ')[0]} has not been implemented in house and cannnot be validated without Great Expectations."
+                        )
+                        continue
 
-                    t_indiv_rule=perf_counter()
-                    #Validate for each individual validation rule.
+                    t_indiv_rule = perf_counter()
+                    # Validate for each individual validation rule.
                     validation_method = getattr(
-                            ValidateAttribute, validation_types[validation_type]['type']
-                        )
+                        ValidateAttribute, validation_types[validation_type]["type"]
+                    )
 
                     if validation_type == "list":
                         vr_errors, vr_warnings, manifest_col = validation_method(
-                            self, rule, manifest[col], dmge,
+                            self,
+                            rule,
+                            manifest[col],
+                            dmge,
                         )
                         manifest[col] = manifest_col
                     elif validation_type.lower().startswith("match"):
@@ -216,29 +234,42 @@ def validate_manifest_rules(
                         )
                     else:
                         vr_errors, vr_warnings = validation_method(
-                            self, rule, manifest[col], dmge,
+                            self,
+                            rule,
+                            manifest[col],
+                            dmge,
                         )
                     # Check for validation rule errors and add them to other errors.
                     if vr_errors:
                         errors.extend(vr_errors)
                     if vr_warnings:
                         warnings.extend(vr_warnings)
-                    logger.debug(f"Rule {rule} elapsed time: {perf_counter()-t_indiv_rule}")
+                    logger.debug(
+                        f"Rule {rule} elapsed time: {perf_counter()-t_indiv_rule}"
+                    )
         logger.debug(f"In House validation elapsed time {perf_counter()-t_err}")
         return manifest, errors, warnings
 
-    def validate_manifest_values(self, manifest, jsonSchema, dmge,
+    def validate_manifest_values(
+        self,
+        manifest,
+        jsonSchema,
+        dmge,
     ) -> (List[List[str]], List[List[str]]):
         t_json_schema = perf_counter()
 
         errors = []
         warnings = []
-        col_attr = {} # save the mapping between column index and attribute name
-        
+        col_attr = {}  # save the mapping between column index and attribute name
+
         # numerical values need to be type string for the jsonValidator
-        for col in manifest.select_dtypes(include=[int, np.int64, float, np.float64]).columns:
-            manifest[col]=manifest[col].astype('string')
-        manifest = manifest.applymap(lambda x: str(x) if isinstance(x, (int, np.int64, float, np.float64)) else x, na_action='ignore')
+        for col in manifest.select_dtypes(
+            include=[int, np.int64, float, np.float64]
+        ).columns:
+            manifest[col] = manifest[col].astype("string")
+        manifest = manifest.map(
+            lambda x: str(x) if isinstance(x, Number) else x, na_action="ignore"
+        )
 
         annotations = json.loads(manifest.to_json(orient="records"))
         for i, annotation in enumerate(annotations):
@@ -250,19 +281,40 @@ def validate_manifest_values(self, manifest, jsonSchema, dmge,
                 errorMsg = error.message[0:500]
                 errorVal = error.instance if len(error.path) > 0 else "Wrong schema"
 
-                val_errors, val_warnings =  GenerateError.generate_schema_error(row_num = errorRow, attribute_name = errorColName, error_msg = errorMsg, invalid_entry = errorVal, dmge = dmge)
+                val_errors, val_warnings = GenerateError.generate_schema_error(
+                    row_num=errorRow,
+                    attribute_name=errorColName,
+                    error_msg=errorMsg,
+                    invalid_entry=errorVal,
+                    dmge=dmge,
+                )
 
                 if val_errors:
                     errors.append(val_errors)
                 if val_warnings:
                     warnings.append(val_warnings)
-        logger.debug(f"JSON Schema validation elapsed time {perf_counter()-t_json_schema}")
+        logger.debug(
+            f"JSON Schema validation elapsed time {perf_counter()-t_json_schema}"
+        )
         return errors, warnings
 
 
-def validate_all(self, errors, warnings, manifest, manifestPath, dmge, jsonSchema, restrict_rules, project_scope: List, access_token: str):
+def validate_all(
+    self,
+    errors,
+    warnings,
+    manifest,
+    manifestPath,
+    dmge,
+    jsonSchema,
+    restrict_rules,
+    project_scope: List,
+    access_token: str,
+):
     vm = ValidateManifest(errors, manifest, manifestPath, dmge, jsonSchema)
-    manifest, vmr_errors, vmr_warnings = vm.validate_manifest_rules(manifest, dmge, restrict_rules, project_scope, access_token)
+    manifest, vmr_errors, vmr_warnings = vm.validate_manifest_rules(
+        manifest, dmge, restrict_rules, project_scope, access_token
+    )
     if vmr_errors:
         errors.extend(vmr_errors)
     if vmr_warnings:
diff --git a/schematic/schemas/commands.py b/schematic/schemas/commands.py
index 80700e2bf..f9660764c 100644
--- a/schematic/schemas/commands.py
+++ b/schematic/schemas/commands.py
@@ -41,13 +41,20 @@ def schema():  # use as `schematic model ...`
 @click.argument(
     "schema", type=click.Path(exists=True), metavar="<DATA_MODEL_CSV>", nargs=1
 )
+@click.option(
+    "--data_model_labels",
+    "-dml",
+    default="class_label",
+    type=click.Choice(["display_label", "class_label"], case_sensitive=True),
+    help=query_dict(schema_commands, ("schema", "convert", "data_model_labels")),
+)
 @click.option(
     "--output_jsonld",
     "-o",
     metavar="<OUTPUT_PATH>",
     help=query_dict(schema_commands, ("schema", "convert", "output_jsonld")),
 )
-def convert(schema, output_jsonld):
+def convert(schema, data_model_labels, output_jsonld):
     """
     Running CLI to convert data model specification in CSV format to
     data model in JSON-LD format.
@@ -67,7 +74,7 @@ def convert(schema, output_jsonld):
 
     # Convert parsed model to graph
     # Instantiate DataModelGraph
-    data_model_grapher = DataModelGraph(parsed_data_model)
+    data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
     # Generate graph
     logger.info("Generating data model graph.")
@@ -101,7 +108,7 @@ def convert(schema, output_jsonld):
 
     # output JSON-LD file alongside CSV file by default, get path.
     if output_jsonld is None:
-        if not '.jsonld' in schema:
+        if not ".jsonld" in schema:
             csv_no_ext = re.sub("[.]csv$", "", schema)
             output_jsonld = csv_no_ext + ".jsonld"
         else:
diff --git a/schematic/schemas/data_model_edges.py b/schematic/schemas/data_model_edges.py
index 7abbc26a8..225039866 100644
--- a/schematic/schemas/data_model_edges.py
+++ b/schematic/schemas/data_model_edges.py
@@ -14,7 +14,7 @@ def generate_edge(
         all_node_dict: dict,
         attr_rel_dict: dict,
         edge_relationships: dict,
-        edge_list:list,
+        edge_list: list,
     ) -> list[tuple[str, str, dict[str:str, str:int]]]:
         """Generate an edge between a target node and relevant other nodes the data model. In short, does this current node belong to a recorded relationship in the attribute, relationshps dictionary. Go through each attribute and relationship to find where the node may be.
         Args:
@@ -67,25 +67,31 @@ def generate_edge(
                         # Add edges, in a manner that preserves directionality
                         # TODO: rewrite to use edge_dir
                         if rel_key in ["subClassOf", "domainIncludes"]:
-                            edge_list.append((
-                                all_node_dict[node]["label"],
-                                all_node_dict[attribute_display_name]["label"],
-                                {'key':edge_key,
-                                'weight':weight,})
+                            edge_list.append(
+                                (
+                                    all_node_dict[node]["label"],
+                                    all_node_dict[attribute_display_name]["label"],
+                                    {
+                                        "key": edge_key,
+                                        "weight": weight,
+                                    },
                                 )
+                            )
                         else:
-                            edge_list.append((
-                                all_node_dict[attribute_display_name]["label"],
-                                all_node_dict[node]["label"],
-                                {'key':edge_key,
-                                'weight':weight},)
+                            edge_list.append(
+                                (
+                                    all_node_dict[attribute_display_name]["label"],
+                                    all_node_dict[node]["label"],
+                                    {"key": edge_key, "weight": weight},
                                 )
+                            )
                         # Add add rangeIncludes/valid value relationships in reverse as well, making the attribute the parent of the valid value.
                         if rel_key == "rangeIncludes":
-                            edge_list.append((
-                                all_node_dict[attribute_display_name]["label"],
-                                all_node_dict[node]["label"],
-                                {'key':"parentOf",
-                                'weight':weight},)
+                            edge_list.append(
+                                (
+                                    all_node_dict[attribute_display_name]["label"],
+                                    all_node_dict[node]["label"],
+                                    {"key": "parentOf", "weight": weight},
                                 )
+                            )
         return edge_list
diff --git a/schematic/schemas/data_model_graph.py b/schematic/schemas/data_model_graph.py
index 917d1eb71..72b1ebf56 100644
--- a/schematic/schemas/data_model_graph.py
+++ b/schematic/schemas/data_model_graph.py
@@ -12,6 +12,7 @@
 from schematic.utils.schema_utils import (
     get_property_label_from_display_name,
     get_class_label_from_display_name,
+    DisplayLabelType,
 )
 from schematic.utils.general import unlist
 from schematic.utils.viz_utils import visualize
@@ -43,20 +44,27 @@ class DataModelGraph:
 
     __metaclass__ = DataModelGraphMeta
 
-    def __init__(self, attribute_relationships_dict: dict) -> None:
+    def __init__(
+        self,
+        attribute_relationships_dict: dict,
+        data_model_labels: DisplayLabelType = "class_label",
+    ) -> None:
         """Load parsed data model.
         Args:
             attributes_relationship_dict, dict: generated in data_model_parser
                 {Attribute Display Name: {
                         Relationships: {
                                     CSV Header: Value}}}
-        Raises:
+            data_model_labels: str, display_label or class_label.
+                display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to schema_label.
+                class_label, default, use standard class or property label.         Raises:
             ValueError, attribute_relationship_dict not loaded.
         """
         self.attribute_relationships_dict = attribute_relationships_dict
         self.dmn = DataModelNodes(self.attribute_relationships_dict)
         self.dme = DataModelEdges()
         self.dmr = DataModelRelationships()
+        self.data_model_labels = data_model_labels
 
         if not self.attribute_relationships_dict:
             raise ValueError(
@@ -86,7 +94,9 @@ def generate_data_model_graph(self) -> nx.MultiDiGraph:
         for node in all_nodes:
             # Gather information for each node
             node_dict = self.dmn.generate_node_dict(
-                node, self.attribute_relationships_dict
+                node_display_name=node,
+                attr_rel_dict=self.attribute_relationships_dict,
+                data_model_labels=self.data_model_labels,
             )
 
             # Add each node to the all_node_dict to be used for generating edges
@@ -110,7 +120,7 @@ def generate_data_model_graph(self) -> nx.MultiDiGraph:
 
         # Add edges to the Graph
         for node_1, node_2, edge_dict in edge_list:
-            G.add_edge(node_1, node_2, key=edge_dict['key'], weight=edge_dict['weight'])
+            G.add_edge(node_1, node_2, key=edge_dict["key"], weight=edge_dict["weight"])
         return G
 
 
@@ -364,7 +374,7 @@ def get_ordered_entry(self, key: str, source_node_label: str) -> list[str]:
             )
 
         edge_key = self.rel_dict[key]["edge_key"]
-        
+
         # Handle out edges
         if self.rel_dict[key]["jsonld_direction"] == "out":
             # use outedges
diff --git a/schematic/schemas/data_model_jsonld.py b/schematic/schemas/data_model_jsonld.py
index fa9af86ef..6d4c2b48c 100644
--- a/schematic/schemas/data_model_jsonld.py
+++ b/schematic/schemas/data_model_jsonld.py
@@ -135,7 +135,7 @@ def get_edges_associated_with_node(
         return node_edges
 
     def get_edges_associated_with_property_nodes(
-        self, node:str
+        self, node: str
     ) -> List[tuple[str, str, dict[str, int]]]:
         """Get edges associated with property nodes to make sure we add that relationship.
         Args:
@@ -144,7 +144,7 @@ def get_edges_associated_with_property_nodes(
             node_edges, list: List of Tuples of edges associated with the given node, tuple contains the two nodes, plus the weight dict associated with the edge connection.
         """
         # Get edge keys for domainIncludes and subclassOf
-        domainIncludes_edge_key = self.rel_dict['domainIncludes']['edge_key']        
+        domainIncludes_edge_key = self.rel_dict["domainIncludes"]["edge_key"]
         node_edges = []
         # Get dict of edges for the current property node
         node_edges_dict = self.graph[node]
@@ -167,10 +167,11 @@ def add_edge_rels_to_template(self, template: dict, rel_vals: dict, node: str):
         # Get all edges associated with the current node
         node_edges = self.get_edges_associated_with_node(node=node)
 
-
         # For properties look for reverse relationships too
         if node in self.dmge.find_properties():
-            property_node_edges = self.get_edges_associated_with_property_nodes(node=node)
+            property_node_edges = self.get_edges_associated_with_property_nodes(
+                node=node
+            )
             node_edges.extend(property_node_edges)
 
         # Get node pairs and weights for each edge
@@ -188,8 +189,10 @@ def add_edge_rels_to_template(self, template: dict, rel_vals: dict, node: str):
                     # If the relationship defined and edge_key
                     if relationship == edge_key:
                         # TODO: rewrite to use edge_dir
-                        domainIncludes_edge_key = self.rel_dict['domainIncludes']['edge_key']
-                        subclassOf_edge_key = self.rel_dict['subClassOf']['edge_key']
+                        domainIncludes_edge_key = self.rel_dict["domainIncludes"][
+                            "edge_key"
+                        ]
+                        subclassOf_edge_key = self.rel_dict["subClassOf"]["edge_key"]
                         if edge_key in [subclassOf_edge_key]:
                             if node_2 == node:
                                 # Make sure the key is in the template (differs between properties and classes)
@@ -303,6 +306,7 @@ def fill_entry_template(self, template: dict, node: str) -> dict:
         template = self.reorder_template_entries(
             template=template,
         )
+
         # Add contexts to certain values
         template = self.add_contexts_to_entries(
             template=template,
@@ -414,7 +418,9 @@ def reorder_template_entries(self, template: dict) -> dict:
                     key=key, source_node_label=template_label
                 )
                 if not len(entry) == len(sorted_edges):
-                    logger.error("There is an error with sorting values in the JSONLD, please issue a bug report.")
+                    logger.error(
+                        "There is an error with sorting values in the JSONLD, please issue a bug report."
+                    )
 
                 edge_weights_dict = {edge: i for i, edge in enumerate(sorted_edges)}
                 ordered_edges = [0] * len(edge_weights_dict.keys())
diff --git a/schematic/schemas/data_model_nodes.py b/schematic/schemas/data_model_nodes.py
index e82369789..2535e3f20 100644
--- a/schematic/schemas/data_model_nodes.py
+++ b/schematic/schemas/data_model_nodes.py
@@ -1,7 +1,7 @@
 from inspect import isfunction
 import networkx as nx
 from rdflib import Namespace
-from typing import Any, Dict, Optional, Text, List, Callable
+from typing import Any, Dict, Optional, Text, List, Literal, Callable
 
 from schematic.schemas.data_model_parser import DataModelJSONLDParser
 from schematic.schemas.data_model_relationships import DataModelRelationships
@@ -11,6 +11,7 @@
     get_attribute_display_name_from_label,
     convert_bool_to_str,
     parse_validation_rules,
+    DisplayLabelType,
 )
 from schematic.utils.validate_rules_utils import validate_schema_rules
 from schematic.schemas.curie import uri2curie, curie2uri
@@ -130,6 +131,7 @@ def run_rel_functions(
         attr_relationships={},
         csv_header="",
         entry_type="",
+        data_model_labels: DisplayLabelType = "class_label",
     ):
         """This function exists to centralzie handling of functions for filling out node information, makes sure all the proper parameters are passed to each function.
         Args:
@@ -157,7 +159,9 @@ def run_rel_functions(
 
         elif rel_func == get_label_from_display_name:
             return get_label_from_display_name(
-                display_name=node_display_name, entry_type=entry_type
+                display_name=node_display_name,
+                entry_type=entry_type,
+                data_model_labels=data_model_labels,
             )
 
         elif rel_func == convert_bool_to_str:
@@ -176,7 +180,12 @@ def run_rel_functions(
                 f"The function provided ({rel_func}) to define the relationship {key} is not captured in the function run_rel_functions, please update."
             )
 
-    def generate_node_dict(self, node_display_name: str, attr_rel_dict: dict) -> dict:
+    def generate_node_dict(
+        self,
+        node_display_name: str,
+        attr_rel_dict: dict,
+        data_model_labels: DisplayLabelType = "class_label",
+    ) -> dict:
         """Gather information to be attached to each node.
         Args:
             node_display_name, str: display name for current node
@@ -184,7 +193,9 @@ def generate_node_dict(self, node_display_name: str, attr_rel_dict: dict) -> dic
                 {Attribute Display Name: {
                         Relationships: {
                                     CSV Header: Value}}}
-
+            data_model_labels: str, display_label or class_label.
+                display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to schema_label.
+                class_label, default, use standard class or property label.
         Returns:
             node_dict, dict: dictionary of relationship information about the current node
                 {'displayName': '', 'label': '', 'comment': 'TBD', 'required': None, 'validationRules': [], 'isPartOf': '', 'uri': ''}
@@ -228,6 +239,7 @@ def generate_node_dict(self, node_display_name: str, attr_rel_dict: dict) -> dic
                                 attr_relationships=attr_relationships,
                                 csv_header=csv_header,
                                 entry_type=entry_type,
+                                data_model_labels=data_model_labels,
                             )
                         }
                     )
@@ -249,6 +261,7 @@ def generate_node_dict(self, node_display_name: str, attr_rel_dict: dict) -> dic
                                 attr_relationships=attr_relationships,
                                 csv_header=csv_header,
                                 entry_type=entry_type,
+                                data_model_labels=data_model_labels,
                             )
                         }
                     )
diff --git a/schematic/schemas/data_model_parser.py b/schematic/schemas/data_model_parser.py
index a541eb3ed..c5dbacb3e 100644
--- a/schematic/schemas/data_model_parser.py
+++ b/schematic/schemas/data_model_parser.py
@@ -1,6 +1,7 @@
 import logging
 import pandas as pd
 import pathlib
+
 from typing import Any, Dict, Optional, Text, List, Union
 
 from schematic.utils.df_utils import load_df
@@ -243,7 +244,13 @@ def __init__(
         # Load relationships dictionary.
         self.rel_dict = self.dmr.define_data_model_relationships()
 
-    def parse_entry(self, rel_entry: any, id_jsonld_key: str, dn_label_dict:dict[str:str], model_jsonld:dict) -> Any:
+    def parse_entry(
+        self,
+        rel_entry: any,
+        id_jsonld_key: str,
+        dn_label_dict: dict[str:str],
+        model_jsonld: dict,
+    ) -> Any:
         """Parse an input entry based on certain attributes
         Args:
             rel_entry: Given a single entry and relationship in a JSONLD data model, the recorded value
@@ -256,7 +263,9 @@ def parse_entry(self, rel_entry: any, id_jsonld_key: str, dn_label_dict:dict[str
             parsed_rel_entry = rel_entry["@id"]
         # Parse list of dictionaries to make a list of entries with context stripped (will update this section when contexts added.)
         elif type(rel_entry) == list and type(rel_entry[0]) == dict:
-            parsed_rel_entry = self.convert_entry_to_dn_label([r[id_jsonld_key].split(":")[1] for r in rel_entry], model_jsonld)
+            parsed_rel_entry = self.convert_entry_to_dn_label(
+                [r[id_jsonld_key].split(":")[1] for r in rel_entry], model_jsonld
+            )
         # Strip context from string and convert true/false to bool
         elif type(rel_entry) == str:
             # Remove contexts and treat strings as appropriate.
@@ -268,16 +277,18 @@ def parse_entry(self, rel_entry: any, id_jsonld_key: str, dn_label_dict:dict[str
                 elif parsed_rel_entry.lower == "false":
                     parsed_rel_entry = False
             else:
-                parsed_rel_entry=self.convert_entry_to_dn_label(rel_entry, model_jsonld)
+                parsed_rel_entry = self.convert_entry_to_dn_label(
+                    rel_entry, model_jsonld
+                )
 
         # For anything else get that
         else:
-            parsed_rel_entry=self.convert_entry_to_dn_label(rel_entry, model_jsonld)
+            parsed_rel_entry = self.convert_entry_to_dn_label(rel_entry, model_jsonld)
 
         return parsed_rel_entry
 
     def label_to_dn_dict(self, model_jsonld: list[dict]):
-        """ Generate a dictionary of labels to display name, so can easily look up display names using the label.
+        """Generate a dictionary of labels to display name, so can easily look up display names using the label.
         Args:
             model_jsonld: list of dictionaries, each dictionary is an entry in the jsonld data model
         Returns:
@@ -289,10 +300,12 @@ def label_to_dn_dict(self, model_jsonld: list[dict]):
         ]
         dn_label_dict = {}
         for entry in model_jsonld:
-            dn_label_dict[entry[label_jsonld_key]]=entry[dn_jsonld_key]
+            dn_label_dict[entry[label_jsonld_key]] = entry[dn_jsonld_key]
         return dn_label_dict
 
-    def convert_entry_to_dn_label(self, parsed_rel_entry:Union[str,list], model_jsonld:list[dict]) -> Union[str,list]:
+    def convert_entry_to_dn_label(
+        self, parsed_rel_entry: Union[str, list], model_jsonld: list[dict]
+    ) -> Union[str, list]:
         """Convert a parsed entry to display name, taking into account the entry type
         Args:
             parsed_rel_entry: an entry that has been parsed base on its input type and characteristics.
@@ -304,7 +317,10 @@ def convert_entry_to_dn_label(self, parsed_rel_entry:Union[str,list], model_json
         dn_label_dict = self.label_to_dn_dict(model_jsonld=model_jsonld)
         # Handle if using the display name as the label
         if type(parsed_rel_entry) == list:
-            parsed_rel_entry = [dn_label_dict.get(entry) if dn_label_dict.get(entry) else entry for entry in parsed_rel_entry ]
+            parsed_rel_entry = [
+                dn_label_dict.get(entry) if dn_label_dict.get(entry) else entry
+                for entry in parsed_rel_entry
+            ]
         elif type(parsed_rel_entry) == str:
             converted_label = dn_label_dict.get(parsed_rel_entry)
             if converted_label:
@@ -362,26 +378,26 @@ def gather_jsonld_attributes_relationships(self, model_jsonld: List[dict]) -> Di
             for rel_key, rel_vals in self.rel_dict.items():
                 # Determine if current entry in the for loop, can be described by the current relationship that is being cycled through.
                 # used to also check "csv_header" in rel_vals.keys() which allows all JSONLD values through even if it does not have a CSV counterpart, will allow other values thorough in the else statement now
-                if (
-                    rel_vals["jsonld_key"] in entry.keys()
-                    and rel_vals["csv_header"]
-                ):
+                if rel_vals["jsonld_key"] in entry.keys() and rel_vals["csv_header"]:
                     # Retrieve entry value associated with the given relationship
                     rel_entry = entry[rel_vals["jsonld_key"]]
                     # If there is an entry parse it by type and add to the attr:relationships dictionary.
                     if rel_entry:
                         parsed_rel_entry = self.parse_entry(
-                            rel_entry=rel_entry, id_jsonld_key=id_jsonld_key, dn_label_dict=dn_label_dict, model_jsonld=model_jsonld,
+                            rel_entry=rel_entry,
+                            id_jsonld_key=id_jsonld_key,
+                            dn_label_dict=dn_label_dict,
+                            model_jsonld=model_jsonld,
                         )
                         rel_csv_header = self.rel_dict[rel_key]["csv_header"]
-                        if rel_key == 'domainIncludes':
+                        if rel_key == "domainIncludes":
                             # In the JSONLD the domain includes field contains the ids of attributes that the current attribute is the property/parent of.
                             # Because of this we need to handle these values differently.
                             # We will get the values in the field (parsed_val), then add the current attribute as to the property key in the attr_rel_dictionary[p_attr_key].
                             for parsed_val in parsed_rel_entry:
                                 attr_in_dict = False
-                                #Get propert/parent key (displayName)
-                                p_attr_key=''
+                                # Get propert/parent key (displayName)
+                                p_attr_key = ""
                                 # Check if the parsed value is already a part of the attr_rel_dictionary
                                 for attr_dn, rels in attr_rel_dictionary.items():
                                     if parsed_val == attr_dn:
@@ -389,23 +405,42 @@ def gather_jsonld_attributes_relationships(self, model_jsonld: List[dict]) -> Di
                                         attr_in_dict = True
                                 # If it is part of the dictionary update add current attribute as a property of the parsed value
                                 if attr_in_dict == True:
-                                    if not rel_csv_header in attr_rel_dictionary[p_attr_key]["Relationships"]:
-                                        attr_rel_dictionary[p_attr_key]["Relationships"].update({rel_csv_header:[entry[dn_jsonld_key]]})
+                                    if (
+                                        not rel_csv_header
+                                        in attr_rel_dictionary[p_attr_key][
+                                            "Relationships"
+                                        ]
+                                    ):
+                                        attr_rel_dictionary[p_attr_key][
+                                            "Relationships"
+                                        ].update(
+                                            {rel_csv_header: [entry[dn_jsonld_key]]}
+                                        )
                                     else:
-                                        attr_rel_dictionary[p_attr_key]["Relationships"].update({rel_csv_header:[entry[dn_jsonld_key]]})
+                                        attr_rel_dictionary[p_attr_key][
+                                            "Relationships"
+                                        ][rel_csv_header].extend([entry[dn_jsonld_key]])
                                 # If the parsed_val is not already recorded in the dictionary, add it
                                 elif attr_in_dict == False:
                                     # Get the display name for the parsed value
-                                    p_attr_key = self.convert_entry_to_dn_label(parsed_val, model_jsonld)
-                                    
-                                    attr_rel_dictionary.update(attr_dict_template(p_attr_key))
-                                    attr_rel_dictionary[p_attr_key]["Relationships"].update({rel_csv_header:[entry[label_jsonld_key]]})
-                        
+                                    p_attr_key = self.convert_entry_to_dn_label(
+                                        parsed_val, model_jsonld
+                                    )
+
+                                    attr_rel_dictionary.update(
+                                        attr_dict_template(p_attr_key)
+                                    )
+                                    attr_rel_dictionary[p_attr_key][
+                                        "Relationships"
+                                    ].update(
+                                        {rel_csv_header: [entry[label_jsonld_key]]}
+                                    )
+
                         else:
                             attr_rel_dictionary[attr_key]["Relationships"].update(
                                 {rel_csv_header: parsed_rel_entry}
                             )
-                        
+
                 elif (
                     rel_vals["jsonld_key"] in entry.keys()
                     and not rel_vals["csv_header"]
@@ -415,7 +450,10 @@ def gather_jsonld_attributes_relationships(self, model_jsonld: List[dict]) -> Di
                     # If there is an entry parset it by type and add to the attr:relationships dictionary.
                     if rel_entry:
                         parsed_rel_entry = self.parse_entry(
-                            rel_entry=rel_entry, id_jsonld_key=id_jsonld_key, dn_label_dict=dn_label_dict, model_jsonld=model_jsonld,
+                            rel_entry=rel_entry,
+                            id_jsonld_key=id_jsonld_key,
+                            dn_label_dict=dn_label_dict,
+                            model_jsonld=model_jsonld,
                         )
                         # Add relationships for each attribute and relationship to the dictionary
                         attr_rel_dictionary[attr_key]["Relationships"].update(
diff --git a/schematic/schemas/data_model_validator.py b/schematic/schemas/data_model_validator.py
index e3d626882..f0939999b 100644
--- a/schematic/schemas/data_model_validator.py
+++ b/schematic/schemas/data_model_validator.py
@@ -5,8 +5,10 @@
 from typing import Any, Dict, Optional, Text, List, Tuple
 
 from schematic.schemas.data_model_relationships import DataModelRelationships
+
 logger = logging.getLogger(__name__)
 
+
 class DataModelValidator:
     """
     Check for consistency within data model.
@@ -87,7 +89,9 @@ def check_is_dag(self) -> List[str]:
         """
         error = []
         if not nx.is_directed_acyclic_graph(self.graph):
-            cycles = multiprocessing.Process(target=self.run_cycles, name="Get Cycles", args=(self.graph,))
+            cycles = multiprocessing.Process(
+                target=self.run_cycles, name="Get Cycles", args=(self.graph,)
+            )
             cycles.start()
 
             # Give up to 5 seconds to find cycles, if not exit and issue standard error
@@ -102,7 +106,7 @@ def check_is_dag(self) -> List[str]:
 
             error.append(
                 f"Schematic requires models be a directed acyclic graph (DAG). Please inspect your model."
-                )
+            )
 
         return error
 
diff --git a/schematic/store/synapse.py b/schematic/store/synapse.py
index c291b742e..1239ae52a 100644
--- a/schematic/store/synapse.py
+++ b/schematic/store/synapse.py
@@ -14,8 +14,15 @@
 import synapseclient
 import uuid  # used to generate unique names for entities
 
-from tenacity import retry, stop_after_attempt, wait_chain, wait_fixed, retry_if_exception_type
+from tenacity import (
+    retry,
+    stop_after_attempt,
+    wait_chain,
+    wait_fixed,
+    retry_if_exception_type,
+)
 from time import sleep
+
 # allows specifying explicit variable types
 from typing import Dict, List, Tuple, Sequence, Union, Optional
 
@@ -34,7 +41,11 @@
 from synapseclient.entity import File
 from synapseclient.table import CsvFileTable, build_table, Schema
 from synapseclient.annotations import from_synapse_annotations
-from synapseclient.core.exceptions import SynapseHTTPError, SynapseAuthenticationError, SynapseUnmetAccessRestrictions
+from synapseclient.core.exceptions import (
+    SynapseHTTPError,
+    SynapseAuthenticationError,
+    SynapseUnmetAccessRestrictions,
+)
 import synapseutils
 from synapseutils.copy_functions import changeFileMetaData
 
@@ -46,16 +57,20 @@
 
 from schematic.utils.df_utils import update_df, load_df, col_in_dataframe
 from schematic.utils.validate_utils import comma_separated_list_regex, rule_in_rule_list
+
 # entity_type_mapping, get_dir_size, create_temp_folder, check_synapse_cache_size, and clear_synapse_cache functions are used for AWS deployment
 # Please do not remove these import statements
-from schematic.utils.general import (entity_type_mapping,
-                                     get_dir_size,
-                                     convert_gb_to_bytes,
-                                     create_temp_folder,
-                                     check_synapse_cache_size,
-                                     clear_synapse_cache,
-                                     profile,
-                                     calculate_datetime)
+from schematic.utils.general import (
+    entity_type_mapping,
+    get_dir_size,
+    convert_gb_to_bytes,
+    create_temp_folder,
+    check_synapse_cache_size,
+    clear_synapse_cache,
+    profile,
+    calculate_datetime,
+)
+
 from schematic.utils.schema_utils import get_class_label_from_display_name
 
 from schematic.store.base import BaseStorage
@@ -64,12 +79,14 @@
 
 logger = logging.getLogger("Synapse storage")
 
+
 @dataclass
 class ManifestDownload(object):
     """
     syn: an object of type synapseclient.
-    manifest_id: id of a manifest  
+    manifest_id: id of a manifest
     """
+
     syn: synapseclient.Synapse
     manifest_id: str
 
@@ -91,33 +108,37 @@ def _download_manifest_to_folder(self) -> File:
             # create temporary folders for storing manifests
             download_location = create_temp_folder(temporary_manifest_storage)
         else:
-            download_location=CONFIG.manifest_folder
+            download_location = CONFIG.manifest_folder
         manifest_data = self.syn.get(
-                self.manifest_id,
-                downloadLocation=download_location,
-                ifcollision="overwrite.local",
-            )
+            self.manifest_id,
+            downloadLocation=download_location,
+            ifcollision="overwrite.local",
+        )
         return manifest_data
 
     def _entity_type_checking(self) -> str:
         """
         check the entity type of the id that needs to be downloaded
-        Return: 
+        Return:
              if the entity type is wrong, raise an error
         """
         # check the type of entity
         entity_type = entity_type_mapping(self.syn, self.manifest_id)
-        if entity_type  != "file":
-            logger.error(f'You are using entity type: {entity_type}. Please provide a file ID')
+        if entity_type != "file":
+            logger.error(
+                f"You are using entity type: {entity_type}. Please provide a file ID"
+            )
 
     @staticmethod
-    def download_manifest(self, newManifestName: str="", manifest_df: pd.DataFrame=pd.DataFrame()) -> Union[str,File]:
+    def download_manifest(
+        self, newManifestName: str = "", manifest_df: pd.DataFrame = pd.DataFrame()
+    ) -> Union[str, File]:
         """
-        Download a manifest based on a given manifest id. 
+        Download a manifest based on a given manifest id.
         Args:
             newManifestName(optional): new name of a manifest that gets downloaded.
             manifest_df(optional): a dataframe containing name and id of manifests in a given asset view
-        Return: 
+        Return:
             manifest_data: synapse entity file object
         """
 
@@ -131,36 +152,44 @@ def download_manifest(self, newManifestName: str="", manifest_df: pd.DataFrame=p
         # download a manifest
         try:
             manifest_data = self._download_manifest_to_folder()
-        except(SynapseUnmetAccessRestrictions, SynapseAuthenticationError):
+        except (SynapseUnmetAccessRestrictions, SynapseAuthenticationError):
             # if there's an error getting an uncensored manifest, try getting the censored manifest
             if not manifest_df.empty:
-                censored_regex=re.compile('.*censored.*')
-                censored = manifest_df['name'].str.contains(censored_regex)
-                new_manifest_id=manifest_df[censored]["id"][0]
+                censored_regex = re.compile(".*censored.*")
+                censored = manifest_df["name"].str.contains(censored_regex)
+                new_manifest_id = manifest_df[censored]["id"][0]
                 self.manifest_id = new_manifest_id
-                try: 
+                try:
                     manifest_data = self._download_manifest_to_folder()
-                except (SynapseUnmetAccessRestrictions, SynapseAuthenticationError) as e:
-                    raise PermissionError("You don't have access to censored and uncensored manifests in this dataset.") from e
+                except (
+                    SynapseUnmetAccessRestrictions,
+                    SynapseAuthenticationError,
+                ) as e:
+                    raise PermissionError(
+                        "You don't have access to censored and uncensored manifests in this dataset."
+                    ) from e
             else:
-                logger.error(f"You don't have access to the requested resource: {self.manifest_id}")
+                logger.error(
+                    f"You don't have access to the requested resource: {self.manifest_id}"
+                )
 
-        if newManifestName and os.path.exists(manifest_data.get('path')):
+        if newManifestName and os.path.exists(manifest_data.get("path")):
             # Rename the file we just made to the new name
-            new_manifest_filename = newManifestName + '.csv'
+            new_manifest_filename = newManifestName + ".csv"
 
             # get location of existing manifest. The manifest that will be renamed should live in the same folder as existing manifest.
-            parent_folder = os.path.dirname(manifest_data.get('path'))
+            parent_folder = os.path.dirname(manifest_data.get("path"))
 
             new_manifest_path_name = os.path.join(parent_folder, new_manifest_filename)
-            os.rename(manifest_data['path'], new_manifest_path_name)
+            os.rename(manifest_data["path"], new_manifest_path_name)
 
             # Update file names/paths in manifest_data
-            manifest_data['name'] = new_manifest_filename
-            manifest_data['filename'] = new_manifest_filename
-            manifest_data['path'] = new_manifest_path_name
+            manifest_data["name"] = new_manifest_filename
+            manifest_data["filename"] = new_manifest_filename
+            manifest_data["path"] = new_manifest_path_name
         return manifest_data
 
+
 class SynapseStorage(BaseStorage):
     """Implementation of Storage interface for datasets/files stored on Synapse.
     Provides utilities to list files in a specific project; update files annotations, create fileviews, etc.
@@ -198,24 +227,28 @@ def __init__(
 
     def _purge_synapse_cache(self, maximum_storage_allowed_cache_gb=1):
         """
-        Purge synapse cache if it exceeds a certain size. Default to 1GB. 
+        Purge synapse cache if it exceeds a certain size. Default to 1GB.
         Args:
-            maximum_storage_allowed_cache_gb: the maximum storage allowed before purging cache. Default is 1 GB. 
+            maximum_storage_allowed_cache_gb: the maximum storage allowed before purging cache. Default is 1 GB.
         """
         # try clearing the cache
         # scan a directory and check size of files
         if os.path.exists(self.root_synapse_cache):
-            maximum_storage_allowed_cache_bytes = convert_gb_to_bytes(maximum_storage_allowed_cache_gb)
+            maximum_storage_allowed_cache_bytes = convert_gb_to_bytes(
+                maximum_storage_allowed_cache_gb
+            )
             nbytes = get_dir_size(self.root_synapse_cache)
             dir_size_bytes = check_synapse_cache_size(directory=self.root_synapse_cache)
             # if 1 GB has already been taken, purge cache before 15 min
             if dir_size_bytes >= maximum_storage_allowed_cache_bytes:
                 num_of_deleted_files = clear_synapse_cache(self.syn.cache, minutes=15)
-                logger.info(f'{num_of_deleted_files}  files have been deleted from {self.root_synapse_cache}')
+                logger.info(
+                    f"{num_of_deleted_files}  files have been deleted from {self.root_synapse_cache}"
+                )
             else:
                 # on AWS, OS takes around 14-17% of our ephemeral storage (20GiB)
                 # instead of guessing how much space that we left, print out .synapseCache here
-                logger.info(f'the total size of .synapseCache is: {nbytes} bytes')
+                logger.info(f"the total size of .synapseCache is: {nbytes} bytes")
 
     def _query_fileview(self):
         self._purge_synapse_cache()
@@ -225,14 +258,14 @@ def _query_fileview(self):
             if self.project_scope:
                 self.storageFileviewTable = self.syn.tableQuery(
                     f"SELECT * FROM {self.storageFileview} WHERE projectId IN {tuple(self.project_scope + [''])}"
-                    ).asDataFrame()
+                ).asDataFrame()
             else:
                 # get data in administrative fileview for this pipeline
                 self.storageFileviewTable = self.syn.tableQuery(
                     "SELECT * FROM " + self.storageFileview
                 ).asDataFrame()
         except SynapseHTTPError:
-            raise AccessCredentialsError(self.storageFileview)    
+            raise AccessCredentialsError(self.storageFileview)
 
     @staticmethod
     def login(token=None, access_token=None):
@@ -253,7 +286,9 @@ def login(token=None, access_token=None):
                 syn = synapseclient.Synapse()
                 syn.default_headers["Authorization"] = f"Bearer {access_token}"
             except synapseclient.core.exceptions.SynapseHTTPError:
-                raise ValueError("No access to resources. Please make sure that your token is correct")
+                raise ValueError(
+                    "No access to resources. Please make sure that your token is correct"
+                )
         else:
             # login using synapse credentials provided by user in .synapseConfig (default) file
             syn = synapseclient.Synapse(configPath=CONFIG.synapse_configuration_path)
@@ -264,18 +299,18 @@ def missing_entity_handler(method):
         def wrapper(*args, **kwargs):
             try:
                 return method(*args, **kwargs)
-            except(SynapseHTTPError) as ex:
-                str_message = str(ex).replace("\n","")
-                if 'trash' in str_message or 'does not exist' in str_message:
+            except SynapseHTTPError as ex:
+                str_message = str(ex).replace("\n", "")
+                if "trash" in str_message or "does not exist" in str_message:
                     logging.warning(str_message)
                     return None
                 else:
                     raise ex
+
         return wrapper
 
     def getStorageFileviewTable(self):
-        """ Returns the storageFileviewTable obtained during initialization.
-        """
+        """Returns the storageFileviewTable obtained during initialization."""
         return self.storageFileviewTable
 
     def getPaginatedRestResults(self, currentUserId: str) -> Dict[str, str]:
@@ -337,7 +372,7 @@ def getStorageProjects(self, project_scope: List = None) -> list[tuple[str, str]
 
         # find set of user projects that are also in this pipeline's storage projects set
         storageProjects = list(set(storageProjects) & set(currentUserProjects))
-        
+
         # Limit projects to scope if specified
         if project_scope:
             storageProjects = list(set(storageProjects) & set(project_scope))
@@ -346,7 +381,7 @@ def getStorageProjects(self, project_scope: List = None) -> list[tuple[str, str]
                 raise Warning(
                     f"There are no projects that the user has access to that match the criteria of the specified project scope: {project_scope}"
                 )
-        
+
         # prepare a return list of project IDs and names
         projects = []
         for projectId in storageProjects:
@@ -418,22 +453,20 @@ def getFilesInStorageDataset(
         Raises:
             ValueError: Dataset ID not found.
         """
-
         # select all files within a given storage dataset folder (top level folder in a Synapse storage project or folder marked with contentType = 'dataset')
-        walked_path = synapseutils.walk(self.syn, datasetId, includeTypes=["folder", "file"])
+        walked_path = synapseutils.walk(
+            self.syn, datasetId, includeTypes=["folder", "file"]
+        )
 
         file_list = []
 
         # iterate over all results
         for dirpath, dirname, filenames in walked_path:
-
             # iterate over all files in a folder
             for filename in filenames:
-
                 if (not "manifest" in filename[0] and not fileNames) or (
                     fileNames and filename[0] in fileNames
                 ):
-
                     # don't add manifest to list of files unless it is specified in the list of specified fileNames; return all found files
                     # except the manifest if no fileNames have been specified
                     # TODO: refactor for clarity/maintainability
@@ -448,39 +481,42 @@ def getFilesInStorageDataset(
         return file_list
 
     def _get_manifest_id(self, manifest: pd.DataFrame) -> str:
-        """If both censored and uncensored manifests are present, return uncensored manifest; if only one manifest is present, return manifest id of that manifest; if more than two manifests are present, return the manifest id of the first one. 
+        """If both censored and uncensored manifests are present, return uncensored manifest; if only one manifest is present, return manifest id of that manifest; if more than two manifests are present, return the manifest id of the first one.
         Args:
         manifest: a dataframe contains name and id of manifests in a given asset view
 
-        Return: 
+        Return:
         manifest_syn_id: id of a given censored or uncensored manifest
-        """ 
-        censored_regex=re.compile('.*censored.*')
-        censored = manifest['name'].str.contains(censored_regex)
+        """
+        censored_regex = re.compile(".*censored.*")
+        censored = manifest["name"].str.contains(censored_regex)
         if any(censored):
             # Try to use uncensored manifest first
-            not_censored=~censored
+            not_censored = ~censored
             if any(not_censored):
-                manifest_syn_id=manifest[not_censored]["id"][0]
+                manifest_syn_id = manifest[not_censored]["id"].iloc[0]
             # if only censored manifests are available, just use the first censored manifest
-            else: 
-                manifest_syn_id = manifest["id"][0]
+            else:
+                manifest_syn_id = manifest["id"].iloc[0]
 
-        #otherwise, use the first (implied only) version that exists
+        # otherwise, use the first (implied only) version that exists
         else:
-            manifest_syn_id = manifest["id"][0]
-        
+            manifest_syn_id = manifest["id"].iloc[0]
+
         return manifest_syn_id
 
     def getDatasetManifest(
-        self, datasetId: str, downloadFile: bool = False, newManifestName: str='',
+        self,
+        datasetId: str,
+        downloadFile: bool = False,
+        newManifestName: str = "",
     ) -> Union[str, File]:
         """Gets the manifest associated with a given dataset.
 
         Args:
             datasetId: synapse ID of a storage dataset.
             downloadFile: boolean argument indicating if manifest file in dataset should be downloaded or not.
-            newManifestName: new name of a manifest that gets downloaded 
+            newManifestName: new name of a manifest that gets downloaded
 
         Returns:
             manifest_syn_id (String): Synapse ID of exisiting manifest file.
@@ -492,104 +528,121 @@ def getDatasetManifest(
         # get a list of files containing the manifest for this dataset (if any)
         all_files = self.storageFileviewTable
 
-        # construct regex based on manifest basename in the config 
-        manifest_re=re.compile(os.path.basename(self.manifest)+".*.[tc]sv")
+        # construct regex based on manifest basename in the config
+        manifest_re = re.compile(os.path.basename(self.manifest) + ".*.[tc]sv")
 
         # search manifest based on given manifest basename regex above
         # and return a dataframe containing name and id of manifests in a given asset view
         manifest = all_files[
-            (all_files['name'].str.contains(manifest_re,regex=True))
+            (all_files["name"].str.contains(manifest_re, regex=True))
             & (all_files["parentId"] == datasetId)
         ]
 
         manifest = manifest[["id", "name"]]
-        
+
         # if there is no pre-exisiting manifest in the specified dataset
         if manifest.empty:
-            logger.warning(f"Could not find a manifest that fits basename {self.manifest} in asset view and dataset {datasetId}")
+            logger.warning(
+                f"Could not find a manifest that fits basename {self.manifest} in asset view and dataset {datasetId}"
+            )
             return ""
 
         # if there is an exisiting manifest
         else:
             manifest_syn_id = self._get_manifest_id(manifest)
-            if downloadFile: 
+            if downloadFile:
                 md = ManifestDownload(self.syn, manifest_id=manifest_syn_id)
-                manifest_data = ManifestDownload.download_manifest(md, newManifestName=newManifestName, manifest_df=manifest)
-                ## TO DO: revisit how downstream code handle manifest_data. If the downstream code would break when manifest_data is an empty string, 
-                ## then we should catch the error here without returning an empty string. 
+                manifest_data = ManifestDownload.download_manifest(
+                    md, newManifestName=newManifestName, manifest_df=manifest
+                )
+                ## TO DO: revisit how downstream code handle manifest_data. If the downstream code would break when manifest_data is an empty string,
+                ## then we should catch the error here without returning an empty string.
                 if not manifest_data:
-                    logger.debug(f"No manifest data returned. Please check if you have successfully downloaded manifest: {manifest_syn_id}")
+                    logger.debug(
+                        f"No manifest data returned. Please check if you have successfully downloaded manifest: {manifest_syn_id}"
+                    )
                 return manifest_data
             return manifest_syn_id
 
-    def getDataTypeFromManifest(self, manifestId:str):
+    def getDataTypeFromManifest(self, manifestId: str):
         """Fetch a manifest and return data types of all columns
-        Args: 
+        Args:
             manifestId: synapse ID of a manifest
         """
-        # get manifest file path 
+        # get manifest file path
         manifest_filepath = self.syn.get(manifestId).path
 
-        # load manifest dataframe 
-        manifest = load_df(manifest_filepath, preserve_raw_input=False, data_model=False)
+        # load manifest dataframe
+        manifest = load_df(
+            manifest_filepath, preserve_raw_input=False, data_model=False
+        )
 
         # convert the dataFrame to use best possible dtypes.
         manifest_new = manifest.convert_dtypes()
 
         # get data types of columns
-        result = manifest_new.dtypes.to_frame('dtypes').reset_index()
-
-        # return the result as a dictionary 
-        result_dict = result.set_index('index')['dtypes'].astype(str).to_dict()
+        result = manifest_new.dtypes.to_frame("dtypes").reset_index()
 
+        # return the result as a dictionary
+        result_dict = result.set_index("index")["dtypes"].astype(str).to_dict()
 
         return result_dict
 
-    def _get_files_metadata_from_dataset(self, datasetId: str, only_new_files: bool, manifest:pd.DataFrame=None) -> Optional[dict]:
+    def _get_files_metadata_from_dataset(
+        self, datasetId: str, only_new_files: bool, manifest: pd.DataFrame = None
+    ) -> Optional[dict]:
         """retrieve file ids under a particular datasetId
 
         Args:
-            datasetId (str): a dataset id 
-            only_new_files (bool): if only adding new files that are not already exist 
-            manifest (pd.DataFrame): metadata manifest dataframe. Default to None. 
+            datasetId (str): a dataset id
+            only_new_files (bool): if only adding new files that are not already exist
+            manifest (pd.DataFrame): metadata manifest dataframe. Default to None.
 
         Returns:
             a dictionary that contains filename and entityid under a given datasetId or None if there is nothing under a given dataset id are not available
         """
         dataset_files = self.getFilesInStorageDataset(datasetId)
         if dataset_files:
-            dataset_file_names_id_dict = self._get_file_entityIds(dataset_files, only_new_files=only_new_files, manifest=manifest)
+            dataset_file_names_id_dict = self._get_file_entityIds(
+                dataset_files, only_new_files=only_new_files, manifest=manifest
+            )
             return dataset_file_names_id_dict
         else:
             return None
 
-    def add_entity_id_and_filename(self,  datasetId: str, manifest: pd.DataFrame) -> pd.DataFrame:
+    def add_entity_id_and_filename(
+        self, datasetId: str, manifest: pd.DataFrame
+    ) -> pd.DataFrame:
         """add entityid and filename column to an existing manifest assuming entityId column is not already present
 
         Args:
             datasetId (str): dataset syn id
-            manifest (pd.DataFrame): existing manifest dataframe, assuming this dataframe does not have an entityId column and Filename column is present but completely empty 
+            manifest (pd.DataFrame): existing manifest dataframe, assuming this dataframe does not have an entityId column and Filename column is present but completely empty
 
         Returns:
-            pd.DataFrame: returns a pandas dataframe 
+            pd.DataFrame: returns a pandas dataframe
         """
-        # get file names and entity ids of a given dataset 
-        dataset_files_dict = self._get_files_metadata_from_dataset(datasetId, only_new_files=False)
+        # get file names and entity ids of a given dataset
+        dataset_files_dict = self._get_files_metadata_from_dataset(
+            datasetId, only_new_files=False
+        )
 
-        if dataset_files_dict: 
-            # turn manifest dataframe back to a dictionary for operation 
-            manifest_dict = manifest.to_dict('list')
+        if dataset_files_dict:
+            # turn manifest dataframe back to a dictionary for operation
+            manifest_dict = manifest.to_dict("list")
 
             # update Filename column
             # add entityId column to the end
             manifest_dict.update(dataset_files_dict)
-            
-            # if the component column exists in existing manifest, fill up that column 
+
+            # if the component column exists in existing manifest, fill up that column
             if "Component" in manifest_dict.keys():
-                manifest_dict["Component"] = manifest_dict["Component"] * max(1, len(manifest_dict["Filename"]))
-            
+                manifest_dict["Component"] = manifest_dict["Component"] * max(
+                    1, len(manifest_dict["Filename"])
+                )
+
             # turn dictionary back to a dataframe
-            manifest_df_index = pd.DataFrame.from_dict(manifest_dict, orient='index')
+            manifest_df_index = pd.DataFrame.from_dict(manifest_dict, orient="index")
             manifest_df_updated = manifest_df_index.transpose()
 
             # fill na with empty string
@@ -602,8 +655,10 @@ def add_entity_id_and_filename(self,  datasetId: str, manifest: pd.DataFrame) ->
         else:
             return manifest
 
-    def fill_in_entity_id_filename(self, datasetId: str, manifest: pd.DataFrame) -> Tuple[List, pd.DataFrame]:
-        """fill in Filename column and EntityId column. EntityId column and Filename column will be created if not already present. 
+    def fill_in_entity_id_filename(
+        self, datasetId: str, manifest: pd.DataFrame
+    ) -> Tuple[List, pd.DataFrame]:
+        """fill in Filename column and EntityId column. EntityId column and Filename column will be created if not already present.
 
         Args:
             datasetId (str): dataset syn id
@@ -620,20 +675,24 @@ def fill_in_entity_id_filename(self, datasetId: str, manifest: pd.DataFrame) ->
         # the columns Filename and entityId are assumed to be present in manifest schema
         # TODO: use idiomatic panda syntax
         if dataset_files:
-            new_files = self._get_file_entityIds(dataset_files=dataset_files, only_new_files=True, manifest=manifest)
+            new_files = self._get_file_entityIds(
+                dataset_files=dataset_files, only_new_files=True, manifest=manifest
+            )
 
             # update manifest so that it contains new dataset files
             new_files = pd.DataFrame(new_files)
             manifest = (
-                    pd.concat([manifest, new_files], sort=False)
-                    .reset_index()
-                    .drop("index", axis=1)
+                pd.concat([manifest, new_files], sort=False)
+                .reset_index()
+                .drop("index", axis=1)
             )
 
-        manifest = manifest.fillna("") 
+        manifest = manifest.fillna("")
         return dataset_files, manifest
-        
-    def updateDatasetManifestFiles(self, dmge: DataModelGraphExplorer, datasetId: str, store:bool = True) -> Union[Tuple[str, pd.DataFrame], None]:
+
+    def updateDatasetManifestFiles(
+        self, dmge: DataModelGraphExplorer, datasetId: str, store: bool = True
+    ) -> Union[Tuple[str, pd.DataFrame], None]:
         """Fetch the names and entity IDs of all current files in dataset in store, if any; update dataset's manifest with new files, if any.
 
         Args:
@@ -644,7 +703,7 @@ def updateDatasetManifestFiles(self, dmge: DataModelGraphExplorer, datasetId: st
 
 
         Returns:
-            Synapse ID of updated manifest and Pandas dataframe containing the updated manifest. 
+            Synapse ID of updated manifest and Pandas dataframe containing the updated manifest.
             If there is no existing manifest return None
         """
 
@@ -670,15 +729,21 @@ def updateDatasetManifestFiles(self, dmge: DataModelGraphExplorer, datasetId: st
                 manifest.to_csv(manifest_filepath, index=False)
 
                 # store manifest and update associated metadata with manifest on Synapse
-                manifest_id = self.associateMetadataWithFiles(dmge, manifest_filepath, datasetId)
+                manifest_id = self.associateMetadataWithFiles(
+                    dmge, manifest_filepath, datasetId
+                )
 
-        
         return manifest_id, manifest
-    
-    def _get_file_entityIds(self, dataset_files: List,  only_new_files: bool = False, manifest: pd.DataFrame = None):
+
+    def _get_file_entityIds(
+        self,
+        dataset_files: List,
+        only_new_files: bool = False,
+        manifest: pd.DataFrame = None,
+    ):
         """
         Get a dictionary of files in a dataset. Either files that are not in the current manifest or all files
-        
+
         Args:
             manifest: metadata manifest
             dataset_file: List of all files in a dataset
@@ -693,7 +758,7 @@ def _get_file_entityIds(self, dataset_files: List,  only_new_files: bool = False
                 raise UnboundLocalError(
                     "No manifest was passed in, a manifest is required when `only_new_files` is True."
                 )
-            
+
             # find new files (that are not in the current manifest) if any
             for file_id, file_name in dataset_files:
                 if not file_id in manifest["entityId"].values:
@@ -725,16 +790,16 @@ def getProjectManifests(
 
         TODO: Return manifest URI instead of Synapse ID for interoperability with other implementations of a store interface
         """
-        component=None
-        entity=None
+        component = None
+        entity = None
         manifests = []
 
         datasets = self.getStorageDatasetsInProject(projectId)
 
-        for (datasetId, datasetName) in datasets:
+        for datasetId, datasetName in datasets:
             # encode information about the manifest in a simple list (so that R clients can unpack it)
             # eventually can serialize differently
-                
+
             # Get synID of manifest for a dataset
             manifestId = self.getDatasetManifest(datasetId)
 
@@ -743,48 +808,53 @@ def getProjectManifests(
                 annotations = self.getFileAnnotations(manifestId)
 
                 # If manifest has annotations specifying component, use that
-                if annotations and 'Component' in annotations:
-                    component = annotations['Component']
+                if annotations and "Component" in annotations:
+                    component = annotations["Component"]
                     entity = self.syn.get(manifestId, downloadFile=False)
                     manifest_name = entity["properties"]["name"]
 
                 # otherwise download the manifest and parse for information
-                elif not annotations or 'Component' not in annotations:
+                elif not annotations or "Component" not in annotations:
                     logging.debug(
                         f"No component annotations have been found for manifest {manifestId}. "
                         "The manifest will be downloaded and parsed instead. "
                         "For increased speed, add component annotations to manifest."
-                        )
+                    )
 
-                    manifest_info = self.getDatasetManifest(datasetId,downloadFile=True)
+                    manifest_info = self.getDatasetManifest(
+                        datasetId, downloadFile=True
+                    )
                     manifest_name = manifest_info["properties"].get("name", "")
 
                     if not manifest_name:
-                        logger.error(f'Failed to download manifests from {datasetId}') 
+                        logger.error(f"Failed to download manifests from {datasetId}")
 
                     manifest_path = manifest_info["path"]
 
                     manifest_df = load_df(manifest_path)
 
                     # Get component from component column if it exists
-                    if "Component" in manifest_df and not manifest_df["Component"].empty:
-                        list(set(manifest_df['Component']))
+                    if (
+                        "Component" in manifest_df
+                        and not manifest_df["Component"].empty
+                    ):
+                        list(set(manifest_df["Component"]))
                         component = list(set(manifest_df["Component"]))
 
-                        #Added to address issues raised during DCA testing
-                        if '' in component:
-                            component.remove('')
+                        # Added to address issues raised during DCA testing
+                        if "" in component:
+                            component.remove("")
 
                         if len(component) == 1:
                             component = component[0]
                         elif len(component) > 1:
                             logging.warning(
-                            f"Manifest {manifestId} is composed of multiple components. Schematic does not support mulit-component manifests at this time."
-                            "Behavior of manifests with multiple components is undefined"
+                                f"Manifest {manifestId} is composed of multiple components. Schematic does not support mulit-component manifests at this time."
+                                "Behavior of manifests with multiple components is undefined"
                             )
             else:
                 manifest_name = ""
-                component = None              
+                component = None
             if component:
                 manifest = (
                     (datasetId, datasetName),
@@ -792,7 +862,9 @@ def getProjectManifests(
                     (component, component),
                 )
             elif manifestId:
-                logging.debug(f"Manifest {manifestId} does not have an associated Component")
+                logging.debug(
+                    f"Manifest {manifestId} does not have an associated Component"
+                )
                 manifest = (
                     (datasetId, datasetName),
                     (manifestId, manifest_name),
@@ -807,10 +879,12 @@ def getProjectManifests(
 
             if manifest:
                 manifests.append(manifest)
-                
+
         return manifests
 
-    def upload_project_manifests_to_synapse(self, dmge: DataModelGraphExplorer, projectId: str) -> List[str]:
+    def upload_project_manifests_to_synapse(
+        self, dmge: DataModelGraphExplorer, projectId: str
+    ) -> List[str]:
         """Upload all metadata manifest files across all datasets in a specified project as tables in Synapse.
 
         Returns: String of all the manifest_table_ids of all the manifests that have been loaded.
@@ -820,7 +894,7 @@ def upload_project_manifests_to_synapse(self, dmge: DataModelGraphExplorer, proj
         manifest_loaded = []
         datasets = self.getStorageDatasetsInProject(projectId)
 
-        for (datasetId, datasetName) in datasets:
+        for datasetId, datasetName in datasets:
             # encode information about the manifest in a simple list (so that R clients can unpack it)
             # eventually can serialize differently
 
@@ -832,20 +906,27 @@ def upload_project_manifests_to_synapse(self, dmge: DataModelGraphExplorer, proj
                 manifest_name = manifest_info["properties"]["name"]
                 manifest_path = manifest_info["path"]
                 manifest_df = load_df(manifest_path)
-                manifest_table_id = uploadDB(dmge=dmge, manifest=manifest, datasetId=datasetId, table_name=datasetName)
+                manifest_table_id = uploadDB(
+                    dmge=dmge,
+                    manifest=manifest,
+                    datasetId=datasetId,
+                    table_name=datasetName,
+                )
                 manifest_loaded.append(datasetName)
         return manifest_loaded
 
-    def upload_annotated_project_manifests_to_synapse(self, projectId:str, path_to_json_ld: str, dry_run: bool = False) -> List[str]:
-        '''
+    def upload_annotated_project_manifests_to_synapse(
+        self, projectId: str, path_to_json_ld: str, dry_run: bool = False
+    ) -> List[str]:
+        """
         Purpose:
             For all manifests in a project, upload them as a table and add annotations manifest csv.
             Assumes the manifest is already present as a CSV in a dataset in the project.
 
-        '''
+        """
         # Instantiate DataModelParser
-        data_model_parser = DataModelParser(path_to_data_model = path_to_json_ld)
-        #Parse Model
+        data_model_parser = DataModelParser(path_to_data_model=path_to_json_ld)
+        # Parse Model
         parsed_data_model = data_model_parser.parse_model()
 
         # Instantiate DataModelGraph
@@ -854,13 +935,13 @@ def upload_annotated_project_manifests_to_synapse(self, projectId:str, path_to_j
         # Generate graph
         graph_data_model = data_model_grapher.generate_data_model_graph()
 
-        #Instantiate DataModelGraphExplorer
+        # Instantiate DataModelGraphExplorer
         dmge = DataModelGraphExplorer(graph_data_model)
 
         manifests = []
         manifest_loaded = []
         datasets = self.getStorageDatasetsInProject(projectId)
-        for (datasetId, datasetName) in datasets:
+        for datasetId, datasetName in datasets:
             # encode information about the manifest in a simple list (so that R clients can unpack it)
             # eventually can serialize differently
 
@@ -873,15 +954,26 @@ def upload_annotated_project_manifests_to_synapse(self, projectId:str, path_to_j
                 manifest_id = manifest_info["properties"]["id"]
                 manifest_name = manifest_info["properties"]["name"]
                 manifest_path = manifest_info["path"]
-                manifest = ((datasetId, datasetName), (manifest_id, manifest_name), ("", ""))
+                manifest = (
+                    (datasetId, datasetName),
+                    (manifest_id, manifest_name),
+                    ("", ""),
+                )
                 if not dry_run:
-                    manifest_syn_id = self.associateMetadataWithFiles(dmge, manifest_path, datasetId, manifest_record_type='table')
+                    manifest_syn_id = self.associateMetadataWithFiles(
+                        dmge, manifest_path, datasetId, manifest_record_type="table"
+                    )
                 manifest_loaded.append(manifest)
-            
-        return manifests, manifest_loaded
 
+        return manifests, manifest_loaded
 
-    def move_entities_to_new_project(self, projectId: str, newProjectId: str, returnEntities: bool = False, dry_run: bool = False):
+    def move_entities_to_new_project(
+        self,
+        projectId: str,
+        newProjectId: str,
+        returnEntities: bool = False,
+        dry_run: bool = False,
+    ):
         """
         For each manifest csv in a project, look for all the entitiy ids that are associated.
         Look up the entitiy in the files, move the entity to new project.
@@ -891,7 +983,7 @@ def move_entities_to_new_project(self, projectId: str, newProjectId: str, return
         manifest_loaded = []
         datasets = self.getStorageDatasetsInProject(projectId)
         if datasets:
-            for (datasetId, datasetName) in datasets:
+            for datasetId, datasetName in datasets:
                 # encode information about the manifest in a simple list (so that R clients can unpack it)
                 # eventually can serialize differently
 
@@ -905,35 +997,48 @@ def move_entities_to_new_project(self, projectId: str, newProjectId: str, return
                     manifest_path = manifest_info["path"]
                     manifest_df = load_df(manifest_path)
 
-                    manifest = ((datasetId, datasetName), (manifest_id, manifest_name), ("", ""))
+                    manifest = (
+                        (datasetId, datasetName),
+                        (manifest_id, manifest_name),
+                        ("", ""),
+                    )
                     manifest_loaded.append(manifest)
 
                     annotation_entities = self.storageFileviewTable[
-                            (self.storageFileviewTable['id'].isin(manifest_df['entityId']))
-                            & (self.storageFileviewTable['type'] == 'folder')
-                        ]['id']
+                        (self.storageFileviewTable["id"].isin(manifest_df["entityId"]))
+                        & (self.storageFileviewTable["type"] == "folder")
+                    ]["id"]
 
                     if returnEntities:
-                        for entityId in annotation_entities: 
+                        for entityId in annotation_entities:
                             if not dry_run:
                                 self.syn.move(entityId, datasetId)
                             else:
-                                logging.info(f"{entityId} will be moved to folder {datasetId}.")
-                    else:                
+                                logging.info(
+                                    f"{entityId} will be moved to folder {datasetId}."
+                                )
+                    else:
                         # generate project folder
-                        archive_project_folder = Folder(projectId+'_archive', parent = newProjectId)
+                        archive_project_folder = Folder(
+                            projectId + "_archive", parent=newProjectId
+                        )
                         archive_project_folder = self.syn.store(archive_project_folder)
-        
+
                         # generate dataset folder
-                        dataset_archive_folder = Folder("_".join([datasetId,datasetName,'archive']), parent = archive_project_folder.id)
-                        dataset_archive_folder = self.syn.store(dataset_archive_folder)                    
+                        dataset_archive_folder = Folder(
+                            "_".join([datasetId, datasetName, "archive"]),
+                            parent=archive_project_folder.id,
+                        )
+                        dataset_archive_folder = self.syn.store(dataset_archive_folder)
 
                         for entityId in annotation_entities:
                             # move entities to folder
                             if not dry_run:
                                 self.syn.move(entityId, dataset_archive_folder.id)
                             else:
-                                logging.info(f"{entityId} will be moved to folder {dataset_archive_folder.id}.")
+                                logging.info(
+                                    f"{entityId} will be moved to folder {dataset_archive_folder.id}."
+                                )
         else:
             raise LookupError(
                 f"No datasets were found in the specified project: {projectId}. Re-check specified master_fileview in CONFIG and retry."
@@ -957,7 +1062,7 @@ def _get_tables(self, datasetId: str = None, projectId: str = None) -> List[Tabl
             project = projectId
         elif datasetId:
             project = self.syn.get(self.getDatasetProject(datasetId))
-        
+
         return list(self.syn.getChildren(project, includeTypes=["table"]))
 
     def get_table_info(self, datasetId: str = None, projectId: str = None) -> List[str]:
@@ -966,205 +1071,266 @@ def get_table_info(self, datasetId: str = None, projectId: str = None) -> List[s
         Returns:
             list[str]: A list of table names
         """
-        tables = self._get_tables(datasetId = datasetId, projectId = projectId)
+        tables = self._get_tables(datasetId=datasetId, projectId=projectId)
         if tables:
             return {table["name"]: table["id"] for table in tables}
-        else: 
-            return {None:None}
+        else:
+            return {None: None}
 
     @missing_entity_handler
-    def uploadDB(self, 
-        dmge: DataModelGraphExplorer, 
-        manifest: pd.DataFrame, 
-        datasetId: str, 
-        table_name: str, 
-        restrict: bool = False, 
-        useSchemaLabel: bool = True, 
-        table_manipulation: str = 'replace',
-        ):
+    def uploadDB(
+        self,
+        dmge: DataModelGraphExplorer,
+        manifest: pd.DataFrame,
+        datasetId: str,
+        table_name: str,
+        restrict: bool = False,
+        table_manipulation: str = "replace",
+        table_column_names: str = "class_label",
+    ):
         """
         Method to upload a database to an asset store. In synapse, this will upload a metadata table
-        
+
         Args:
             dmge: DataModelGraphExplorer object
             manifest: pd.Df manifest to upload
             datasetId: synID of the dataset for the manifest
             table_name: name of the table to be uploaded
-            restrict: bool, whether or not the manifest contains sensitive data that will need additional access restrictions 
-            useSchemaLabel: bool whether to use schemaLabel (True) or display label (False)
+            restrict: bool, whether or not the manifest contains sensitive data that will need additional access restrictions
             existingTableId: str of the synId of the existing table, if one already exists
             table_manipulation: str, 'replace' or 'upsert', in the case where a manifest already exists, should the new metadata replace the existing (replace) or be added to it (upsert)
-
+            table_column_names: (str): display_name/display_label/class_label (default). Sets labeling style for table column names. display_name will use the raw display name as the column name. class_label will format the display
+                name as upper camelcase, and strip blacklisted characters, display_label will strip blacklisted characters including spaces, to retain
+                display label formatting.
         Returns:
             manifest_table_id: synID of the uploaded table
             manifest: the original manifset
             table_manifest: manifest formatted appropriately for the table
-        
+
         """
-        
 
-        col_schema, table_manifest = self.formatDB(dmge=dmge, manifest=manifest, useSchemaLabel=useSchemaLabel)
+        col_schema, table_manifest = self.formatDB(
+            dmge=dmge, manifest=manifest, table_column_names=table_column_names
+        )
 
-        manifest_table_id = self.buildDB(datasetId, table_name, col_schema, table_manifest, table_manipulation, dmge, restrict,)
+        manifest_table_id = self.buildDB(
+            datasetId,
+            table_name,
+            col_schema,
+            table_manifest,
+            table_manipulation,
+            dmge,
+            restrict,
+        )
 
         return manifest_table_id, manifest, table_manifest
 
-    def formatDB(self, dmge, manifest, useSchemaLabel):
+    def formatDB(self, dmge, manifest, table_column_names):
         """
         Method to format a manifest appropriatly for upload as table
-        
+
         Args:
             dmge: DataModelGraphExplorer object
             manifest: pd.Df manifest to upload
-            useSchemaLabel: bool whether to use schemaLabel (True) or display label (False)
-
+            table_column_names: (str): display_name/display_label/class_label (default). Sets labeling style for table column names. display_name will use the raw display name as the column name. class_label will format the display
+                name as upper camelcase, and strip blacklisted characters, display_label will strip blacklisted characters including spaces, to retain
+                display label formatting.
         Returns:
             col_schema: schema for table columns: type, size, etc
             table_manifest: formatted manifest
-        
+
         """
         # Rename the manifest columns to display names to match fileview
 
-        blacklist_chars = ['(', ')', '.', ' ', '-']
+        blacklist_chars = ["(", ")", ".", " ", "-"]
         manifest_columns = manifest.columns.tolist()
 
-        table_manifest=deepcopy(manifest)
+        table_manifest = deepcopy(manifest)
+
+        if table_column_names == "display_name":
+            cols = table_manifest.columns
 
-        if useSchemaLabel:
+        elif table_column_names == "display_label":
             cols = [
-                get_class_label_from_display_name(
-                    str(col)
-                    ).translate({ord(x): '' for x in blacklist_chars})
+                str(col).translate({ord(x): "" for x in blacklist_chars})
                 for col in manifest_columns
             ]
 
-            cols = list(map(lambda x: x.replace('EntityId', 'entityId'), cols))
+        elif table_column_names == "class_label":
+            cols = [
+                get_class_label_from_display_name(str(col)).translate(
+                    {ord(x): "" for x in blacklist_chars}
+                )
+                for col in manifest_columns
+            ]
+        else:
+            ValueError(
+                f"The provided table_column_name: {table_column_names} is not valid, please resubmit with an allowed value only."
+            )
 
+        cols = list(map(lambda x: x.replace("EntityId", "entityId"), cols))
 
-            # Reset column names in table manifest
-            table_manifest.columns = cols
+        # Reset column names in table manifest
+        table_manifest.columns = cols
 
-        #move entity id to end of df
-        entity_col = table_manifest.pop('entityId')
-        table_manifest.insert(len(table_manifest.columns), 'entityId', entity_col)
+        # move entity id to end of df
+        entity_col = table_manifest.pop("entityId")
+        table_manifest.insert(len(table_manifest.columns), "entityId", entity_col)
 
         # Get the column schema
         col_schema = as_table_columns(table_manifest)
 
         # Set Id column length to 64 (for some reason not being auto set.)
         for i, col in enumerate(col_schema):
-            if col['name'].lower() == 'id':
-                col_schema[i]['maximumSize'] = 64
+            if col["name"].lower() == "id":
+                col_schema[i]["maximumSize"] = 64
 
         return col_schema, table_manifest
 
-    def buildDB(self,  
-        datasetId: str, 
-        table_name: str, 
+    def buildDB(
+        self,
+        datasetId: str,
+        table_name: str,
         col_schema: List,
         table_manifest: pd.DataFrame,
         table_manipulation: str,
-        dmge: DataModelGraphExplorer,  
+        dmge: DataModelGraphExplorer,
         restrict: bool = False,
-        
-        ):
+    ):
         """
         Method to construct the table appropriately: create new table, replace existing, or upsert new into existing
-        Calls TableOperations class to execute 
-        
+        Calls TableOperations class to execute
+
         Args:
             datasetId: synID of the dataset for the manifest
             table_name: name of the table to be uploaded
             col_schema: schema for table columns: type, size, etc from `formatDB`
             table_manifest: formatted manifest that can be uploaded as a table
             table_manipulation: str, 'replace' or 'upsert', in the case where a manifest already exists, should the new metadata replace the existing (replace) or be added to it (upsert)
-            restrict: bool, whether or not the manifest contains sensitive data that will need additional access restrictions 
+            restrict: bool, whether or not the manifest contains sensitive data that will need additional access restrictions
 
         Returns:
             manifest_table_id: synID of the uploaded table
-        
+
         """
-        table_info = self.get_table_info(datasetId = datasetId)
+        table_info = self.get_table_info(datasetId=datasetId)
         # Put table manifest onto synapse
-        schema = Schema(name=table_name, columns=col_schema, parent=self.getDatasetProject(datasetId))
+        schema = Schema(
+            name=table_name,
+            columns=col_schema,
+            parent=self.getDatasetProject(datasetId),
+        )
 
         if table_name in table_info:
             existingTableId = table_info[table_name]
         else:
             existingTableId = None
 
-
         tableOps = TableOperations(
-            synStore = self,  
-            tableToLoad = table_manifest,
-            tableName = table_name,
-            datasetId = datasetId, 
-            existingTableId = existingTableId,
-            restrict = restrict,
-            )
+            synStore=self,
+            tableToLoad=table_manifest,
+            tableName=table_name,
+            datasetId=datasetId,
+            existingTableId=existingTableId,
+            restrict=restrict,
+        )
 
         if not table_manipulation or table_name not in table_info.keys():
-            manifest_table_id = tableOps.createTable(columnTypeDict=col_schema, specifySchema=True,)
+            manifest_table_id = tableOps.createTable(
+                columnTypeDict=col_schema,
+                specifySchema=True,
+            )
         elif table_name in table_info.keys() and table_info[table_name]:
-
-            if table_manipulation.lower() == 'replace':
-                manifest_table_id = tableOps.replaceTable(specifySchema = True, columnTypeDict=col_schema,)
-            elif table_manipulation.lower() == 'upsert':
-                manifest_table_id = tableOps.upsertTable(dmge=dmge,)
-            elif table_manipulation.lower() == 'update':
+            if table_manipulation.lower() == "replace":
+                manifest_table_id = tableOps.replaceTable(
+                    specifySchema=True,
+                    columnTypeDict=col_schema,
+                )
+            elif table_manipulation.lower() == "upsert":
+                manifest_table_id = tableOps.upsertTable(
+                    dmge=dmge,
+                )
+            elif table_manipulation.lower() == "update":
                 manifest_table_id = tableOps.updateTable()
 
-
-
-        if table_manipulation and table_manipulation.lower() == 'upsert':
-            existing_tables=self.get_table_info(datasetId=datasetId)
-            tableId=existing_tables[table_name]
+        if table_manipulation and table_manipulation.lower() == "upsert":
+            existing_tables = self.get_table_info(datasetId=datasetId)
+            tableId = existing_tables[table_name]
             annos = self.syn.get_annotations(tableId)
-            annos['primary_key'] = table_manifest['Component'][0] + "_id"
+            annos["primary_key"] = table_manifest["Component"][0] + "_id"
             annos = self.syn.set_annotations(annos)
 
         return manifest_table_id
 
-
-    def upload_manifest_file(self, manifest, metadataManifestPath, datasetId, restrict_manifest, component_name = ''):
+    def upload_manifest_file(
+        self,
+        manifest,
+        metadataManifestPath,
+        datasetId,
+        restrict_manifest,
+        component_name="",
+    ):
         # Update manifest to have the new entityId column
         manifest.to_csv(metadataManifestPath, index=False)
 
         # store manifest to Synapse as a CSV
         # update file name
-        file_name_full = metadataManifestPath.split('/')[-1]
-        file_extension = file_name_full.split('.')[-1]
+        file_name_full = metadataManifestPath.split("/")[-1]
+        file_extension = file_name_full.split(".")[-1]
 
         # Differentiate "censored" and "uncensored" manifest
-        if "censored" in file_name_full: 
-            file_name_new = os.path.basename(CONFIG.synapse_manifest_basename) + "_" + component_name + "_censored" + '.' + file_extension
-        else: 
-            file_name_new = os.path.basename(CONFIG.synapse_manifest_basename) + "_" + component_name + '.' + file_extension
+        if "censored" in file_name_full:
+            file_name_new = (
+                os.path.basename(CONFIG.synapse_manifest_basename)
+                + "_"
+                + component_name
+                + "_censored"
+                + "."
+                + file_extension
+            )
+        else:
+            file_name_new = (
+                os.path.basename(CONFIG.synapse_manifest_basename)
+                + "_"
+                + component_name
+                + "."
+                + file_extension
+            )
 
         manifestSynapseFile = File(
             metadataManifestPath,
             description="Manifest for dataset " + datasetId,
             parent=datasetId,
-            name=file_name_new
+            name=file_name_new,
+        )
+
+        manifest_synapse_file_id = self.syn.store(
+            manifestSynapseFile, isRestricted=restrict_manifest
+        ).id
+        changeFileMetaData(
+            syn=self.syn, entity=manifest_synapse_file_id, downloadAs=file_name_new
         )
 
-        manifest_synapse_file_id = self.syn.store(manifestSynapseFile, isRestricted = restrict_manifest).id
-        changeFileMetaData(syn = self.syn, entity = manifest_synapse_file_id, downloadAs = file_name_new)
-        
         return manifest_synapse_file_id
 
     @missing_entity_handler
-    def format_row_annotations(self, dmge, row, entityId, hideBlanks):
+    def format_row_annotations(
+        self, dmge, row, entityId: str, hideBlanks: bool, annotation_keys: str
+    ):
         # prepare metadata for Synapse storage (resolve display name into a name that Synapse annotations support (e.g no spaces, parenthesis)
         # note: the removal of special characters, will apply only to annotation keys; we are not altering the manifest
         # this could create a divergence between manifest column and annotations. this should be ok for most use cases.
         # columns with special characters are outside of the schema
         metadataSyn = {}
-        blacklist_chars = ['(', ')', '.', ' ', '-']
-        
-        for k, v in row.to_dict().items():
+        blacklist_chars = ["(", ")", ".", " ", "-"]
 
-            keySyn = get_class_label_from_display_name(str(k)).translate({ord(x): '' for x in blacklist_chars})
+        for k, v in row.to_dict().items():
+            if annotation_keys == "display_label":
+                keySyn = str(k).translate({ord(x): "" for x in blacklist_chars})
+            elif annotation_keys == "class_label":
+                keySyn = get_class_label_from_display_name(str(k)).translate(
+                    {ord(x): "" for x in blacklist_chars}
+                )
 
             # Skip `Filename` and `ETag` columns when setting annotations
             if keySyn in ["Filename", "ETag", "eTag"]:
@@ -1181,45 +1347,51 @@ def format_row_annotations(self, dmge, row, entityId, hideBlanks):
             metadataSyn[keySyn] = v
         # set annotation(s) for the various objects/items in a dataset on Synapse
         annos = self.syn.get_annotations(entityId)
-        csv_list_regex=comma_separated_list_regex()
+        csv_list_regex = comma_separated_list_regex()
         for anno_k, anno_v in metadataSyn.items():
-            
             # Remove keys with nan or empty string values from dict of annotations to be uploaded
             # if present on current data annotation
-            if hideBlanks and (anno_v == '' or (isinstance(anno_v,float) and np.isnan(anno_v))):
+            if hideBlanks and (
+                anno_v == "" or (isinstance(anno_v, float) and np.isnan(anno_v))
+            ):
                 annos.pop(anno_k) if anno_k in annos.keys() else annos
             # Otherwise save annotation as approrpriate
             else:
-                if isinstance(anno_v,float) and np.isnan(anno_v):
-                        annos[anno_k] = ""
-                elif isinstance(anno_v,str) and re.fullmatch(csv_list_regex, anno_v) and rule_in_rule_list('list', dmge.get_node_validation_rules(anno_k)):
+                if isinstance(anno_v, float) and np.isnan(anno_v):
+                    annos[anno_k] = ""
+                elif (
+                    isinstance(anno_v, str)
+                    and re.fullmatch(csv_list_regex, anno_v)
+                    and rule_in_rule_list(
+                        "list", dmge.get_node_validation_rules(anno_k)
+                    )
+                ):
                     annos[anno_k] = anno_v.split(",")
                 else:
                     annos[anno_k] = anno_v
-                
+
         return annos
 
     @missing_entity_handler
     def format_manifest_annotations(self, manifest, manifest_synapse_id):
-        '''
+        """
         Set annotations for the manifest (as a whole) so they can be applied to the manifest table or csv.
         For now just getting the Component.
-        '''
-        
+        """
+
         entity = self.syn.get(manifest_synapse_id, downloadFile=False)
         is_file = entity.concreteType.endswith(".FileEntity")
         is_table = entity.concreteType.endswith(".TableEntity")
 
         if is_file:
-
             # Get file metadata
             metadata = self.getFileAnnotations(manifest_synapse_id)
 
             # If there is a defined component add it to the metadata.
-            if 'Component' in manifest.columns:
+            if "Component" in manifest.columns:
                 # Gather component information
-                component = manifest['Component'].unique()
-                
+                component = manifest["Component"].unique()
+
                 # Double check that only a single component is listed, else raise an error.
                 try:
                     len(component) == 1
@@ -1229,12 +1401,12 @@ def format_manifest_annotations(self, manifest, manifest_synapse_id):
                     ) from err
 
                 # Add component to metadata
-                metadata['Component'] = component[0]
-        
+                metadata["Component"] = component[0]
+
         elif is_table:
             # Get table metadata
             metadata = self.getTableAnnotations(manifest_synapse_id)
-        
+
         # Get annotations
         annos = self.syn.get_annotations(manifest_synapse_id)
 
@@ -1243,6 +1415,7 @@ def format_manifest_annotations(self, manifest, manifest_synapse_id):
             annos[annos_k] = annos_v
 
         return annos
+
     '''
     def annotate_upload_manifest_table(self, manifest, datasetId, metadataManifestPath,
         useSchemaLabel: bool = True, hideBlanks: bool = False, restrict_manifest = False):
@@ -1320,7 +1493,7 @@ def annotate_upload_manifest_table(self, manifest, datasetId, metadataManifestPa
         return manifest_synapse_table_id
     '''
 
-    def _read_manifest(self, metadataManifestPath:str) -> pd.DataFrame:
+    def _read_manifest(self, metadataManifestPath: str) -> pd.DataFrame:
         """Helper function to read in provided manifest as a pandas DataFrame for subsequent downstream processing.
         Args:
             metadataManifestPath (str): path where manifest is stored
@@ -1331,17 +1504,21 @@ def _read_manifest(self, metadataManifestPath:str) -> pd.DataFrame:
         """
         # read new manifest csv
         try:
-            load_args={
-                "dtype":"string",
+            load_args = {
+                "dtype": "string",
             }
-            manifest = load_df(metadataManifestPath, preserve_raw_input = False, **load_args)
+            manifest = load_df(
+                metadataManifestPath, preserve_raw_input=False, **load_args
+            )
         except FileNotFoundError as err:
             raise FileNotFoundError(
                 f"No manifest file was found at this path: {metadataManifestPath}"
             ) from err
         return manifest
 
-    def _add_id_columns_to_manifest(self, manifest: pd.DataFrame, dmge: DataModelGraphExplorer):
+    def _add_id_columns_to_manifest(
+        self, manifest: pd.DataFrame, dmge: DataModelGraphExplorer
+    ):
         """Helper function to add id and entityId columns to the manifest if they do not already exist, Fill id values per row.
         Args:
             Manifest loaded as a pd.Dataframe
@@ -1353,22 +1530,28 @@ def _add_id_columns_to_manifest(self, manifest: pd.DataFrame, dmge: DataModelGra
         if not col_in_dataframe("Id", manifest):
             # See if schema has `Uuid` column specified
             try:
-                uuid_col_in_schema = dmge.is_class_in_schema('Uuid') or dmge.is_class_in_schema('uuid')      
-            except (KeyError):
+                uuid_col_in_schema = dmge.is_class_in_schema(
+                    "Uuid"
+                ) or dmge.is_class_in_schema("uuid")
+            except KeyError:
                 uuid_col_in_schema = False
 
             # Rename `Uuid` column if it wasn't specified in the schema
             if col_in_dataframe("Uuid", manifest) and not uuid_col_in_schema:
-                manifest.rename(columns={'Uuid': 'Id'}, inplace=True)
+                manifest.rename(columns={"Uuid": "Id"}, inplace=True)
             # If no `Uuid` column exists or it is specified in the schema, create a new `Id` column
             else:
-                manifest["Id"] = ''
+                manifest["Id"] = ""
 
-        for idx,row in manifest.iterrows():
-            if not row["Id"]:
+        # Retrieve the ID column name (id, Id and ID) are treated the same.
+        id_col_name = [col for col in manifest.columns if col.lower() == "id"][0]
+
+        # Check if values have been added to the Id coulumn, if not add a UUID so value in the row is not blank.
+        for idx, row in manifest.iterrows():
+            if not row[id_col_name]:
                 gen_uuid = str(uuid.uuid4())
-                row["Id"] = gen_uuid
-                manifest.loc[idx, 'Id'] = gen_uuid
+                row[id_col_name] = gen_uuid
+                manifest.loc[idx, id_col_name] = gen_uuid
 
         # add entityId as a column if not already there or
         # fill any blanks with an empty string.
@@ -1388,29 +1571,41 @@ def _generate_table_name(self, manifest):
             component_name (str): Name of the manifest component (if applicable)
         """
         # Create table name here.
-        if 'Component' in manifest.columns:
-            component_name = manifest['Component'][0].lower()
-            table_name = component_name + '_synapse_storage_manifest_table'
+        if "Component" in manifest.columns:
+            component_name = manifest["Component"][0].lower()
+            table_name = component_name + "_synapse_storage_manifest_table"
         else:
-            component_name = ''
-            table_name = 'synapse_storage_manifest_table'
+            component_name = ""
+            table_name = "synapse_storage_manifest_table"
         return table_name, component_name
 
-    def _add_annotations(self, dmge, row, entityId, hideBlanks):
+    def _add_annotations(
+        self,
+        dmge,
+        row,
+        entityId: str,
+        hideBlanks: bool,
+        annotation_keys: str,
+    ):
         """Helper function to format and add annotations to entities in Synapse.
         Args:
             dmge: DataModelGraphExplorer object,
             row: current row of manifest being processed
             entityId (str): synapseId of entity to add annotations to
             hideBlanks: Boolean flag that does not upload annotation keys with blank values when true. Uploads Annotation keys with empty string values when false.
+            annotation_keys:  (str) display_label/class_label(default), Determines labeling syle for annotation keys. class_label will format the display
+                name as upper camelcase, and strip blacklisted characters, display_label will strip blacklisted characters including spaces, to retain
+                display label formatting while ensuring the label is formatted properly for Synapse annotations.
         Returns:
             Annotations are added to entities in Synapse, no return.
         """
         # Format annotations for Synapse
-        annos = self.format_row_annotations(dmge, row, entityId, hideBlanks)
+        annos = self.format_row_annotations(
+            dmge, row, entityId, hideBlanks, annotation_keys
+        )
 
         if annos:
-        # Store annotations for an entity folder
+            # Store annotations for an entity folder
             self.syn.set_annotations(annos)
         return
 
@@ -1424,7 +1619,7 @@ def _create_entity_id(self, idx, row, manifest, datasetId):
         Returns:
             manifest (pd.DataFrame): manifest with entityId added to the appropriate row
             entityId (str): Generated Entity Id.
-        
+
         """
         rowEntity = Folder(str(uuid.uuid4()), parent=datasetId)
         rowEntity = self.syn.store(rowEntity)
@@ -1434,15 +1629,16 @@ def _create_entity_id(self, idx, row, manifest, datasetId):
         return manifest, entityId
 
     def add_annotations_to_entities_files(
-                    self,
-                    dmge,
-                    manifest,
-                    manifest_record_type,
-                    datasetId,
-                    hideBlanks,
-                    manifest_synapse_table_id=''
-                    ):
-        '''Depending on upload type add Ids to entityId row. Add anotations to connected files.
+        self,
+        dmge,
+        manifest,
+        manifest_record_type: str,
+        datasetId: str,
+        hideBlanks: bool,
+        manifest_synapse_table_id="",
+        annotation_keys: str = "class_label",
+    ):
+        """Depending on upload type add Ids to entityId row. Add anotations to connected files.
         Args:
             dmge: DataModelGraphExplorer Object
             manifest (pd.DataFrame): loaded df containing user supplied data.
@@ -1450,55 +1646,67 @@ def add_annotations_to_entities_files(
             datasetId (str): synapse ID of folder containing the dataset
             hideBlanks (bool): Default is false -Boolean flag that does not upload annotation keys with blank values when true. Uploads Annotation keys with empty string values when false.
             manifest_synapse_table_id (str): Default is an empty string ''.
+            annotation_keys: (str) display_label/class_label(default), Determines labeling syle for annotation keys. class_label will format the display
+                name as upper camelcase, and strip blacklisted characters, display_label will strip blacklisted characters including spaces, to retain
+                display label formatting while ensuring the label is formatted properly for Synapse annotations.
         Returns:
             manifest (pd.DataFrame): modified to add entitiyId as appropriate.
 
-        '''
+        """
 
         # Expected behavior is to annotate files if `Filename` is present regardless of `-mrt` setting
-        if 'filename' in [col.lower() for col in manifest.columns]:
+        if "filename" in [col.lower() for col in manifest.columns]:
             # get current list of files and store as dataframe
             dataset_files = self.getFilesInStorageDataset(datasetId)
-            files_and_entityIds = self._get_file_entityIds(dataset_files=dataset_files, only_new_files=False)
+            files_and_entityIds = self._get_file_entityIds(
+                dataset_files=dataset_files, only_new_files=False
+            )
             file_df = pd.DataFrame(files_and_entityIds)
-            
+
             # Merge dataframes to add entityIds
-            manifest = manifest.merge(file_df, how = 'left', on='Filename', suffixes=['_x',None]).drop('entityId_x',axis=1)
+            manifest = manifest.merge(
+                file_df, how="left", on="Filename", suffixes=["_x", None]
+            ).drop("entityId_x", axis=1)
 
         # Fill `entityId` for each row if missing and annotate entity as appropriate
         for idx, row in manifest.iterrows():
-            if not row["entityId"] and (manifest_record_type == 'file_and_entities' or 
-                manifest_record_type == 'table_file_and_entities'):
-                manifest, entityId = self._create_entity_id(idx, row, manifest, datasetId)
-            elif not row["entityId"] and manifest_record_type == 'table_and_file':
-                # If not using entityIds, fill with manifest_table_id so 
+            if not row["entityId"] and (
+                manifest_record_type == "file_and_entities"
+                or manifest_record_type == "table_file_and_entities"
+            ):
+                manifest, entityId = self._create_entity_id(
+                    idx, row, manifest, datasetId
+                )
+            elif not row["entityId"] and manifest_record_type == "table_and_file":
+                # If not using entityIds, fill with manifest_table_id so
                 row["entityId"] = manifest_synapse_table_id
                 manifest.loc[idx, "entityId"] = manifest_synapse_table_id
-                entityId = ''
+                entityId = ""
             else:
                 # get the file id of the file to annotate, collected in above step.
                 entityId = row["entityId"]
 
             # Adding annotations to connected files.
             if entityId:
-                self._add_annotations(dmge, row, entityId, hideBlanks)
+                self._add_annotations(dmge, row, entityId, hideBlanks, annotation_keys)
                 logger.info(f"Added annotations to entity: {entityId}")
         return manifest
 
     def upload_manifest_as_table(
-                            self,
-                            dmge,
-                            manifest,
-                            metadataManifestPath,
-                            datasetId,
-                            table_name,
-                            component_name,
-                            restrict,
-                            manifest_record_type,
-                            useSchemaLabel,
-                            hideBlanks,
-                            table_manipulation,
-                            ):
+        self,
+        dmge: DataModelGraphExplorer,
+        manifest: pd.DataFrame,
+        metadataManifestPath: str,
+        datasetId: str,
+        table_name: str,
+        component_name: str,
+        restrict: bool,
+        manifest_record_type: str,
+        hideBlanks: bool,
+        table_manipulation: str,
+        table_column_names: str,
+        annotation_keys: str,
+    ):
         """Upload manifest to Synapse as a table and csv.
         Args:
             dmge: DataModelGraphExplorer object
@@ -1511,53 +1719,81 @@ def upload_manifest_as_table(
             manifest_record_type (str): valid values are 'entity', 'table' or 'both'. Specifies whether to create entity ids and folders for each row in a manifest, a Synapse table to house the entire manifest or do both.
             hideBlanks (bool): Default is False -Boolean flag that does not upload annotation keys with blank values when true. Uploads Annotation keys with empty string values when false.
             table_malnipulation (str): Specify the way the manifest tables should be store as on Synapse when one with the same name already exists. Options are 'replace' and 'upsert'.
+            table_column_names: (str): display_name/display_label/class_label (default). Sets labeling style for table column names. display_name will use the raw display name as the column name. class_label will format the display
+                name as upper camelcase, and strip blacklisted characters, display_label will strip blacklisted characters including spaces, to retain
+                display label formatting.
+            annotation_keys: (str) display_label/class_label (default), Sets labeling syle for annotation keys. class_label will format the display
+                name as upper camelcase, and strip blacklisted characters, display_label will strip blacklisted characters including spaces, to retain
+                display label formatting while ensuring the label is formatted properly for Synapse annotations.
         Return:
             manifest_synapse_file_id: SynID of manifest csv uploaded to synapse.
-        """      
+        """
         # Upload manifest as a table, get the ID and updated manifest.
         manifest_synapse_table_id, manifest, table_manifest = self.uploadDB(
-                                                    dmge=dmge,
-                                                    manifest=manifest,
-                                                    datasetId=datasetId,
-                                                    table_name=table_name,
-                                                    restrict=restrict,
-                                                    useSchemaLabel=useSchemaLabel,
-                                                    table_manipulation=table_manipulation)
-
-        manifest = self.add_annotations_to_entities_files(dmge, manifest, manifest_record_type, datasetId, hideBlanks, manifest_synapse_table_id)
+            dmge=dmge,
+            manifest=manifest,
+            datasetId=datasetId,
+            table_name=table_name,
+            restrict=restrict,
+            table_manipulation=table_manipulation,
+            table_column_names=table_column_names,
+        )
+
+        manifest = self.add_annotations_to_entities_files(
+            dmge,
+            manifest,
+            manifest_record_type,
+            datasetId,
+            hideBlanks,
+            manifest_synapse_table_id,
+            annotation_keys,
+        )
         # Load manifest to synapse as a CSV File
-        manifest_synapse_file_id = self.upload_manifest_file(manifest, metadataManifestPath, datasetId, restrict, component_name = component_name)
-        
+        manifest_synapse_file_id = self.upload_manifest_file(
+            manifest,
+            metadataManifestPath,
+            datasetId,
+            restrict,
+            component_name=component_name,
+        )
+
         # Set annotations for the file manifest.
-        manifest_annotations = self.format_manifest_annotations(manifest, manifest_synapse_file_id)
+        manifest_annotations = self.format_manifest_annotations(
+            manifest, manifest_synapse_file_id
+        )
         self.syn.set_annotations(manifest_annotations)
         logger.info("Associated manifest file with dataset on Synapse.")
-        
+
         # Update manifest Synapse table with new entity id column.
         manifest_synapse_table_id, manifest, table_manifest = self.uploadDB(
-                                                    dmge=dmge,
-                                                    manifest=manifest, 
-                                                    datasetId=datasetId, 
-                                                    table_name=table_name,  
-                                                    restrict=restrict,
-                                                    useSchemaLabel=useSchemaLabel,
-                                                    table_manipulation='update')
+            dmge=dmge,
+            manifest=manifest,
+            datasetId=datasetId,
+            table_name=table_name,
+            restrict=restrict,
+            table_manipulation="update",
+            table_column_names=table_column_names,
+        )
 
         # Set annotations for the table manifest
-        manifest_annotations = self.format_manifest_annotations(manifest, manifest_synapse_table_id)
+        manifest_annotations = self.format_manifest_annotations(
+            manifest, manifest_synapse_table_id
+        )
         self.syn.set_annotations(manifest_annotations)
         return manifest_synapse_file_id
 
     def upload_manifest_as_csv(
-                            self,
-                            dmge,
-                            manifest,
-                            metadataManifestPath,
-                            datasetId,
-                            restrict,
-                            manifest_record_type,
-                            hideBlanks,
-                            component_name):
+        self,
+        dmge,
+        manifest,
+        metadataManifestPath,
+        datasetId,
+        restrict,
+        manifest_record_type,
+        hideBlanks,
+        component_name,
+        annotation_keys: str,
+    ):
         """Upload manifest to Synapse as a csv only.
         Args:
             dmge: DataModelGraphExplorer object
@@ -1567,40 +1803,55 @@ def upload_manifest_as_csv(
             restrict (bool): Flag for censored data.
             manifest_record_type: valid values are 'entity', 'table' or 'both'. Specifies whether to create entity ids and folders for each row in a manifest, a Synapse table to house the entire manifest or do both.
             hideBlanks (bool): Default is False -Boolean flag that does not upload annotation keys with blank values when true. Uploads Annotation keys with empty string values when false.
-            table_malnipulation (str): Specify the way the manifest tables should be store as on Synapse when one with the same name already exists. Options are 'replace' and 'upsert'.
-            with_entities (bool): Default is False - Flag to indicate whether to create entityIds and add annotations.
+            annotation_keys: (str) display_label/class_label (default), Sets labeling syle for annotation keys. class_label will format the display
+                name as upper camelcase, and strip blacklisted characters, display_label will strip blacklisted characters including spaces, to retain
+                display label formatting while ensuring the label is formatted properly for Synapse annotations.
         Return:
             manifest_synapse_file_id (str): SynID of manifest csv uploaded to synapse.
         """
-
-        manifest = self.add_annotations_to_entities_files(dmge, manifest, manifest_record_type, datasetId, hideBlanks)
+        manifest = self.add_annotations_to_entities_files(
+            dmge,
+            manifest,
+            manifest_record_type,
+            datasetId,
+            hideBlanks,
+            annotation_keys=annotation_keys,
+        )
 
         # Load manifest to synapse as a CSV File
-        manifest_synapse_file_id = self.upload_manifest_file(manifest,
-                metadataManifestPath, datasetId, restrict, component_name = component_name)
-        
+        manifest_synapse_file_id = self.upload_manifest_file(
+            manifest,
+            metadataManifestPath,
+            datasetId,
+            restrict,
+            component_name=component_name,
+        )
+
         # Set annotations for the file manifest.
-        manifest_annotations = self.format_manifest_annotations(manifest, manifest_synapse_file_id)
+        manifest_annotations = self.format_manifest_annotations(
+            manifest, manifest_synapse_file_id
+        )
         self.syn.set_annotations(manifest_annotations)
 
         logger.info("Associated manifest file with dataset on Synapse.")
-        
+
         return manifest_synapse_file_id
 
     def upload_manifest_combo(
-                            self,
-                            dmge,
-                            manifest,
-                            metadataManifestPath,
-                            datasetId,
-                            table_name,
-                            component_name,
-                            restrict,
-                            manifest_record_type,
-                            useSchemaLabel,
-                            hideBlanks,
-                            table_manipulation,
-                            ):
+        self,
+        dmge,
+        manifest,
+        metadataManifestPath,
+        datasetId,
+        table_name,
+        component_name,
+        restrict,
+        manifest_record_type,
+        hideBlanks,
+        table_manipulation,
+        table_column_names: str,
+        annotation_keys: str,
+    ):
         """Upload manifest to Synapse as a table and CSV with entities.
         Args:
             dmge: DataModelGraphExplorer object
@@ -1611,53 +1862,82 @@ def upload_manifest_combo(
             component_name (str): Name of the component manifest that is currently being uploaded.
             restrict (bool): Flag for censored data.
             manifest_record_type: valid values are 'entity', 'table' or 'both'. Specifies whether to create entity ids and folders for each row in a manifest, a Synapse table to house the entire manifest or do both.
-            useSchemaLabel (bool): Default is True - use the schema label. If False, uses the display label from the schema. Attribute display names in the schema must not only include characters that are not accepted by Synapse. Annotation names may only contain: letters, numbers, '_' and '.'.
             hideBlanks (bool): Default is False -Boolean flag that does not upload annotation keys with blank values when true. Uploads Annotation keys with empty string values when false.
             table_malnipulation (str): Specify the way the manifest tables should be store as on Synapse when one with the same name already exists. Options are 'replace' and 'upsert'.
+            table_column_names: (str): display_name/display_label/class_label (default). Sets labeling style for table column names. display_name will use the raw display name as the column name. class_label will format the display
+                name as upper camelcase, and strip blacklisted characters, display_label will strip blacklisted characters including spaces, to retain
+                display label formatting.
+            annotation_keys: (str) display_label/class_label (default), Sets labeling syle for annotation keys. class_label will format the display
+                name as upper camelcase, and strip blacklisted characters, display_label will strip blacklisted characters including spaces, to retain
+                display label formatting while ensuring the label is formatted properly for Synapse annotations.
         Return:
             manifest_synapse_file_id (str): SynID of manifest csv uploaded to synapse.
         """
         manifest_synapse_table_id, manifest, table_manifest = self.uploadDB(
-                                                    dmge=dmge,
-                                                    manifest=manifest,
-                                                    datasetId=datasetId,
-                                                    table_name=table_name,
-                                                    restrict=restrict,
-                                                    useSchemaLabel=useSchemaLabel,
-                                                    table_manipulation=table_manipulation)
-
-        manifest = self.add_annotations_to_entities_files(dmge, manifest, manifest_record_type, datasetId, hideBlanks, manifest_synapse_table_id)
-        
+            dmge=dmge,
+            manifest=manifest,
+            datasetId=datasetId,
+            table_name=table_name,
+            restrict=restrict,
+            table_manipulation=table_manipulation,
+            table_column_names=table_column_names,
+        )
+
+        manifest = self.add_annotations_to_entities_files(
+            dmge,
+            manifest,
+            manifest_record_type,
+            datasetId,
+            hideBlanks,
+            manifest_synapse_table_id,
+            annotation_keys=annotation_keys,
+        )
+
         # Load manifest to synapse as a CSV File
-        manifest_synapse_file_id = self.upload_manifest_file(manifest, metadataManifestPath, datasetId, restrict, component_name)
-        
+        manifest_synapse_file_id = self.upload_manifest_file(
+            manifest, metadataManifestPath, datasetId, restrict, component_name
+        )
+
         # Set annotations for the file manifest.
-        manifest_annotations = self.format_manifest_annotations(manifest, manifest_synapse_file_id)
+        manifest_annotations = self.format_manifest_annotations(
+            manifest, manifest_synapse_file_id
+        )
         self.syn.set_annotations(manifest_annotations)
         logger.info("Associated manifest file with dataset on Synapse.")
-        
+
         # Update manifest Synapse table with new entity id column.
         manifest_synapse_table_id, manifest, table_manifest = self.uploadDB(
-                                                                dmge=dmge,
-                                                                manifest=manifest,
-                                                                datasetId=datasetId,
-                                                                table_name=table_name,
-                                                                restrict=restrict,
-                                                                useSchemaLabel=useSchemaLabel,
-                                                                table_manipulation='update')
+            dmge=dmge,
+            manifest=manifest,
+            datasetId=datasetId,
+            table_name=table_name,
+            restrict=restrict,
+            table_manipulation="update",
+            table_column_names=table_column_names,
+        )
 
         # Set annotations for the table manifest
-        manifest_annotations = self.format_manifest_annotations(manifest, manifest_synapse_table_id)
+        manifest_annotations = self.format_manifest_annotations(
+            manifest, manifest_synapse_table_id
+        )
         self.syn.set_annotations(manifest_annotations)
         return manifest_synapse_file_id
 
     def associateMetadataWithFiles(
-        self, dmge: DataModelGraphExplorer, metadataManifestPath: str, datasetId: str, manifest_record_type: str = 'table_file_and_entities', 
-        useSchemaLabel: bool = True, hideBlanks: bool = False, restrict_manifest = False, table_manipulation: str = 'replace',
+        self,
+        dmge: DataModelGraphExplorer,
+        metadataManifestPath: str,
+        datasetId: str,
+        manifest_record_type: str = "table_file_and_entities",
+        hideBlanks: bool = False,
+        restrict_manifest=False,
+        table_manipulation: str = "replace",
+        table_column_names: str = "class_label",
+        annotation_keys: str = "class_label",
     ) -> str:
         """Associate metadata with files in a storage dataset already on Synapse.
         Upload metadataManifest in the storage dataset folder on Synapse as well. Return synapseId of the uploaded manifest file.
-        
+
         If this is a new manifest there could be no Synapse entities associated with the rows of this manifest
         this may be due to data type (e.g. clinical data) being tabular
         and not requiring files; to utilize uniform interfaces downstream
@@ -1674,10 +1954,15 @@ def associateMetadataWithFiles(
             In this case, the system creates a file on Synapse for each row in the table (e.g. patient, biospecimen) and associates the columnset data as metadata/annotations to his file.
             datasetId: synapse ID of folder containing the dataset
             manifest_record_type: Default value is 'table_file_and_entities'. valid values are 'file_only', 'file_and_entities', 'table_and_file' or 'table_file_and_entities'. 'file_and_entities' will store the manifest as a csv and create Synapse files for each row in the manifest.'table_and_file' will store the manifest as a table and a csv on Synapse. 'file_only' will store the manifest as a csv only on Synapse. 'table_file_and_entities' will perform the options file_with_entites and table in combination.
-            useSchemaLabel: Default is True - use the schema label. If False, uses the display label from the schema. Attribute display names in the schema must not only include characters that are not accepted by Synapse. Annotation names may only contain: letters, numbers, '_' and '.'.
             hideBlanks: Default is false. Boolean flag that does not upload annotation keys with blank values when true. Uploads Annotation keys with empty string values when false.
             restrict_manifest (bool): Default is false. Flag for censored data.
             table_malnipulation (str): Default is 'replace'. Specify the way the manifest tables should be store as on Synapse when one with the same name already exists. Options are 'replace' and 'upsert'.
+            table_column_names: (str): display_name/display_label/class_label (default). Sets labeling style for table column names. display_name will use the raw display name as the column name. class_label will format the display
+                name as upper camelcase, and strip blacklisted characters, display_label will strip blacklisted characters including spaces, to retain
+                display label formatting.
+            annotation_keys: (str) display_label/class_label (default), Sets labeling syle for annotation keys. class_label will format the display
+                name as upper camelcase, and strip blacklisted characters, display_label will strip blacklisted characters including spaces, to retain
+                display label formatting while ensuring the label is formatted properly for Synapse annotations.
         Returns:
             manifest_synapse_file_id: SynID of manifest csv uploaded to synapse.
         """
@@ -1688,62 +1973,66 @@ def associateMetadataWithFiles(
         table_name, component_name = self._generate_table_name(manifest)
 
         # Upload manifest to synapse based on user input (manifest_record_type)
-        
+
         if manifest_record_type == "file_only":
             manifest_synapse_file_id = self.upload_manifest_as_csv(
-                                        dmge,
-                                        manifest,
-                                        metadataManifestPath,
-                                        datasetId=datasetId,
-                                        restrict=restrict_manifest,
-                                        hideBlanks=hideBlanks,
-                                        manifest_record_type=manifest_record_type,
-                                        component_name = component_name,
-                                        )
+                dmge,
+                manifest,
+                metadataManifestPath,
+                datasetId=datasetId,
+                restrict=restrict_manifest,
+                hideBlanks=hideBlanks,
+                manifest_record_type=manifest_record_type,
+                component_name=component_name,
+                annotation_keys=annotation_keys,
+            )
         elif manifest_record_type == "table_and_file":
             manifest_synapse_file_id = self.upload_manifest_as_table(
-                                        dmge,
-                                        manifest,
-                                        metadataManifestPath,
-                                        datasetId=datasetId,
-                                        table_name=table_name,
-                                        component_name=component_name,
-                                        restrict=restrict_manifest,
-                                        useSchemaLabel=useSchemaLabel,
-                                        hideBlanks=hideBlanks,
-                                        manifest_record_type=manifest_record_type,
-                                        table_manipulation=table_manipulation,
-                                        )
+                dmge,
+                manifest,
+                metadataManifestPath,
+                datasetId=datasetId,
+                table_name=table_name,
+                component_name=component_name,
+                restrict=restrict_manifest,
+                hideBlanks=hideBlanks,
+                manifest_record_type=manifest_record_type,
+                table_manipulation=table_manipulation,
+                table_column_names=table_column_names,
+                annotation_keys=annotation_keys,
+            )
         elif manifest_record_type == "file_and_entities":
-            manifest_synapse_file_id = self.upload_manifest_as_csv( 
-                                        dmge,
-                                        manifest,
-                                        metadataManifestPath,
-                                        datasetId=datasetId,
-                                        restrict=restrict_manifest,
-                                        hideBlanks=hideBlanks,
-                                        manifest_record_type=manifest_record_type,
-                                        component_name = component_name,
-                                        )
+            manifest_synapse_file_id = self.upload_manifest_as_csv(
+                dmge,
+                manifest,
+                metadataManifestPath,
+                datasetId=datasetId,
+                restrict=restrict_manifest,
+                hideBlanks=hideBlanks,
+                manifest_record_type=manifest_record_type,
+                component_name=component_name,
+                annotation_keys=annotation_keys,
+            )
         elif manifest_record_type == "table_file_and_entities":
             manifest_synapse_file_id = self.upload_manifest_combo(
-                                        dmge,
-                                        manifest,
-                                        metadataManifestPath,
-                                        datasetId=datasetId,
-                                        table_name=table_name,
-                                        component_name=component_name,
-                                        restrict=restrict_manifest,
-                                        useSchemaLabel=useSchemaLabel,
-                                        hideBlanks=hideBlanks,
-                                        manifest_record_type=manifest_record_type,
-                                        table_manipulation=table_manipulation,
-                                        )
+                dmge,
+                manifest,
+                metadataManifestPath,
+                datasetId=datasetId,
+                table_name=table_name,
+                component_name=component_name,
+                restrict=restrict_manifest,
+                hideBlanks=hideBlanks,
+                manifest_record_type=manifest_record_type,
+                table_manipulation=table_manipulation,
+                table_column_names=table_column_names,
+                annotation_keys=annotation_keys,
+            )
         else:
             raise ValueError("Please enter a valid manifest_record_type.")
         return manifest_synapse_file_id
 
-    def getTableAnnotations(self, table_id:str):
+    def getTableAnnotations(self, table_id: str):
         """Generate dictionary of annotations for the given Synapse file.
         Synapse returns all custom annotations as lists since they
         can contain multiple values. In all cases, the values will
@@ -1881,7 +2170,7 @@ def getDatasetAnnotations(
         # Add filenames for the files that "survived" annotation retrieval
         filenames = [dataset_files_map[i] for i in table["entityId"]]
 
-        if 'Filename' not in table.columns:
+        if "Filename" not in table.columns:
             table.insert(0, "Filename", filenames)
 
         # Ensure that entityId and eTag are at the end
@@ -1904,17 +2193,21 @@ def checkIfinAssetView(self, syn_id) -> str:
         # get data in administrative fileview for this pipeline
         assetViewTable = self.getStorageFileviewTable()
         all_files = list(assetViewTable["id"])
-        if syn_id in all_files: 
+        if syn_id in all_files:
             return True
-        else: 
+        else:
             return False
 
-    @retry(stop = stop_after_attempt(5), 
-            wait = wait_chain(*[wait_fixed(10) for i in range (2)] + 
-                    [wait_fixed(15) for i in range(2)] + 
-                    [wait_fixed(20)]),
-            retry=retry_if_exception_type(LookupError),
-            retry_error_callback = raise_final_error)
+    @retry(
+        stop=stop_after_attempt(5),
+        wait=wait_chain(
+            *[wait_fixed(10) for i in range(2)]
+            + [wait_fixed(15) for i in range(2)]
+            + [wait_fixed(20)]
+        ),
+        retry=retry_if_exception_type(LookupError),
+        retry_error_callback=raise_final_error,
+    )
     def getDatasetProject(self, datasetId: str) -> str:
         """Get parent project for a given dataset ID.
 
@@ -1941,7 +2234,6 @@ def getDatasetProject(self, datasetId: str) -> str:
             dataset_index = self.storageFileviewTable["id"] == datasetId
             dataset_row = self.storageFileviewTable[dataset_index]
 
-
         # Return `projectId` for given row if only one found
         if len(dataset_row) == 1:
             dataset_project = dataset_row["projectId"].values[0]
@@ -1959,11 +2251,11 @@ def getDatasetProject(self, datasetId: str) -> str:
             )
 
         # If not, then assume dataset not in file view
-        raise LookupError (
+        raise LookupError(
             f"The given dataset ({datasetId}) doesn't appear in the "
             f"configured file view ({self.storageFileview}). This might "
             "mean that the file view's scope needs to be updated."
-        )     
+        )
 
     def getDatasetAnnotationsBatch(
         self, datasetId: str, dataset_file_ids: Sequence[str] = None
@@ -1994,21 +2286,20 @@ def getDatasetAnnotationsBatch(
         return table
 
     def _get_table_schema_by_cname(self, table_schema):
-
         # assume no duplicate column names in the table
         table_schema_by_cname = {}
 
         for col_record in table_schema:
-
-            #TODO clean up dictionary for compactness (e.g. remove redundant 'name' key)
+            # TODO clean up dictionary for compactness (e.g. remove redundant 'name' key)
             table_schema_by_cname[col_record["name"]] = col_record
 
         return table_schema_by_cname
 
+
 class TableOperations:
     """
     Object to hold functions for various table operations specific to the Synapse Asset Store.
-    
+
     Currently implement operations are:
     createTable: upload a manifest as a new table when none exist
     replaceTable: replace a metadata in a table from one manifest with metadata from another manifest
@@ -2017,15 +2308,16 @@ class TableOperations:
     Operations currently in development are:
     upsertTable: add metadata from a manifest to an existing table that contains metadata from another manifest
     """
-    def __init__(self, 
-                 synStore: SynapseStorage, 
-                 tableToLoad: pd.DataFrame = None, 
-                 tableName: str = None, 
-                 datasetId: str = None, 
-                 existingTableId: str = None,
-                 restrict: bool = False
-                 ):
-        
+
+    def __init__(
+        self,
+        synStore: SynapseStorage,
+        tableToLoad: pd.DataFrame = None,
+        tableName: str = None,
+        datasetId: str = None,
+        existingTableId: str = None,
+        restrict: bool = False,
+    ):
         """
         Class governing table operations (creation, replacement, upserts, updates) in schematic
 
@@ -2033,7 +2325,7 @@ def __init__(self,
         tableName: name of the table to be uploaded
         datasetId: synID of the dataset for the manifest
         existingTableId: synId of the table currently exising on synapse (if there is one)
-        restrict: bool, whether or not the manifest contains sensitive data that will need additional access restrictions 
+        restrict: bool, whether or not the manifest contains sensitive data that will need additional access restrictions
 
         """
         self.synStore = synStore
@@ -2043,78 +2335,100 @@ def __init__(self,
         self.existingTableId = existingTableId
         self.restrict = restrict
 
-
-    def createTable(self, columnTypeDict: dict = None, specifySchema: bool = True,):
+    def createTable(
+        self,
+        columnTypeDict: dict = None,
+        specifySchema: bool = True,
+    ):
         """
         Method to create a table from a metadata manifest and upload it to synapse
-        
+
         Args:
             columnTypeDict: dictionary schema for table columns: type, size, etc
-            specifySchema: to specify a specific schema for the table format                      
+            specifySchema: to specify a specific schema for the table format
 
         Returns:
             table.schema.id: synID of the newly created table
         """
 
-        datasetEntity = self.synStore.syn.get(self.datasetId, downloadFile = False)
+        datasetEntity = self.synStore.syn.get(self.datasetId, downloadFile=False)
         datasetName = datasetEntity.name
-        table_schema_by_cname = self.synStore._get_table_schema_by_cname(columnTypeDict) 
+        table_schema_by_cname = self.synStore._get_table_schema_by_cname(columnTypeDict)
 
         if not self.tableName:
-            self.tableName = datasetName + 'table'
+            self.tableName = datasetName + "table"
         datasetParentProject = self.synStore.getDatasetProject(self.datasetId)
         if specifySchema:
             if columnTypeDict == {}:
                 logger.error("Did not provide a columnTypeDict.")
-            #create list of columns:
+            # create list of columns:
             cols = []
             for col in self.tableToLoad.columns:
                 if col in table_schema_by_cname:
-                    col_type = table_schema_by_cname[col]['columnType']
-                    max_size = table_schema_by_cname[col]['maximumSize'] if 'maximumSize' in table_schema_by_cname[col].keys() else 100
+                    col_type = table_schema_by_cname[col]["columnType"]
+                    max_size = (
+                        table_schema_by_cname[col]["maximumSize"]
+                        if "maximumSize" in table_schema_by_cname[col].keys()
+                        else 100
+                    )
                     max_list_len = 250
                     if max_size and max_list_len:
-                        cols.append(Column(name=col, columnType=col_type, 
-                            maximumSize=max_size, maximumListLength=max_list_len))
+                        cols.append(
+                            Column(
+                                name=col,
+                                columnType=col_type,
+                                maximumSize=max_size,
+                                maximumListLength=max_list_len,
+                            )
+                        )
                     elif max_size:
-                        cols.append(Column(name=col, columnType=col_type, 
-                            maximumSize=max_size))
+                        cols.append(
+                            Column(name=col, columnType=col_type, maximumSize=max_size)
+                        )
                     else:
                         cols.append(Column(name=col, columnType=col_type))
                 else:
-                    #TODO add warning that the given col was not found and it's max size is set to 100
-                    cols.append(Column(name=col, columnType='STRING', maximumSize=100))
-            schema = Schema(name=self.tableName, columns=cols, parent=datasetParentProject)
+                    # TODO add warning that the given col was not found and it's max size is set to 100
+                    cols.append(Column(name=col, columnType="STRING", maximumSize=100))
+            schema = Schema(
+                name=self.tableName, columns=cols, parent=datasetParentProject
+            )
             table = Table(schema, self.tableToLoad)
-            table = self.synStore.syn.store(table, isRestricted = self.restrict)
+            table = self.synStore.syn.store(table, isRestricted=self.restrict)
             return table.schema.id
         else:
             # For just uploading the tables to synapse using default
             # column types.
             table = build_table(self.tableName, datasetParentProject, self.tableToLoad)
-            table = self.synStore.syn.store(table, isRestricted = self.restrict)
+            table = self.synStore.syn.store(table, isRestricted=self.restrict)
             return table.schema.id
 
-    def replaceTable(self, specifySchema: bool = True, columnTypeDict: dict = None,):
+    def replaceTable(
+        self,
+        specifySchema: bool = True,
+        columnTypeDict: dict = None,
+    ):
         """
         Method to replace an existing table on synapse with metadata from a new manifest
-        
+
         Args:
-            specifySchema: to infer a schema for the table format      
-            columnTypeDict: dictionary schema for table columns: type, size, etc            
+            specifySchema: to infer a schema for the table format
+            columnTypeDict: dictionary schema for table columns: type, size, etc
 
         Returns:
            existingTableId: synID of the already existing table that had its metadata replaced
         """
-        datasetEntity = self.synStore.syn.get(self.datasetId, downloadFile = False)
+        datasetEntity = self.synStore.syn.get(self.datasetId, downloadFile=False)
         datasetName = datasetEntity.name
-        table_schema_by_cname = self.synStore._get_table_schema_by_cname(columnTypeDict) 
-        existing_table, existing_results = self.synStore.get_synapse_table(self.existingTableId)
+        table_schema_by_cname = self.synStore._get_table_schema_by_cname(columnTypeDict)
+        existing_table, existing_results = self.synStore.get_synapse_table(
+            self.existingTableId
+        )
         # remove rows
         self.synStore.syn.delete(existing_results)
         # wait for row deletion to finish on synapse before getting empty table
         sleep(10)
-        
+
         # removes all current columns
         current_table = self.synStore.syn.get(self.existingTableId)
         current_columns = self.synStore.syn.getTableColumns(current_table)
@@ -2122,58 +2436,70 @@ def replaceTable(self, specifySchema: bool = True, columnTypeDict: dict = None,)
             current_table.removeColumn(col)
 
         if not self.tableName:
-            self.tableName = datasetName + 'table'
-        
+            self.tableName = datasetName + "table"
+
         # Process columns according to manifest entries
-        table_schema_by_cname = self.synStore._get_table_schema_by_cname(columnTypeDict) 
+        table_schema_by_cname = self.synStore._get_table_schema_by_cname(columnTypeDict)
         datasetParentProject = self.synStore.getDatasetProject(self.datasetId)
         if specifySchema:
             if columnTypeDict == {}:
                 logger.error("Did not provide a columnTypeDict.")
-            #create list of columns:
+            # create list of columns:
             cols = []
-            
+
             for col in self.tableToLoad.columns:
-                
                 if col in table_schema_by_cname:
-                    col_type = table_schema_by_cname[col]['columnType']
-                    max_size = table_schema_by_cname[col]['maximumSize'] if 'maximumSize' in table_schema_by_cname[col].keys() else 100
+                    col_type = table_schema_by_cname[col]["columnType"]
+                    max_size = (
+                        table_schema_by_cname[col]["maximumSize"]
+                        if "maximumSize" in table_schema_by_cname[col].keys()
+                        else 100
+                    )
                     max_list_len = 250
                     if max_size and max_list_len:
-                        cols.append(Column(name=col, columnType=col_type, 
-                            maximumSize=max_size, maximumListLength=max_list_len))
+                        cols.append(
+                            Column(
+                                name=col,
+                                columnType=col_type,
+                                maximumSize=max_size,
+                                maximumListLength=max_list_len,
+                            )
+                        )
                     elif max_size:
-                        cols.append(Column(name=col, columnType=col_type, 
-                            maximumSize=max_size))
+                        cols.append(
+                            Column(name=col, columnType=col_type, maximumSize=max_size)
+                        )
                     else:
                         cols.append(Column(name=col, columnType=col_type))
                 else:
-                    
-                    #TODO add warning that the given col was not found and it's max size is set to 100
-                    cols.append(Column(name=col, columnType='STRING', maximumSize=100))
-            
+                    # TODO add warning that the given col was not found and it's max size is set to 100
+                    cols.append(Column(name=col, columnType="STRING", maximumSize=100))
+
             # adds new columns to schema
             for col in cols:
                 current_table.addColumn(col)
-            self.synStore.syn.store(current_table, isRestricted = self.restrict)
+            self.synStore.syn.store(current_table, isRestricted=self.restrict)
 
             # wait for synapse store to finish
             sleep(1)
 
             # build schema and table from columns and store with necessary restrictions
-            schema = Schema(name=self.tableName, columns=cols, parent=datasetParentProject)
+            schema = Schema(
+                name=self.tableName, columns=cols, parent=datasetParentProject
+            )
             schema.id = self.existingTableId
-            table = Table(schema, self.tableToLoad, etag = existing_results.etag)
-            table = self.synStore.syn.store(table, isRestricted = self.restrict)
+            table = Table(schema, self.tableToLoad, etag=existing_results.etag)
+            table = self.synStore.syn.store(table, isRestricted=self.restrict)
         else:
             logging.error("Must specify a schema for table replacements")
 
         # remove system metadata from manifest
-        existing_table.drop(columns = ['ROW_ID', 'ROW_VERSION'], inplace = True)
+        existing_table.drop(columns=["ROW_ID", "ROW_VERSION"], inplace=True)
         return self.existingTableId
-    
 
-    def _get_auth_token(self,):
+    def _get_auth_token(
+        self,
+    ):
         authtoken = None
 
         # Get access token from environment variable if available
@@ -2185,14 +2511,16 @@ def _get_auth_token(self,):
 
         # Get token from authorization header
         # Primarily useful for API endpoint functionality
-        if 'Authorization' in self.synStore.syn.default_headers:
-            authtoken = self.synStore.syn.default_headers['Authorization'].split('Bearer ')[-1]
+        if "Authorization" in self.synStore.syn.default_headers:
+            authtoken = self.synStore.syn.default_headers["Authorization"].split(
+                "Bearer "
+            )[-1]
             return authtoken
 
         # retrive credentials from synapse object
         # Primarily useful for local users, could only be stored here when a .synapseConfig file is used, but including to be safe
         synapse_object_creds = self.synStore.syn.credentials
-        if hasattr(synapse_object_creds, '_token'):
+        if hasattr(synapse_object_creds, "_token"):
             authtoken = synapse_object_creds.secret
 
         # Try getting creds from .synapseConfig file if it exists
@@ -2201,51 +2529,61 @@ def _get_auth_token(self,):
             config = self.synStore.syn.getConfigFile(CONFIG.synapse_configuration_path)
 
             # check which credentials are provided in file
-            if config.has_option('authentication', 'authtoken'):
-                authtoken = config.get('authentication', 'authtoken')
-        
+            if config.has_option("authentication", "authtoken"):
+                authtoken = config.get("authentication", "authtoken")
+
         # raise error if required credentials are not found
         if not authtoken:
             raise NameError(
                 "authtoken credentials could not be found in the environment, synapse object, or the .synapseConfig file"
             )
-        
+
         return authtoken
 
     def upsertTable(self, dmge: DataModelGraphExplorer):
         """
         Method to upsert rows from a new manifest into an existing table on synapse
-        For upsert functionality to work, primary keys must follow the naming convention of <componenet>_id        
+        For upsert functionality to work, primary keys must follow the naming convention of <componenet>_id
         `-tm upsert` should be used for initial table uploads if users intend to upsert into them at a later time; using 'upsert' at creation will generate the metadata necessary for upsert functionality.
         Currently it is required to use -dl/--use_display_label with table upserts.
-        
+
 
         Args:
             dmge: DataModelGraphExplorer instance
-            
+
         Returns:
            existingTableId: synID of the already existing table that had its metadata replaced
-        """            
+        """
 
         authtoken = self._get_auth_token()
 
-        synapseDB = SynapseDatabase(auth_token=authtoken, project_id=self.synStore.getDatasetProject(self.datasetId))
+        synapseDB = SynapseDatabase(
+            auth_token=authtoken,
+            project_id=self.synStore.getDatasetProject(self.datasetId),
+        )
 
         try:
             # Try performing upsert
-            synapseDB.upsert_table_rows(table_name=self.tableName, data=self.tableToLoad)
-        except(SynapseHTTPError) as ex:
+            synapseDB.upsert_table_rows(
+                table_name=self.tableName, data=self.tableToLoad
+            )
+        except SynapseHTTPError as ex:
             # If error is raised because Table has old `Uuid` column and not new `Id` column, then handle and re-attempt upload
-            if 'Id is not a valid column name or id' in str(ex):
+            if "Id is not a valid column name or id" in str(ex):
                 self._update_table_uuid_column(dmge)
-                synapseDB.upsert_table_rows(table_name=self.tableName, data=self.tableToLoad)
+                synapseDB.upsert_table_rows(
+                    table_name=self.tableName, data=self.tableToLoad
+                )
             # Raise if other error
             else:
                 raise ex
 
         return self.existingTableId
-    
-    def _update_table_uuid_column(self, dmge: DataModelGraphExplorer,) -> None:
+
+    def _update_table_uuid_column(
+        self,
+        dmge: DataModelGraphExplorer,
+    ) -> None:
         """Removes the `Uuid` column when present, and relpaces with an `Id` column
         Used to enable backwards compatability for manifests using the old `Uuid` convention
 
@@ -2259,61 +2597,77 @@ def _update_table_uuid_column(self, dmge: DataModelGraphExplorer,) -> None:
         # Get the columns of the schema
         schema = self.synStore.syn.get(self.existingTableId)
         cols = self.synStore.syn.getTableColumns(schema)
-        
+
         # Iterate through columns until `Uuid` column is found
         for col in cols:
-            if col.name.lower() == 'uuid':
+            if col.name.lower() == "uuid":
                 # See if schema has `Uuid` column specified
                 try:
-                    uuid_col_in_schema = dmge.is_class_in_schema(col.name)      
-                except (KeyError):
+                    uuid_col_in_schema = dmge.is_class_in_schema(col.name)
+                except KeyError:
                     uuid_col_in_schema = False
 
                 # If there is, then create a new `Id` column from scratch
                 if uuid_col_in_schema:
-                    new_col = Column(columnType = "STRING", maximumSize = 64, name = "Id")
+                    new_col = Column(columnType="STRING", maximumSize=64, name="Id")
                     schema.addColumn(new_col)
                     schema = self.synStore.syn.store(schema)
                 # If there is not, then use the old `Uuid` column as a basis for the new `Id` column
                 else:
-                    
                     # Build ColumnModel that will be used for new column
-                    id_column = Column(name='Id', columnType='STRING', maximumSize=64, defaultValue=None, maximumListLength=1)
+                    id_column = Column(
+                        name="Id",
+                        columnType="STRING",
+                        maximumSize=64,
+                        defaultValue=None,
+                        maximumListLength=1,
+                    )
                     new_col_response = self.synStore.syn.store(id_column)
 
-
                     # Define columnChange body
                     columnChangeDict = {
                         "concreteType": "org.sagebionetworks.repo.model.table.TableSchemaChangeRequest",
                         "entityId": self.existingTableId,
                         "changes": [
-                            {                        
-                                "oldColumnId": col['id'],
-                                "newColumnId": new_col_response['id'],
+                            {
+                                "oldColumnId": col["id"],
+                                "newColumnId": new_col_response["id"],
                             }
-                        ]
+                        ],
                     }
 
-                    self.synStore.syn._async_table_update(table=self.existingTableId, changes=[columnChangeDict], wait=False)
+                    self.synStore.syn._async_table_update(
+                        table=self.existingTableId,
+                        changes=[columnChangeDict],
+                        wait=False,
+                    )
                 break
 
         return
 
-    def updateTable(self, update_col: str = 'Id',):
+    def updateTable(
+        self,
+        update_col: str = "Id",
+    ):
         """
         Method to update an existing table with a new column
-        
+
         Args:
-            updateCol: column to index the old and new tables on            
+            updateCol: column to index the old and new tables on
 
         Returns:
            existingTableId: synID of the already existing table that had its metadata replaced
         """
-        existing_table, existing_results = self.synStore.get_synapse_table(self.existingTableId)
-        
+        existing_table, existing_results = self.synStore.get_synapse_table(
+            self.existingTableId
+        )
+
         self.tableToLoad = update_df(existing_table, self.tableToLoad, update_col)
         # store table with existing etag data and impose restrictions as appropriate
-        self.synStore.syn.store(Table(self.existingTableId, self.tableToLoad, etag = existing_results.etag), isRestricted = self.restrict)
+        self.synStore.syn.store(
+            Table(self.existingTableId, self.tableToLoad, etag=existing_results.etag),
+            isRestricted=self.restrict,
+        )
 
         return self.existingTableId
 
diff --git a/schematic/utils/cli_utils.py b/schematic/utils/cli_utils.py
index c68fe46f6..52debd51c 100644
--- a/schematic/utils/cli_utils.py
+++ b/schematic/utils/cli_utils.py
@@ -1,17 +1,16 @@
-#!/usr/bin/env python3
+"""CLI utils"""
+
+# pylint: disable=logging-fstring-interpolation
+# pylint: disable=anomalous-backslash-in-string
 
-import inspect
 import logging
 
-from typing import Any, Mapping, Sequence, Union, List
+from typing import Any, Mapping, Sequence, Union, Optional
 from functools import reduce
 import re
 
 logger = logging.getLogger(__name__)
 
-# We are using fstrings in logger methods
-# pylint: disable=logging-fstring-interpolation
-
 
 def query_dict(dictionary: Mapping[Any, Any], keys: Sequence[Any]) -> Union[Any, None]:
     """Access a nested value in a dictionary corresponding
@@ -36,7 +35,7 @@ def extract(dictionary: Any, key: Any) -> Union[Any, None]:
     return reduce(extract, keys, dictionary)
 
 
-def log_value_from_config(arg_name: str, config_value: Any):
+def log_value_from_config(arg_name: str, config_value: Any) -> None:
     """Logs when getting a value from the config
 
     Args:
@@ -47,48 +46,57 @@ def log_value_from_config(arg_name: str, config_value: Any):
         f"The {arg_name} argument is being taken from configuration file, i.e., {config_value}."
     )
 
-def parse_synIDs(
-    ctx, param, synIDs,
-) -> List[str]:
-    """Parse and validate a comma separated string of synIDs
 
-    Args:
-        ctx:
-            click option context
-        param:
-            click option argument name
-        synIDs:
-            comma separated string of synIDs
+def parse_syn_ids(
+    ctx: Any,  # pylint: disable=unused-argument
+    param: str,  # pylint: disable=unused-argument
+    syn_ids: str,
+) -> Optional[list[str]]:
+    """Parse and validate a comma separated string of synapse ids
 
-    Returns:
-        List of synID strings
+    Args:
+        ctx (Any): click option context
+        param (str): click option argument name
+        syn_ids (str): comma separated string of synapse ids
 
     Raises:
-        ValueError: If the entire string does not match a regex for 
+        ValueError:  If the entire string does not match a regex for
             a valid comma separated string of SynIDs
+
+    Returns:
+        Optional[list[str]]:  List of synapse ids
     """
-    if synIDs:
-        project_regex = re.compile("(syn\d+\,?)+")
-        valid=project_regex.fullmatch(synIDs)
+    if not syn_ids:
+        return None
+
+    project_regex = re.compile("(syn\d+\,?)+")
+    valid = project_regex.fullmatch(syn_ids)
 
-        if valid:
-            synIDs = synIDs.split(",")
+    if not valid:
+        raise ValueError(
+            f"The provided list of project synID(s): {syn_ids}, is not formatted correctly. "
+            "\nPlease check your list of projects for errors."
+        )
 
-            return synIDs
+    return syn_ids.split(",")
 
-        else:
-            raise ValueError(
-                        f"The provided list of project synID(s): {synIDs}, is not formatted correctly. "
-                        "\nPlease check your list of projects for errors."
-                    )
-    else:
-        return
 
 def parse_comma_str_to_list(
-    ctx, param, comma_string,
-) -> List[str]:
+    ctx: Any,  # pylint: disable=unused-argument
+    param: str,  # pylint: disable=unused-argument
+    comma_string: str,
+) -> Optional[list[str]]:
+    """Separates a comma separated sting into a list of strings
+
+    Args:
+        ctx (Any): click option context
+        param (str): click option argument name
+        comma_string (str): comma separated string
+
+    Returns:
+        Optional[list[str]]: _description_
+    """
+    if not comma_string:
+        return None
 
-    if comma_string:
-        return comma_string.split(",")
-    else:
-        return None
\ No newline at end of file
+    return comma_string.split(",")
diff --git a/schematic/utils/curie_utils.py b/schematic/utils/curie_utils.py
index 42361b482..9345f2b87 100644
--- a/schematic/utils/curie_utils.py
+++ b/schematic/utils/curie_utils.py
@@ -1,20 +1,21 @@
+"""Curie utils"""
+
 import logging
 
 
 logger = logging.getLogger(__name__)
 
 
-def extract_name_from_uri_or_curie(item):
+def extract_name_from_uri_or_curie(item: str) -> str:
     """Extract name from uri or curie"""
     if "http" not in item and len(item.split(":")) == 2:
         return item.split(":")[-1]
-    elif len(item.split("//")[-1].split("/")) > 1:
+    if len(item.split("//")[-1].split("/")) > 1:
         return item.split("//")[-1].split("/")[-1]
-    else:
-        raise ValueError("Error extracting name from URI or Curie.")
+    raise ValueError("Error extracting name from URI or Curie.")
 
 
-def expand_curie_to_uri(curie, context_info):
+def expand_curie_to_uri(curie: str, context_info: dict[str, str]) -> str:
     """Expand curie to uri based on the context given
 
     parmas
@@ -24,17 +25,15 @@ def expand_curie_to_uri(curie, context_info):
     "http://schema.biothings.io/"})
     """
     # as suggested in SchemaOrg standard file, these prefixes don't expand
-    PREFIXES_NOT_EXPAND = ["rdf", "rdfs", "xsd"]
+    prefixes_not_expand = ["rdf", "rdfs", "xsd"]
     # determine if a value is curie
     if len(curie.split(":")) == 2:
         prefix, value = curie.split(":")
-        if prefix in context_info and prefix not in PREFIXES_NOT_EXPAND:
+        if prefix in context_info and prefix not in prefixes_not_expand:
             return context_info[prefix] + value
         # if the input is not curie, return the input unmodified
-        else:
-            return curie
-    else:
         return curie
+    return curie
 
 
 def expand_curies_in_schema(schema):
@@ -44,28 +43,28 @@ def expand_curies_in_schema(schema):
     new_schema = {"@context": context, "@graph": [], "@id": schema["@id"]}
     for record in graph:
         new_record = {}
-        for k, v in record.items():
-            if type(v) == str:
-                new_record[expand_curie_to_uri(k, context)] = expand_curie_to_uri(
-                    v, context
+        for key, value in record.items():
+            if isinstance(value, str):
+                new_record[expand_curie_to_uri(key, context)] = expand_curie_to_uri(
+                    value, context
                 )
-            elif type(v) == list:
-                if type(v[0]) == dict:
-                    new_record[expand_curie_to_uri(k, context)] = []
-                    for _item in v:
-                        new_record[expand_curie_to_uri(k, context)].append(
+            elif isinstance(value, list):
+                if isinstance(value[0], dict):
+                    new_record[expand_curie_to_uri(key, context)] = []
+                    for _item in value:
+                        new_record[expand_curie_to_uri(key, context)].append(
                             {"@id": expand_curie_to_uri(_item["@id"], context)}
                         )
                 else:
-                    new_record[expand_curie_to_uri(k, context)] = [
-                        expand_curie_to_uri(_item, context) for _item in v
+                    new_record[expand_curie_to_uri(key, context)] = [
+                        expand_curie_to_uri(_item, context) for _item in value
                     ]
-            elif type(v) == dict and "@id" in v:
-                new_record[expand_curie_to_uri(k, context)] = {
-                    "@id": expand_curie_to_uri(v["@id"], context)
+            elif isinstance(value, dict) and "@id" in value:
+                new_record[expand_curie_to_uri(key, context)] = {
+                    "@id": expand_curie_to_uri(value["@id"], context)
                 }
-            elif v == None:
-                new_record[expand_curie_to_uri(k, context)] = None
+            elif value is None:
+                new_record[expand_curie_to_uri(key, context)] = None
         new_schema["@graph"].append(new_record)
     return new_schema
 
diff --git a/schematic/utils/df_utils.py b/schematic/utils/df_utils.py
index 789fb4881..1bba83c7a 100644
--- a/schematic/utils/df_utils.py
+++ b/schematic/utils/df_utils.py
@@ -1,100 +1,167 @@
+"""df utils"""
+
+# pylint: disable=logging-fstring-interpolation
+
 import logging
 from copy import deepcopy
 from time import perf_counter
-import datetime as dt
+from typing import Union
+from datetime import datetime
 import dateparser as dp
 import pandas as pd
 import numpy as np
-from pandarallel import pandarallel
+from pandarallel import pandarallel  # type: ignore
 
 logger = logging.getLogger(__name__)
 
 
-def load_df(file_path, preserve_raw_input=True, data_model=False, **load_args):
+def load_df(
+    file_path: str,
+    preserve_raw_input: bool = True,
+    data_model: bool = False,
+    **load_args: dict,
+) -> pd.DataFrame:
     """
     Universal function to load CSVs and return DataFrames
     Parses string entries to convert as appropriate to type int, float, and pandas timestamp
-    Pandarallel is used for type inference for large manfiests to improve performance
+    Pandarallel is used for type inference for large manifests to improve performance
+
     Args:
-        file_path: path of csv to open
-        preserve_raw_input: Bool. If false, convert cell datatypes to an inferred type
-        data_model: bool, indicates if importing a data model
-        load_args: dict of key value pairs to be passed to the pd.read_csv function
-        **kwargs: keyword arguments for pd.read_csv()
+        file_path (str): path of csv to open
+        preserve_raw_input (bool, optional): If false, convert cell datatypes to an inferred type
+        data_model (bool, optional): bool, indicates if importing a data model
+        **load_args(dict): dict of key value pairs to be passed to the pd.read_csv function
 
-    Returns: a processed dataframe for manifests or unprocessed df for data models and where indicated
+    Raises:
+        ValueError: When pd.read_csv on the file path doesn't return as dataframe
+
+    Returns:
+        pd.DataFrame: a processed dataframe for manifests or unprocessed df for data models and
+      where indicated
     """
-    large_manifest_cutoff_size = 1000
     # start performance timer
     t_load_df = perf_counter()
-    
-    #Read CSV to df as type specified in kwargs
-    org_df = pd.read_csv(file_path, keep_default_na = True, encoding='utf8', **load_args)
-    
-    # If type inference not allowed: trim and return
+
+    # Read CSV to df as type specified in kwargs
+    org_df = pd.read_csv(  # type: ignore
+        file_path, keep_default_na=True, encoding="utf8", **load_args
+    )
+    if not isinstance(org_df, pd.DataFrame):
+        raise ValueError(
+            (
+                "Pandas did not return a dataframe. "
+                "Pandas will return a TextFileReader if chunksize parameter is used."
+            )
+        )
+
+    # only trim if not data model csv
+    if not data_model:
+        org_df = trim_commas_df(org_df)
+
     if preserve_raw_input:
-        #only trim if not data model csv
-        if not data_model:
-            org_df=trim_commas_df(org_df)
-        
-            # log manifest load and processing time
-            logger.debug(f"Load Elapsed time {perf_counter()-t_load_df}")
+        logger.debug(f"Load Elapsed time {perf_counter()-t_load_df}")
         return org_df
 
-    # If type inferences is allowed: infer types, trim, and return
-    else:
-        # create a separate copy of the manifest 
-        # before beginning conversions to store float values
-        float_df=deepcopy(org_df)
-        
-        # Cast the columns in the dataframe to string and
-        # replace Null values with empty strings
-        null_cells = org_df.isnull() 
-        org_df = org_df.astype(str).mask(null_cells, '')
-
-        # Find integers stored as strings and replace with entries of type np.int64
-        if org_df.size < large_manifest_cutoff_size:  # If small manifest, iterate as normal for improved performance
-            ints = org_df.applymap(lambda x: np.int64(x) if str.isdigit(x) else False, na_action='ignore').fillna(False)
-
-        else:   # parallelize iterations for large manfiests
-            pandarallel.initialize(verbose = 1)
-            ints = org_df.parallel_applymap(lambda x: np.int64(x) if str.isdigit(x) else False, na_action='ignore').fillna(False)
-
-        # Identify cells converted to intergers
-        ints_tf_df = ints.applymap(pd.api.types.is_integer)
-
-        # convert strings to numerical dtype (float) if possible, preserve non-numerical strings
-        for col in org_df.columns:
-            float_df[col]=pd.to_numeric(float_df[col], errors='coerce')
-            # replace values that couldn't be converted to float with the original str values
-            float_df[col].fillna(org_df[col][float_df[col].isna()],inplace=True)
-        
-        # Trim nans and empty rows and columns
-        processed_df = trim_commas_df(float_df)
-
-        # Store values that were converted to type int in the final dataframe
-        processed_df=processed_df.mask(ints_tf_df, other = ints)
-        
-        # log manifest load and processing time
-        logger.debug(f"Load Elapsed time {perf_counter()-t_load_df}")
-        return processed_df
+    is_null = org_df.isnull()
+    org_df = org_df.astype(str).mask(is_null, "")
+
+    ints, is_int = find_and_convert_ints(org_df)
+
+    float_df = convert_floats(org_df)
+
+    # Store values that were converted to type int in the final dataframe
+    processed_df = float_df.mask(is_int, other=ints)
+
+    logger.debug(f"Load Elapsed time {perf_counter()-t_load_df}")
+    return processed_df
+
+
+def find_and_convert_ints(dataframe: pd.DataFrame) -> tuple[pd.DataFrame, pd.DataFrame]:
+    """
+    Find strings that represent integers and convert to type int
+    Args:
+        dataframe: dataframe with nulls masked as empty strings
+    Returns:
+        ints: dataframe with values that were converted to type int
+        is_int: dataframe with boolean values indicating which cells were converted to type int
+
+    """
+    # pylint: disable=unnecessary-lambda
+    large_manifest_cutoff_size = 1000
+    # Find integers stored as strings and replace with entries of type np.int64
+    if (
+        dataframe.size < large_manifest_cutoff_size
+    ):  # If small manifest, iterate as normal for improved performance
+        ints = dataframe.map(
+            lambda cell: convert_ints(cell), na_action="ignore"
+        ).fillna(False)
+
+    else:  # parallelize iterations for large manifests
+        pandarallel.initialize(verbose=1)
+        ints = dataframe.parallel_applymap(
+            lambda cell: convert_ints(cell), na_action="ignore"
+        ).fillna(False)
 
+    # Identify cells converted to integers
+    is_int = ints.map(pd.api.types.is_integer)
 
-def _parse_dates(date_string):
+    return ints, is_int
+
+
+def convert_ints(string: str) -> Union[np.int64, bool]:
+    """
+    Lambda function to convert a string to an integer if possible, otherwise returns False
+    Args:
+        string: string to attempt conversion to int
+    Returns:
+        string converted to type int if possible, otherwise False
+    """
+    return np.int64(string) if str.isdigit(string) else False
+
+
+def convert_floats(dataframe: pd.DataFrame) -> pd.DataFrame:
+    """
+    Convert strings that represent floats to type float
+    Args:
+        dataframe: dataframe with nulls masked as empty strings
+    Returns:
+        float_df: dataframe with values that were converted to type float. Columns are type object
+    """
+    # create a separate copy of the manifest
+    # before beginning conversions to store float values
+    float_df = deepcopy(dataframe)
+
+    # convert strings to numerical dtype (float) if possible, preserve non-numerical strings
+    for col in dataframe.columns:
+        float_df[col] = pd.to_numeric(float_df[col], errors="coerce").astype("object")
+
+        # replace values that couldn't be converted to float with the original str values
+        float_df[col].fillna(dataframe[col][float_df[col].isna()], inplace=True)
+
+    return float_df
+
+
+def parse_dates(date_string: str) -> Union[datetime, bool]:
+    """Gets a datetime from a string
+
+    Args:
+        date_string (str): The string to get the datetime from
+
+    Returns:
+        Union[datetime, bool]: The parsed datetime or False
+    """
     try:
-        date = dp.parse(date_string = date_string, settings = {'STRICT_PARSING': True})
+        date = dp.parse(date_string=date_string, settings={"STRICT_PARSING": True})
         return date if date else False
     except TypeError:
         return False
 
 
-
-def normalize_table(df: pd.DataFrame, primary_key: str) -> pd.DataFrame:
-
+def normalize_table(dataframe: pd.DataFrame, primary_key: str) -> pd.DataFrame:
     """
     Function to normalize a table (e.g. dedup)
     Args:
-        df: data frame to normalize
+        dataframe: data frame to normalize
         primary_key: primary key on which to perform dedup
 
     Returns: a dedupped dataframe
@@ -102,9 +169,9 @@ def normalize_table(df: pd.DataFrame, primary_key: str) -> pd.DataFrame:
 
     try:
         # if valid primary key has been provided normalize df
-        df = df.reset_index()
-        df_norm = df.drop_duplicates(subset=[primary_key])
-        df_norm = df.drop(columns=["index"])
+        dataframe = dataframe.reset_index()
+        df_norm = dataframe.drop_duplicates(subset=[primary_key])
+        df_norm = dataframe.drop(columns=["index"])
         return df_norm
     except KeyError:
         # if the primary key is not in the df; then return the same df w/o changes
@@ -112,7 +179,7 @@ def normalize_table(df: pd.DataFrame, primary_key: str) -> pd.DataFrame:
             "Specified primary key is not in table schema. Proceeding without table changes."
         )
 
-        return df
+        return dataframe
 
 
 def update_df(
@@ -160,49 +227,54 @@ def update_df(
     input_df_idx.reset_index(inplace=True)
     input_df_idx = input_df_idx[input_df.columns]
 
-     # Sometimes pandas update can change the column datatype, recast
+    # Sometimes pandas update can change the column datatype, recast
     for col in input_df_idx.columns:
         input_df_idx[col] = input_df_idx[col].astype(input_df.dtypes[col])
 
     return input_df_idx
 
 
-def trim_commas_df(df: pd.DataFrame):
+def trim_commas_df(dataframe: pd.DataFrame) -> pd.DataFrame:
     """Removes empty (trailing) columns and empty rows from pandas dataframe (manifest data).
 
     Args:
-        df: pandas dataframe with data from manifest file.
+        dataframe: pandas dataframe with data from manifest file.
 
     Returns:
         df: cleaned-up pandas dataframe.
     """
     # remove all columns which have substring "Unnamed" in them
-    df = df.loc[:, ~df.columns.str.contains("^Unnamed")]
+    dataframe = dataframe.loc[:, ~dataframe.columns.str.contains("^Unnamed")]
 
     # remove all completely empty rows
-    df = df.dropna(how="all", axis=0)
+    dataframe = dataframe.dropna(how="all", axis=0)
 
-    #Fill in nan cells with empty strings
-    df.fillna("", inplace=True)
-    return df
+    # Fill in nan cells with empty strings
+    dataframe.fillna("", inplace=True)
+    return dataframe
 
 
-def col_in_dataframe(col: str, df: pd.DataFrame) -> bool:
-    """Check if a column is in a dataframe, without worring about case
+def col_in_dataframe(col: str, dataframe: pd.DataFrame) -> bool:
+    """Check if a column is in a dataframe, without worrying about case
 
     Args:
         col: name of column whose presence in the dataframe is being checked
-        df: pandas dataframe with data from manifest file.
+        dataframe: pandas dataframe with data from manifest file.
 
     Returns:
         bool: whether or not the column name is a column in the dataframe, case agnostic
     """
-    return col.lower() in [manifest_col.lower() for manifest_col in df.columns.to_list()]
+    return col.lower() in [
+        manifest_col.lower() for manifest_col in dataframe.columns.to_list()
+    ]
+
 
-def populate_df_col_with_another_col(df: pd.DataFrame, source_col: str, target_col: str) -> pd.DataFrame:
+def populate_df_col_with_another_col(
+    dataframe: pd.DataFrame, source_col: str, target_col: str
+) -> pd.DataFrame:
     """Copy the values from one column in a dataframe to another column in the same dataframe
     Args:
-        df: pandas dataframe with data from manifest file.
+        dataframe: pandas dataframe with data from manifest file.
         source_col: column whose contents to copy over
         target_col: column to be updated with other contents
 
@@ -210,5 +282,5 @@ def populate_df_col_with_another_col(df: pd.DataFrame, source_col: str, target_c
         dataframe with contents updated
     """
     # Copy the contents over
-    df[target_col]=df[source_col]
-    return df
\ No newline at end of file
+    dataframe[target_col] = dataframe[source_col]
+    return dataframe
diff --git a/schematic/utils/general.py b/schematic/utils/general.py
index 8b7b62e35..246d0bc9e 100644
--- a/schematic/utils/general.py
+++ b/schematic/utils/general.py
@@ -1,6 +1,8 @@
-# allows specifying explicit variable types
+"""General utils"""
+
+# pylint: disable=logging-fstring-interpolation
+
 import logging
-import math
 import os
 import pstats
 import subprocess
@@ -8,79 +10,123 @@
 from cProfile import Profile
 from datetime import datetime, timedelta
 from functools import wraps
-from typing import Union
-
-from synapseclient.core.exceptions import SynapseHTTPError
-from synapseclient.entity import File, Folder, Project
-from synapseclient.table import EntityViewSchema
+from typing import Union, TypeVar, Any, Optional, Sequence, Callable
 
-import synapseclient.core.cache as cache
+from synapseclient.core.exceptions import SynapseHTTPError  # type: ignore
+from synapseclient.entity import File, Folder, Project  # type: ignore
+from synapseclient.table import EntityViewSchema  # type: ignore
+from synapseclient.core import cache  # type: ignore
+from synapseclient import Synapse  # type: ignore
 
 logger = logging.getLogger(__name__)
 
-def find_duplicates(_list):
+T = TypeVar("T")
+
+
+def find_duplicates(_list: list[T]) -> set[T]:
     """Find duplicate items in a list"""
-    return set([x for x in _list if _list.count(x) > 1])
+    return {x for x in _list if _list.count(x) > 1}
 
 
-def dict2list(dictionary):
-    if type(dictionary) == list:
-        return dictionary
-    elif type(dictionary) == dict:
-        return [dictionary]
+def dict2list(item: Any) -> Optional[Union[dict, list]]:
+    """Puts a dictionary into a list
 
+    Args:
+        item (Any): Any type of input
 
-def str2list(_str):
-    if type(_str) == str:
-        return [_str]
-    elif type(_str) == list:
-        return _str
+    Returns:
+        Optional[Union[dict, list]]:
+          If input is a list, return it
+          If input is a dict, return it in a list
+          Return None for anything else
+    """
+    if isinstance(item, list):
+        return item
+    if isinstance(item, dict):
+        return [item]
+    return None
 
 
-def unlist(_list):
-    if len(_list) == 1:
-        return _list[0]
-    else:
-        return _list
+def str2list(item: Any) -> Optional[list]:
+    """Puts a string into a list
+
+    Args:
+        item (Any): Any type of input
+
+    Returns:
+        Optional[list]:
+          If input is a list, return it
+          If input is a string, return it in a list
+          Return None for anything else
+    """
+    if isinstance(item, str):
+        return [item]
+    if isinstance(item, list):
+        return item
+    return None
 
 
-def get_dir_size(path: str):
-    """Recursively descend the directory tree rooted at the top and call .st_size function to calculate size of files in bytes. 
+def unlist(seq: Sequence) -> Any:
+    """Returns the first item of a sequence
+
+    Args:
+        seq (Sequence): Any sequence
+
+    Returns:
+        Any:
+          if sequence is length one, return the first item
+          otherwise return the sequence
+    """
+    if len(seq) == 1:
+        return seq[0]
+    return seq
+
+
+def get_dir_size(path: str) -> int:
+    """
+    Recursively descend the directory tree rooted at the top and call
+      .st_size function to calculate size of files in bytes.
     Args:
         path: path to a folder
-    return: total size of all the files in a given directory in bytes. 
+    return: total size of all the files in a given directory in bytes.
     """
     total = 0
     # Recursively scan directory to find entries
-    with os.scandir(path) as it:
-        for entry in it:
+    with os.scandir(path) as itr:
+        for entry in itr:
             if entry.is_file():
                 total += entry.stat().st_size
             elif entry.is_dir():
                 total += get_dir_size(entry.path)
     return total
 
-def calculate_datetime(minutes: int, input_date: datetime, before_or_after: str = "before") -> datetime:
-    """calculate date time 
+
+def calculate_datetime(
+    minutes: int, input_date: datetime, before_or_after: str = "before"
+) -> datetime:
+    """calculate date time
 
     Args:
         input_date (datetime): date time object provided by users
         minutes (int): number of minutes
-        before_or_after (str): default to "before". if "before", calculate x minutes before current date time. if "after", calculate x minutes after current date time. 
+        before_or_after (str): default to "before". if "before", calculate x minutes before
+         current date time. if "after", calculate x minutes after current date time.
 
     Returns:
         datetime:  return result of date time calculation
     """
-    if before_or_after=="before": 
+    if before_or_after == "before":
         date_time_result = input_date - timedelta(minutes=minutes)
-    elif before_or_after=="after":
+    elif before_or_after == "after":
         date_time_result = input_date + timedelta(minutes=minutes)
     else:
         raise ValueError("Invalid value. Use either 'before' or 'after'.")
     return date_time_result
 
 
-def check_synapse_cache_size(directory='/root/.synapseCache')-> Union[float, int]:
+def check_synapse_cache_size(
+    directory: str = "/root/.synapseCache",
+) -> Union[float, int]:
     """use du --sh command to calculate size of .synapseCache.
 
     Args:
@@ -89,83 +135,97 @@ def check_synapse_cache_size(directory='/root/.synapseCache')-> Union[float, int
     Returns:
         float or integer: returns size of .synapsecache directory in bytes
     """
-    # Note: this command might fail on windows user. But since this command is primarily for running on AWS, it is fine. 
-    command = ['du', '-sh', directory]
-    output = subprocess.run(command, capture_output=True).stdout.decode('utf-8')
-    
+    # Note: this command might fail on windows user.
+    # But since this command is primarily for running on AWS, it is fine.
+    command = ["du", "-sh", directory]
+    output = subprocess.run(command, capture_output=True, check=False).stdout.decode(
+        "utf-8"
+    )
+
     # Parsing the output to extract the directory size
-    size = output.split('\t')[0]
+    size = output.split("\t")[0]
     if "K" in size:
-        size_in_kb = float(size.rstrip('K'))
+        size_in_kb = float(size.rstrip("K"))
         byte_size = size_in_kb * 1000
     elif "M" in size:
-        size_in_mb = float(size.rstrip('M'))
+        size_in_mb = float(size.rstrip("M"))
         byte_size = size_in_mb * 1000000
-    elif "G" in size: 
-        size_in_gb = float(size.rstrip('G'))
+    elif "G" in size:
+        size_in_gb = float(size.rstrip("G"))
         byte_size = convert_gb_to_bytes(size_in_gb)
     elif "B" in size:
-        byte_size = float(size.rstrip('B'))
+        byte_size = float(size.rstrip("B"))
     else:
-        logger.error('Cannot recongize the file size unit')
+        logger.error("Cannot recongize the file size unit")
     return byte_size
 
-def clear_synapse_cache(cache: cache.Cache, minutes: int) -> int:
+
+def clear_synapse_cache(synapse_cache: cache.Cache, minutes: int) -> int:
     """clear synapse cache before a certain time
 
     Args:
-        cache: an object of synapseclient Cache.
+        synapse_cache: an object of synapseclient Cache.
         minutes (int): all files before this minute will be removed
     Returns:
         int: number of files that get deleted
     """
     current_date = datetime.utcnow()
-    minutes_earlier = calculate_datetime(input_date=current_date, minutes=minutes, before_or_after="before")
-    num_of_deleted_files = cache.purge(before_date = minutes_earlier)
+    minutes_earlier = calculate_datetime(
+        input_date=current_date, minutes=minutes, before_or_after="before"
+    )
+    num_of_deleted_files = synapse_cache.purge(before_date=minutes_earlier)
     return num_of_deleted_files
 
-def convert_gb_to_bytes(gb: int):
+
+def convert_gb_to_bytes(g_bytes: int) -> int:
     """convert gb to bytes
     Args:
-        gb: number of gb
+        g_bytes: number of gb
     return: total number of bytes
     """
-    return gb * 1024 * 1024 * 1024
+    return g_bytes * 1024 * 1024 * 1024
 
 
-def entity_type_mapping(syn, entity_id):
-    """
-    Return the entity type of manifest
+def entity_type_mapping(syn: Synapse, entity_id: str) -> str:
+    """Return the entity type of manifest
+
     Args:
-        entity_id: id of an entity
-    Return:
-        type_entity: type of the manifest being returned
+        syn (Synapse): Synapse object
+        entity_id (str): id of an entity
+
+    Raises:
+        SynapseHTTPError: Re-raised SynapseHTTPError
+
+    Returns:
+        str: type of the manifest being returned
     """
     # check the type of entity
     try:
         entity = syn.get(entity_id, downloadFile=False)
-    except SynapseHTTPError as e:
+    except SynapseHTTPError as exc:
         logger.error(
             f"cannot get {entity_id} from asset store. Please make sure that {entity_id} exists"
         )
         raise SynapseHTTPError(
             f"cannot get {entity_id} from asset store. Please make sure that {entity_id} exists"
-        ) from e
+        ) from exc
 
     if isinstance(entity, EntityViewSchema):
-        return "asset view"
+        entity_type = "asset view"
     elif isinstance(entity, Folder):
-        return "folder"
+        entity_type = "folder"
     elif isinstance(entity, File):
-        return "file"
+        entity_type = "file"
     elif isinstance(entity, Project):
-        return "project"
+        entity_type = "project"
     else:
         # if there's no matching type, return concreteType
-        return entity.concreteType
+        entity_type = entity.concreteType
+    return entity_type
+
 
 def create_temp_folder(path: str) -> str:
-    """This function creates a temporary directory in the specified directory 
+    """This function creates a temporary directory in the specified directory
     Args:
         path(str): a directory path where all the temporary files will live
     Returns: returns the absolute pathname of the new directory.
@@ -175,64 +235,78 @@ def create_temp_folder(path: str) -> str:
     return path
 
 
-def profile(output_file=None, sort_by='cumulative', lines_to_print=None, strip_dirs=False):
+def profile(
+    output_file: Optional[str] = None,
+    sort_by: Any = "cumulative",
+    lines_to_print: Optional[int] = None,
+    strip_dirs: bool = False,
+) -> Callable:
     """
-    The function was initially taken from: https://towardsdatascience.com/how-to-profile-your-code-in-python-e70c834fad89
+    The function was initially taken from:
+    https://towardsdatascience.com/how-to-profile-your-code-in-python-e70c834fad89
     A time profiler decorator.
     Inspired by and modified the profile decorator of Giampaolo Rodola:
     http://code.activestate.com/recipes/577817-profile-decorator/
+
     Args:
-        output_file: str or None. Default is None
+        output_file (Optional[str], optional):
             Path of the output file. If only name of the file is given, it's
             saved in the current directory.
             If it's None, the name of the decorated function is used.
-        sort_by: str or SortKey enum or tuple/list of str/SortKey enum
+            Defaults to None.
+        sort_by (str, optional):
+            str or SortKey enum or tuple/list of str/SortKey enum
             Sorting criteria for the Stats object.
             For a list of valid string and SortKey refer to:
             https://docs.python.org/3/library/profile.html#pstats.Stats.sort_stats
-        lines_to_print: int or None
-            Number of lines to print. Default (None) is for all the lines.
+            Defaults to "cumulative".
+        lines_to_print (Optional[int], optional):
+            Number of lines to print.
             This is useful in reducing the size of the printout, especially
             that sorting by 'cumulative', the time consuming operations
             are printed toward the top of the file.
-        strip_dirs: bool
+            Default (None) is for all the lines.
+        strip_dirs (bool, optional):
             Whether to remove the leading path info from file names.
             This is also useful in reducing the size of the printout
+            Defaults to False.
+
     Returns:
-        Profile of the decorated function
+        Callable: Profile of the decorated function
     """
 
     def inner(func):
         @wraps(func)
         def wrapper(*args, **kwargs):
-            _output_file = output_file or func.__name__ + '.prof'
-            pr = Profile()
-            pr.enable()
+            _output_file = output_file or func.__name__ + ".prof"
+            profiler = Profile()
+            profiler.enable()
             retval = func(*args, **kwargs)
-            pr.disable()
-            pr.dump_stats(_output_file)
+            profiler.disable()
+            profiler.dump_stats(_output_file)
 
-            #if we are running the functions on AWS: 
+            # if we are running the functions on AWS:
             if "SECRETS_MANAGER_SECRETS" in os.environ:
-                ps = pstats.Stats(pr)
+                p_stats = pstats.Stats(profiler)
                 # limit this to 30 line for now otherwise it will be too long for AWS log
-                ps.sort_stats('cumulative').print_stats(30)
-            else: 
-                with open(_output_file, 'w') as f:
-                    ps = pstats.Stats(pr, stream=f)
+                p_stats.sort_stats("cumulative").print_stats(30)
+            else:
+                with open(_output_file, "w", encoding="utf-8") as fle:
+                    p_stats = pstats.Stats(profiler, stream=fle)
                     if strip_dirs:
-                        ps.strip_dirs()
+                        p_stats.strip_dirs()
                     if isinstance(sort_by, (tuple, list)):
-                        ps.sort_stats(*sort_by)
+                        p_stats.sort_stats(*sort_by)
                     else:
-                        ps.sort_stats(sort_by)
-                    ps.print_stats(lines_to_print)
+                        p_stats.sort_stats(sort_by)
+                    p_stats.print_stats(lines_to_print)
             return retval
 
         return wrapper
 
     return inner
 
+
 def normalize_path(path: str, parent_folder: str) -> str:
     """
     Normalizes a path.
diff --git a/schematic/utils/google_api_utils.py b/schematic/utils/google_api_utils.py
index ac3def72f..4cc743e6b 100644
--- a/schematic/utils/google_api_utils.py
+++ b/schematic/utils/google_api_utils.py
@@ -1,19 +1,17 @@
+"""Google API utils"""
+
+# pylint: disable=logging-fstring-interpolation
+
 import os
-import pickle
 import logging
 import json
-import pygsheets as ps
-
-from typing import Dict, Any
+from typing import Any, Union
 
-from googleapiclient.discovery import build
-from google_auth_oauthlib.flow import InstalledAppFlow
-from google.auth.transport.requests import Request
-from google.oauth2 import service_account
-from google.oauth2.credentials import Credentials
+import pandas as pd
+from googleapiclient.discovery import build  # type: ignore
+from google.oauth2 import service_account  # type: ignore
 from schematic.configuration.configuration import CONFIG
 from schematic.store.synapse import SynapseStorage
-import pandas as pd
 
 logger = logging.getLogger(__name__)
 
@@ -24,32 +22,26 @@
     "https://www.googleapis.com/auth/drive",
 ]
 
-# TODO: replace by pygsheets calls?
-def build_credentials() -> Dict[str, Any]:
-    creds = generate_token()
-
-    # get a Google Sheet API service
-    sheet_service = build("sheets", "v4", credentials=creds)
-    # get a Google Drive API service
-    drive_service = build("drive", "v3", credentials=creds)
-
-    return {
-        "sheet_service": sheet_service,
-        "drive_service": drive_service,
-        "creds": creds,
-    }
 
+def build_service_account_creds() -> dict[str, Any]:
+    """Build Google service account credentials
 
-def build_service_account_creds() -> Dict[str, Any]:
+    Returns:
+        dict[str, Any]: The credentials
+    """
     if "SERVICE_ACCOUNT_CREDS" in os.environ:
-        dict_creds=json.loads(os.environ["SERVICE_ACCOUNT_CREDS"])
-        credentials = service_account.Credentials.from_service_account_info(dict_creds, scopes=SCOPES)
+        dict_creds = json.loads(os.environ["SERVICE_ACCOUNT_CREDS"])
+        credentials = service_account.Credentials.from_service_account_info(
+            dict_creds, scopes=SCOPES
+        )
 
     # for AWS deployment
     elif "SECRETS_MANAGER_SECRETS" in os.environ:
-        all_secrets_dict =json.loads(os.environ["SECRETS_MANAGER_SECRETS"])
-        dict_creds=json.loads(all_secrets_dict["SERVICE_ACCOUNT_CREDS"])
-        credentials = service_account.Credentials.from_service_account_info(dict_creds, scopes=SCOPES)
+        all_secrets_dict = json.loads(os.environ["SECRETS_MANAGER_SECRETS"])
+        dict_creds = json.loads(all_secrets_dict["SERVICE_ACCOUNT_CREDS"])
+        credentials = service_account.Credentials.from_service_account_info(
+            dict_creds, scopes=SCOPES
+        )
     else:
         credentials = service_account.Credentials.from_service_account_file(
             CONFIG.service_account_credentials_path, scopes=SCOPES
@@ -68,21 +60,24 @@ def build_service_account_creds() -> Dict[str, Any]:
 
 
 def download_creds_file() -> None:
+    """Download google credentials file"""
     syn = SynapseStorage.login()
 
     # if file path of service_account does not exist
     # and if an environment variable related to service account is not found
     # regenerate service_account credentials
-    if not os.path.exists(CONFIG.service_account_credentials_path) and "SERVICE_ACCOUNT_CREDS" not in os.environ:
-
+    if (
+        not os.path.exists(CONFIG.service_account_credentials_path)
+        and "SERVICE_ACCOUNT_CREDS" not in os.environ
+    ):
         # synapse ID of the 'schematic_service_account_creds.json' file
-        API_CREDS = CONFIG.service_account_credentials_synapse_id
+        api_creds = CONFIG.service_account_credentials_synapse_id
 
         # Download in parent directory of SERVICE_ACCT_CREDS to
         # ensure same file system for os.rename()
         creds_dir = os.path.dirname(CONFIG.service_account_credentials_path)
 
-        creds_file = syn.get(API_CREDS, downloadLocation=creds_dir)
+        creds_file = syn.get(api_creds, downloadLocation=creds_dir)
         os.rename(creds_file.path, CONFIG.service_account_credentials_path)
 
         logger.info(
@@ -97,16 +92,19 @@ def download_creds_file() -> None:
         )
 
 
-def execute_google_api_requests(service, requests_body, **kwargs):
+def execute_google_api_requests(service: Any, requests_body: Any, **kwargs) -> Any:
     """
     Execute google API requests batch; attempt to execute in parallel.
+
     Args:
-        service: google api service; for now assume google sheets service that is instantiated and authorized
-        service_type: default batchUpdate; TODO: add logic for values update
+        service (Any): google api service; for now assume google sheets service that is
+          instantiated and authorized
+        requests_body (Any): _description_
         kwargs: google API service parameters
-    Return: google API response
-    """
 
+    Returns:
+        Any: google API response or None
+    """
     if (
         "spreadsheet_id" in kwargs
         and "service_type" in kwargs
@@ -120,88 +118,55 @@ def execute_google_api_requests(service, requests_body, **kwargs):
         )
 
         return response
+    return None
 
-def export_manifest_drive_service(manifest_url, file_path, mimeType):
-    '''
-    Export manifest by using google drive api. If export as an Excel spreadsheet, the exported spreasheet would also include a hidden sheet 
-    Args:
-        manifest_url: google sheet manifest url
-        file_path: file path of the exported manifest
-        mimeType: exporting mimetype
 
+def export_manifest_drive_service(
+    manifest_url: str, file_path: str, mime_type: str
+) -> None:
+    """
+    Export manifest by using google drive api. If export as an Excel spreadsheet,
+      the exported spreadsheet would also include a hidden sheet
     result: Google sheet gets exported in desired format
 
-    '''
-
-    # intialize drive service 
+    Args:
+        manifest_url (str): google sheet manifest url
+        file_path (str): file path of the exported manifest
+        mime_type (str):  exporting mimetype
+    """
+    # initialize drive service
     services_creds = build_service_account_creds()
     drive_service = services_creds["drive_service"]
 
     # get spreadsheet id
-    spreadsheet_id = manifest_url.split('/')[-1]
+    spreadsheet_id = manifest_url.split("/")[-1]
 
-    # use google drive 
-    data = drive_service.files().export(fileId=spreadsheet_id, mimeType=mimeType).execute()
+    # use google drive
+    # Pylint seems to have trouble with the google api classes, recognizing their methods
+    data = (
+        drive_service.files()  # pylint: disable=no-member
+        .export(fileId=spreadsheet_id, mimeType=mime_type)
+        .execute()
+    )
 
     # open file and write data
-    with open(os.path.abspath(file_path), 'wb') as f:
-        try: 
-            f.write(data)
-        except FileNotFoundError as not_found: 
+    with open(os.path.abspath(file_path), "wb") as fle:
+        try:
+            fle.write(data)
+        except FileNotFoundError as not_found:
             logger.error(f"{not_found.filename} could not be found")
 
-    f.close
-   
 
-def export_manifest_csv(file_path, manifest):
-    '''
+def export_manifest_csv(file_path: str, manifest: Union[pd.DataFrame, str]) -> None:
+    """
     Export manifest as a CSV by using google drive api
-    Args:
-        manifest: could be a dataframe or a manifest url
-        file_path: file path of the exported manifest
-        mimeType: exporting mimetype
-
     result: Google sheet gets exported as a CSV
-    '''
 
-    if isinstance(manifest, pd.DataFrame):
-        manifest.to_csv(file_path, index=False)
-    else: 
-        export_manifest_drive_service(manifest, file_path, mimeType = 'text/csv')
-
-
-
-def export_manifest_excel(manifest, output_excel=None):
-    '''
-    Export manifest as an Excel spreadsheet by using google sheet API. This approach could export hidden sheet
     Args:
-        manifest: could be a dataframe or a manifest url 
-        output_excel: name of the exported manifest sheet
-    result: Google sheet gets exported as an excel spreadsheet. If there's a hidden sheet, the hidden sheet also gets exported. 
-    '''
-    # intialize drive service 
-    services_creds = build_service_account_creds()
-    sheet_service = services_creds["sheet_service"]
-
+        file_path (str):  file path of the exported manifest
+        manifest (Union[pd.DataFrame, str]): could be a dataframe or a manifest url
+    """
     if isinstance(manifest, pd.DataFrame):
-        manifest.to_excel(output_excel, index=False)
+        manifest.to_csv(file_path, index=False)
     else:
-        # get spreadsheet id from url 
-        spreadsheet_id = manifest.split('/')[-1]
-
-        # use google sheet api
-        sheet_metadata = sheet_service.spreadsheets().get(spreadsheetId=spreadsheet_id).execute()
-        sheets = sheet_metadata.get('sheets')
-
-        # export to Excel
-        writer = pd.ExcelWriter(output_excel)
-
-        # export each sheet in manifest
-        for sheet in sheets:
-            dataset = sheet_service.spreadsheets().values().get(spreadsheetId=spreadsheet_id, range=sheet['properties']['title']).execute()
-            dataset_df = pd.DataFrame(dataset['values'])
-            dataset_df.columns = dataset_df.iloc[0]
-            dataset_df.drop(dataset_df.index[0], inplace=True)
-            dataset_df.to_excel(writer, sheet_name=sheet['properties']['title'], index=False)
-        writer.save()
-        writer.close()   
\ No newline at end of file
+        export_manifest_drive_service(manifest, file_path, mime_type="text/csv")
diff --git a/schematic/utils/io_utils.py b/schematic/utils/io_utils.py
index 016ea5dcd..1651d085e 100644
--- a/schematic/utils/io_utils.py
+++ b/schematic/utils/io_utils.py
@@ -1,11 +1,12 @@
-import os
+"""io utils"""
+
+from typing import Any
 import json
 import urllib.request
-
 from schematic import LOADER
 
 
-def load_json(file_path):
+def load_json(file_path: str) -> Any:
     """Load json document from file path or url
 
     :arg str file_path: The path of the url doc, could be url or file path
@@ -16,28 +17,26 @@ def load_json(file_path):
             return data
     # handle file path
     else:
-        with open(file_path, encoding="utf8") as f:
-            data = json.load(f)
+        with open(file_path, encoding="utf8") as fle:
+            data = json.load(fle)
             return data
 
 
-def export_json(json_doc, file_path):
+def export_json(json_doc: Any, file_path: str) -> None:
     """Export JSON doc to file"""
-    with open(file_path, "w", encoding="utf8") as f:
-        json.dump(json_doc, f, sort_keys=True, indent=4, ensure_ascii=False)
+    with open(file_path, "w", encoding="utf8") as fle:
+        json.dump(json_doc, fle, sort_keys=True, indent=4, ensure_ascii=False)
 
 
-def load_default():
+def load_default() -> Any:
     """Load biolink vocabulary"""
     data_path = "data_models/biothings.model.jsonld"
     biothings_path = LOADER.filename(data_path)
-
     return load_json(biothings_path)
 
 
-def load_schemaorg():
-    """Load SchemOrg vocabulary"""
+def load_schemaorg() -> Any:
+    """Load SchemaOrg vocabulary"""
     data_path = "data_models/schema_org.model.jsonld"
-    schemaorg_path = LOADER.filename(data_path)
-
-    return load_json(schemaorg_path)
+    schema_org_path = LOADER.filename(data_path)
+    return load_json(schema_org_path)
diff --git a/schematic/utils/schema_utils.py b/schematic/utils/schema_utils.py
index b8cab8e66..6caba81c6 100644
--- a/schematic/utils/schema_utils.py
+++ b/schematic/utils/schema_utils.py
@@ -1,33 +1,53 @@
 import inflection
 import json
+import logging
 import networkx as nx
+import re
 import string
-from typing import List, Dict
-
-def attr_dict_template(key_name:str)->Dict[str,dict[str,dict]]:
-    return {key_name: {'Relationships': {}}}
-
-def get_property_label_from_display_name(display_name:str, strict_camel_case:bool = False) -> str:
-        """Convert a given display name string into a proper property label string
-        Args:
-            display_name, str: node display name
-            strict_camel_case, bool: Default, False; defines whether or not to use strict camel case or not for conversion.
-        Returns:
-            label, str: property label of display name
-        """
-        # This is the newer more strict method
-        if strict_camel_case:
-            display_name = display_name.strip().translate({ord(c): "_" for c in string.whitespace})
-            label = inflection.camelize(display_name, uppercase_first_letter=False)
-
-        # This method remains for backwards compatibility
-        else:
-            display_name = display_name.translate({ord(c): None for c in string.whitespace})
-            label = inflection.camelize(display_name.strip(), uppercase_first_letter=False)
+from typing import List, Literal, Dict, Tuple, Union
+
+
+logger = logging.getLogger(__name__)
+
+DisplayLabelType = Literal["class_label", "display_label"]
+BLACKLISTED_CHARS = ["(", ")", ".", " ", "-"]
+COMPONENT_NAME_DELIMITER = "#"
+COMPONENT_RULES_DELIMITER = "^^"
+RULE_DELIMITER = "::"
+
+
+def attr_dict_template(key_name: str) -> Dict[str, dict[str, dict]]:
+    return {key_name: {"Relationships": {}}}
+
+
+def get_property_label_from_display_name(
+    display_name: str, strict_camel_case: bool = False
+) -> str:
+    """Convert a given display name string into a proper property label string
+    Args:
+        display_name, str: node display name
+        strict_camel_case, bool: Default, False; defines whether or not to use strict camel case or not for conversion.
+    Returns:
+        label, str: property label of display name
+    """
+    # This is the newer more strict method
+    if strict_camel_case:
+        display_name = display_name.strip().translate(
+            {ord(c): "_" for c in string.whitespace}
+        )
+        label = inflection.camelize(display_name, uppercase_first_letter=False)
+
+    # This method remains for backwards compatibility
+    else:
+        display_name = display_name.translate({ord(c): None for c in string.whitespace})
+        label = inflection.camelize(display_name.strip(), uppercase_first_letter=False)
+
+    return label
 
-        return label
 
-def get_class_label_from_display_name(display_name:str, strict_camel_case:bool = False) -> str:
+def get_class_label_from_display_name(
+    display_name: str, strict_camel_case: bool = False
+) -> str:
     """Convert a given display name string into a proper class label string
     Args:
         display_name, str: node display name
@@ -37,7 +57,9 @@ def get_class_label_from_display_name(display_name:str, strict_camel_case:bool =
     """
     # This is the newer more strict method
     if strict_camel_case:
-        display_name = display_name.strip().translate({ord(c): "_" for c in string.whitespace})
+        display_name = display_name.strip().translate(
+            {ord(c): "_" for c in string.whitespace}
+        )
         label = inflection.camelize(display_name, uppercase_first_letter=True)
 
     # This method remains for backwards compatibility
@@ -47,22 +69,78 @@ def get_class_label_from_display_name(display_name:str, strict_camel_case:bool =
 
     return label
 
-def get_attribute_display_name_from_label(node_name: str, attr_relationships: dict) -> str:
-    '''Get attribute display name for a node, using the node label, requires the attr_relationships dicitonary from the data model parser
+
+def get_attribute_display_name_from_label(
+    node_name: str, attr_relationships: dict
+) -> str:
+    """Get attribute display name for a node, using the node label, requires the attr_relationships dicitonary from the data model parser
     Args:
         node_name, str: node label
         attr_relationships, dict: dictionary defining attributes and relationships, generated in data model parser.
     Returns:
         display_name, str: node display name, recorded in attr_relationships.
-    '''
-    if 'Attribute' in attr_relationships.keys():
-        display_name = attr_relationships['Attribute']
+    """
+    if "Attribute" in attr_relationships.keys():
+        display_name = attr_relationships["Attribute"]
     else:
         display_name = node_name
     return display_name
 
-def get_label_from_display_name(display_name:str, entry_type:str, strict_camel_case:bool = False) -> str:
-    """Get node label from provided display name, based on whether the node is a class or property
+
+def check_if_display_name_is_valid_label(
+    display_name: str,
+    blacklisted_chars: list[str] = BLACKLISTED_CHARS,
+) -> bool:
+    """Check if the display name can be used as a display label
+    Args:
+        display_name, str: node display name
+        blacklisted_chars, list[str]: characters that are not permitted for synapse annotations uploads.
+    Returns:
+        valid_label, bool: True, if the display name can be used as a label, False, if it cannot.
+    """
+    valid_label = True
+    if any(map(display_name.__contains__, blacklisted_chars)):
+        valid_label = False
+    return valid_label
+
+
+def get_stripped_label(
+    display_name: str,
+    entry_type: str,
+    blacklisted_chars: list[str] = BLACKLISTED_CHARS,
+) -> str:
+    """
+    Args:
+        display_name, str: node display name
+        entry_type, str: 'class' or 'property', defines what type the entry is.
+        blacklisted_chars, list[str]: characters that are not permitted for synapse annotations uploads.
+    Returns:
+        stripped_label, str: class or property label that has been stripped of blacklisted characters.
+    """
+    if entry_type.lower() == "class":
+        stripped_label = [
+            get_class_label_from_display_name(str(display_name)).translate(
+                {ord(x): "" for x in blacklisted_chars}
+            )
+        ][0]
+
+    elif entry_type.lower() == "property":
+        stripped_label = [
+            get_property_label_from_display_name(str(display_name)).translate(
+                {ord(x): "" for x in blacklisted_chars}
+            )
+        ][0]
+
+    logger.warning(
+        f"Cannot use display name {display_name} as the data model label, becaues it is not formatted properly. Please remove all spaces and blacklisted characters: {str(blacklisted_chars)}. The following label was assigned instead: {stripped_label}"
+    )
+    return stripped_label
+
+
+def get_schema_label(
+    display_name: str, entry_type: str, strict_camel_case: bool
+) -> str:
+    """Get the class or property label for a given display name
     Args:
         display_name, str: node display name
         entry_type, str: 'class' or 'property', defines what type the entry is.
@@ -70,18 +148,60 @@ def get_label_from_display_name(display_name:str, entry_type:str, strict_camel_c
     Returns:
         label, str: class label of display name
     Raises:
-        ValueError if entry_type.lower(), is not either 'class' or 'property'
+        Error Logged if entry_type.lower(), is not either 'class' or 'property'
+    """
+    if entry_type.lower() == "class":
+        label = get_class_label_from_display_name(
+            display_name=display_name, strict_camel_case=strict_camel_case
+        )
 
+    elif entry_type.lower() == "property":
+        label = get_property_label_from_display_name(
+            display_name=display_name, strict_camel_case=strict_camel_case
+        )
+    else:
+        logger.error(
+            f"The entry type submitted: {entry_type}, is not one of the permitted types: 'class' or 'property'"
+        )
+    return label
+
+
+def get_label_from_display_name(
+    display_name: str,
+    entry_type: str,
+    strict_camel_case: bool = False,
+    data_model_labels: DisplayLabelType = "class_label",
+) -> str:
+    """Get node label from provided display name, based on whether the node is a class or property
+    Args:
+        display_name, str: node display name
+        entry_type, str: 'class' or 'property', defines what type the entry is.
+        strict_camel_case, bool: Default, False; defines whether or not to use strict camel case or not for conversion.
+    Returns:
+        label, str: label to be used for the provided display name.
     """
-    if entry_type.lower()=='class':
-        label = get_class_label_from_display_name(display_name=display_name, strict_camel_case=strict_camel_case)
-    
-    elif entry_type.lower()=='property':
-        label=get_property_label_from_display_name(display_name=display_name, strict_camel_case=strict_camel_case)
+    if data_model_labels == "display_label":
+        # Check that display name can be used as a label.
+        valid_display_name = check_if_display_name_is_valid_label(
+            display_name=display_name
+        )
+        # If the display name is valid, set the label to be the display name
+        if valid_display_name:
+            label = display_name
+        # If not, set get a stripped class or property label (as indicated by the entry type)
+        else:
+            label = get_stripped_label(display_name=display_name, entry_type=entry_type)
+
     else:
-        raise ValueError(f"The entry type submitted: {entry_type}, is not one of the permitted types: 'class' or 'property'")
+        label = get_schema_label(
+            display_name=display_name,
+            entry_type=entry_type,
+            strict_camel_case=strict_camel_case,
+        )
+
     return label
 
+
 def convert_bool_to_str(provided_bool: bool) -> str:
     """Convert bool to string.
     Args:
@@ -91,17 +211,211 @@ def convert_bool_to_str(provided_bool: bool) -> str:
     """
     return str(provided_bool)
 
-def parse_validation_rules(validation_rules:List[str]) -> List[str]:
+
+def get_individual_rules(
+    rule: str, validation_rules: list[Union[str, None]]
+) -> Union[str, list]:
+    """Extract individual rules from a string and add to a list of rules
+    Args:
+        rule, str: valdation rule that has been parsed from a component rule.
+        validaiton_rules, list: list of rules being collected,
+            if this is the first time the list is being added to, it will be empty
+    Returns:
+        validaiton_rules, list: list of rules being collected.
+    """
+    # Separate multiple rules (defined by addition of the rule delimiter)
+    if RULE_DELIMITER in rule:
+        validation_rules.append(parse_single_set_validation_rules(rule))
+    # Get single rule
+    else:
+        validation_rules.append(rule)
+    return validation_rules
+
+
+def get_component_name_rules(
+    component_names: list[Union[str, None]], component_rule: str
+) -> Tuple[list, str]:
+    """Get component name and rule from an string that was initilly split by the COMPONENT_RULES_DELIMITER
+    Args:
+        component_names, list[Union[str,None]]: list of components, will be empty if being added to for the first time.
+        component_rule, str: component rule string that has only been split by the COMPONENT_RULES_DELIMETER
+    Returns:
+        Tuple[list,str]: list with the a new component name or 'all_other_components' appended,
+            rule with the component name stripped off.
+    Raises:
+        Error Logged if it looks like a component name should have been added to the list, but wass not.
+    """
+    # If a component name is not attached to the rule, have it apply to all other components
+    if COMPONENT_NAME_DELIMITER != component_rule[0]:
+        component_names.append("all_other_components")
+    # Get the component name if available
+    else:
+        component_names.append(
+            component_rule.split(" ")[0].replace(COMPONENT_NAME_DELIMITER, "")
+        )
+        if component_names[-1] == " ":
+            logger.error(
+                f"There was an error capturing at least one of the component names "
+                f"in the following rule: {component_rule}, "
+                f"please ensure there is not extra whitespace or non-allowed characters."
+            )
+
+        component_rule = component_rule.replace(component_rule.split(" ")[0], "")
+        component_rule = component_rule.strip()
+    return component_names, component_rule
+
+
+def check_for_duplicate_components(
+    component_names: list[str], validation_rule_string: str
+) -> None:
+    """Check if component names are repeated in a validation rule
+    Args:
+        component_names, list[str]: list of components identified in the validation rule
+        validation_rule_str, str: validation rule, used if error needs to be raised.
+    Returns:
+        None
+    Raises: Error Logged if a component name is duplicated.
+    """
+    duplicated_entries = [cn for cn in component_names if component_names.count(cn) > 1]
+    if duplicated_entries:
+        logger.error(
+            f"Oops, it looks like the following rule {validation_rule_string}, contains the same component "
+            f"name more than once. An attribute can only have a single rule applied per manifest/component."
+        )
+    return
+
+
+def parse_component_validation_rules(validation_rule_string: str) -> Dict:
+    """If a validation rule is identified to be fomatted as a component validation rule, parse to a dictionary of components:rules
+    Args:
+        validation_rule_string, str: validation rule provided by user.
+    Returns:
+        validation_rules_dict, dict: validation rules parsed to a dictionary where
+            the key is the component name (or 'all_other_components') and the value is the parsed validaiton rule for
+            the given component.
+    """
+    component_names = []
+    validation_rules = []
+
+    component_rules = validation_rule_string.split(COMPONENT_RULES_DELIMITER)
+    # Extract component rules, per component
+    for component_rule in component_rules:
+        component_rule = component_rule.strip()
+        if component_rule:
+            # Get component name attached to rule
+            component_names, component_rule = get_component_name_rules(
+                component_names=component_names, component_rule=component_rule
+            )
+
+            # Get rules
+            validation_rules = get_individual_rules(
+                rule=component_rule, validation_rules=validation_rules
+            )
+
+    # Ensure we collected the component names and validation rules like expected
+    if len(component_names) != len(validation_rules):
+        logger.error(
+            f"The number of components names and validation rules does not match "
+            f"for validation rule: {validation_rule_string}."
+        )
+
+    # If a component name is repeated throw an error.
+    check_for_duplicate_components(component_names, validation_rule_string)
+
+    validation_rules_dict = dict(zip(component_names, validation_rules))
+
+    return validation_rules_dict
+
+
+def parse_single_set_validation_rules(validation_rule_string: str) -> list:
+    """Parse a single set of validation rules.
+    Args:
+        validation_rule_string, str: validation rule provided by user.
+    Returns:
+        list, the valiation rule string split by the rule delimiter
+    Raise:
+        ValueEror if the string contains a component name delimter in the beginning.
+            This would indicate that a user was trying to set component rules, but did so improperly.
+    """
+    # Try to catch an improperly formatted rule
+    if COMPONENT_NAME_DELIMITER == validation_rule_string[0]:
+        logger.error(
+            f"The provided validation rule {validation_rule_string}, looks to be formatted as a component "
+            f"based rule, but is missing the necessary formatting, "
+            f"please refer to the SchemaHub documentation for more details."
+        )
+
+    return validation_rule_string.split(RULE_DELIMITER)
+
+
+def parse_validation_rules(validation_rules: Union[list, dict]) -> Union[list, dict]:
     """Split multiple validation rules based on :: delimiter
     Args:
-        validation_rules, list: list containing a string validation rule
+        validation_rules, Any[List[str], Dict]: List or Dictionary of validation rules,
+            if list, contains a string validation rule; if dictionary, key is the component the
+            rule (value) is applied to
     Returns:
-        validation_rules, list: if submitted List
+        validation_rules, Union[list,dict]: Parsed validation rules, component rules are output as a dictionary,
+            single sets are a list.
+    Raises:
+        Error Logged if Rule is not formatted properly
     """
-    if validation_rules and '::' in validation_rules[0]:
-        validation_rules = validation_rules[0].split('::')
+
+    if isinstance(validation_rules, dict):
+        # Rules pulled in as a dict can be used directly
+        return validation_rules
+    elif isinstance(validation_rules, list):
+        # If rules are already parsed from the JSONLD
+        if len(validation_rules) > 1 and isinstance(validation_rules[-1], str):
+            return validation_rules
+        # Parse rules set for a subset of components/manifests
+        elif COMPONENT_RULES_DELIMITER in validation_rules[0]:
+            return parse_component_validation_rules(
+                validation_rule_string=validation_rules[0]
+            )
+        # Parse rules that are set across *all* components/manifests
+        else:
+            return parse_single_set_validation_rules(
+                validation_rule_string=validation_rules[0]
+            )
+    return
+
+
+def extract_component_validation_rules(
+    manifest_component: str, validation_rules: dict[str, list]
+) -> list:
+    """Parse a component validation rule dictionary to pull out the rule (if any) for a given manifest
+    Args:
+        manifest_component, str: Component label, pulled from the manifest directly
+        validation_rules, dict[str, list[Union[list,str]]: Validation rules dictionary, where keys are the manifest component label,
+            and the value is a parsed set of validation rules.
+    Returns:
+        validation_rules, list[str]: rule for the provided manifest component if one is available,
+            if a validation rule is not specified for a given component but "all_other_components" is specified (as a key), then pull that one,
+            otherwise return an empty list.
+    """
+    manifest_component_rule = validation_rules.get(manifest_component)
+    all_component_rules = validation_rules.get("all_other_components")
+
+    # Capture situation where manifest_component rule is an empty string
+    if manifest_component_rule is not None:
+        if isinstance(manifest_component_rule, str):
+            if manifest_component_rule == "":
+                validation_rules = []
+            else:
+                validation_rules = [manifest_component_rule]
+        elif isinstance(manifest_component_rule, list):
+            validation_rules = manifest_component_rule
+    elif all_component_rules:
+        if isinstance(all_component_rules, str):
+            validation_rules = [all_component_rules]
+        elif isinstance(all_component_rules, list):
+            validation_rules = all_component_rules
+    else:
+        validation_rules = []
     return validation_rules
 
+
 def export_schema(schema: dict, file_path: str) -> None:
     """Export schema to given filepath.
     Args:
@@ -111,16 +425,17 @@ def export_schema(schema: dict, file_path: str) -> None:
     with open(file_path, "w") as f:
         json.dump(schema, f, sort_keys=True, indent=4, ensure_ascii=False)
 
+
 def strip_context(context_value: str) -> tuple[str]:
-        """Strip contexts from str entry.
-        Args:
-            context_value, str: string from which to strip context from
-        Returns:
-            context, str: the original context
-            v, str: value separated from context
-        """
-        if ':' in context_value:
-            context, v = context_value.split(':')
-        elif '@' in context_value:
-            context, v = context_value.split('@')
-        return context, v
+    """Strip contexts from str entry.
+    Args:
+        context_value, str: string from which to strip context from
+    Returns:
+        context, str: the original context
+        v, str: value separated from context
+    """
+    if ":" in context_value:
+        context, v = context_value.split(":")
+    elif "@" in context_value:
+        context, v = context_value.split("@")
+    return context, v
diff --git a/schematic/utils/validate_rules_utils.py b/schematic/utils/validate_rules_utils.py
index f0e91a470..3ee3399e6 100644
--- a/schematic/utils/validate_rules_utils.py
+++ b/schematic/utils/validate_rules_utils.py
@@ -1,170 +1,201 @@
-from ast import arg
-from jsonschema import ValidationError
+"""validate rules utils"""
+
 import logging
-import pandas as pd
-from typing import Any, Dict, Optional, Text, List
+from typing import Union
+from jsonschema import ValidationError
 
 
 logger = logging.getLogger(__name__)
 
-def validation_rule_info():
-    '''
+
+def validation_rule_info() -> (
+    dict[str, dict[str, Union[tuple[int, int], str, list[str], None]]]
+):
+    """
     Function to return dict that holds information about each rule
     Will be pulled into validate_single_rule, validate_manifest_rules, validate_schema_rules
-    Structure:    
+    Structure:
         Rule:{
             'arguments':(<num arguments allowed>, <num arguments required>),
             'type': <rule type>,
             'complementary_rules': [<rules available for pairing>]}
         }
-    '''
-    rule_dict = {
-            "int": {
-                'arguments':(1, 0),
-                'type': "type_validation",
-                'complementary_rules': ['inRange', 'IsNA'],
-                'default_message_level': 'error'},
-
-            "float": {
-                'arguments':(1, 0),
-                'type': "type_validation",
-                'complementary_rules': ['inRange', 'IsNA'],
-                'default_message_level': 'error'},
-
-            "num": {
-                'arguments':(1, 0),
-                'type': "type_validation",
-                'complementary_rules': ['inRange', 'IsNA'],
-                'default_message_level': 'error'},
-
-            "str": {
-                'arguments':(1, 0),
-                'type': "type_validation",
-                'complementary_rules': None,
-                'default_message_level': 'error'},
-
-            "date": {
-                'arguments':(1, 0),
-                'type': "content_validation",
-                'complementary_rules': None,
-                'default_message_level': 'error'
-            },
-
-            "regex": {
-                'arguments':(3, 2), 
-                'fixed_arg': ['strict'], 
-                'type': "regex_validation",
-                'complementary_rules': ['list'],
-                'default_message_level': 'error'},
-
-            "url" : {
-                'arguments':(101, 0), 
-                'type': "url_validation",
-                'complementary_rules': None,
-                'default_message_level': 'error'},
-
-            "list": {
-                'arguments':(2, 0), 
-                'type': "list_validation",
-                'complementary_rules': ['regex'],
-                'default_message_level': 'error'},
-                
-            "matchAtLeastOne": {
-                'arguments':(3, 2), 
-                'type': "cross_validation",
-                'complementary_rules': None,
-                'default_message_level': 'warning'},
-
-            "matchExactlyOne": {
-                'arguments':(3, 2), 
-                'type': "cross_validation",
-                'complementary_rules': None,
-                'default_message_level': 'warning'},
-                
-            "recommended": {
-                'arguments':(1, 0), 
-                'type': "content_validation",
-                'complementary_rules': None,
-                'default_message_level': 'warning'},
-
-            "protectAges": {
-                'arguments':(1, 0), 
-                'type': "content_validation",
-                'complementary_rules': ['inRange',],
-                'default_message_level': 'warning'},
-
-            "unique": {
-                'arguments':(1, 0), 
-                'type': "content_validation",
-                'complementary_rules': None,
-                'default_message_level': 'error'},
-                
-            "inRange": {
-                'arguments':(3, 2), 
-                'type': "content_validation",
-                'complementary_rules': ['int','float','num','protectAges'],
-                'default_message_level': 'error'},
-            
-            "IsNA":     {
-                'arguments':(1, 0), 
-                'type': "content_validation",
-                'complementary_rules': ['int', 'float', 'num', ],
-                'default_message_level': 'warning'},            
-            }
-
-    return rule_dict
-
-def get_error(validation_rules: list, 
-        attribute_name: str, error_type: str, input_filetype:str,) -> List[str]:
-    '''
-    Generate error message for errors when trying to specify 
+    """
+    return {
+        "int": {
+            "arguments": (1, 0),
+            "type": "type_validation",
+            "complementary_rules": ["inRange", "IsNA"],
+            "default_message_level": "error",
+        },
+        "float": {
+            "arguments": (1, 0),
+            "type": "type_validation",
+            "complementary_rules": ["inRange", "IsNA"],
+            "default_message_level": "error",
+        },
+        "num": {
+            "arguments": (1, 0),
+            "type": "type_validation",
+            "complementary_rules": ["inRange", "IsNA"],
+            "default_message_level": "error",
+        },
+        "str": {
+            "arguments": (1, 0),
+            "type": "type_validation",
+            "complementary_rules": None,
+            "default_message_level": "error",
+        },
+        "date": {
+            "arguments": (1, 0),
+            "type": "content_validation",
+            "complementary_rules": None,
+            "default_message_level": "error",
+        },
+        "regex": {
+            "arguments": (3, 2),
+            "fixed_arg": ["strict"],
+            "type": "regex_validation",
+            "complementary_rules": ["list"],
+            "default_message_level": "error",
+        },
+        "url": {
+            "arguments": (101, 0),
+            "type": "url_validation",
+            "complementary_rules": None,
+            "default_message_level": "error",
+        },
+        "list": {
+            "arguments": (2, 0),
+            "type": "list_validation",
+            "complementary_rules": ["regex"],
+            "default_message_level": "error",
+        },
+        "matchAtLeastOne": {
+            "arguments": (3, 2),
+            "type": "cross_validation",
+            "complementary_rules": None,
+            "default_message_level": "warning",
+        },
+        "matchExactlyOne": {
+            "arguments": (3, 2),
+            "type": "cross_validation",
+            "complementary_rules": None,
+            "default_message_level": "warning",
+        },
+        "recommended": {
+            "arguments": (1, 0),
+            "type": "content_validation",
+            "complementary_rules": None,
+            "default_message_level": "warning",
+        },
+        "protectAges": {
+            "arguments": (1, 0),
+            "type": "content_validation",
+            "complementary_rules": [
+                "inRange",
+            ],
+            "default_message_level": "warning",
+        },
+        "unique": {
+            "arguments": (1, 0),
+            "type": "content_validation",
+            "complementary_rules": None,
+            "default_message_level": "error",
+        },
+        "inRange": {
+            "arguments": (3, 2),
+            "type": "content_validation",
+            "complementary_rules": ["int", "float", "num", "protectAges"],
+            "default_message_level": "error",
+        },
+        "IsNA": {
+            "arguments": (1, 0),
+            "type": "content_validation",
+            "complementary_rules": [
+                "int",
+                "float",
+                "num",
+            ],
+            "default_message_level": "warning",
+        },
+    }
+
+
+def get_error(
+    validation_rules: str,
+    attribute_name: str,
+    error_type: str,
+    input_filetype: str,
+) -> list[str]:
+    """
+    Generate error message for errors when trying to specify
     multiple validation rules.
-    '''
-    error_col = attribute_name # Attribute name
-    
-    if error_type == 'delimiter':
-        error_str = (f"The {input_filetype}, has an error in the validation rule "
-            f"for the attribute: {attribute_name}, the provided validation rules ({validation_rules}) are improperly "
-            f"specified. Please check your delimiter is '::'")
+    """
+    error_col = attribute_name  # Attribute name
+
+    if error_type == "delimiter":
+        error_str = (
+            f"The {input_filetype}, has an error in the validation rule "
+            f"for the attribute: {attribute_name}, the provided validation rules "
+            f"({validation_rules}) are improperly "
+            "specified. Please check your delimiter is '::'"
+        )
         logging.error(error_str)
         error_message = error_str
-        error_val = f"Multiple Rules: Delimiter"
-    
-    if error_type == 'not_rule':
-        error_str = (f"The {input_filetype}, has an error in the validation rule "
-            f"for the attribute: {attribute_name}, the provided validation rules ({validation_rules}) is not "
-            f"a valid rule. Please check spelling.")
+        error_val = "Multiple Rules: Delimiter"
+
+    if error_type == "not_rule":
+        error_str = (
+            f"The {input_filetype}, has an error in the validation rule "
+            f"for the attribute: {attribute_name}, the provided validation rules "
+            f"({validation_rules}) is not "
+            "a valid rule. Please check spelling."
+        )
         logging.error(error_str)
         error_message = error_str
-        error_val = f"Not a Rule"
-    
-    if error_type == 'args_not_allowed':
-        error_str = (f"The {input_filetype}, has an error in the validation rule "
-            f"for the attribute: {attribute_name}, the provided validation rules ({validation_rules}) is not"
-            f"formatted properly. No additional arguments are allowed for this rule.")
+        error_val = "Not a Rule"
+
+    if error_type == "args_not_allowed":
+        error_str = (
+            f"The {input_filetype}, has an error in the validation rule "
+            f"for the attribute: {attribute_name}, the provided validation rules "
+            f"({validation_rules}) is not"
+            "formatted properly. No additional arguments are allowed for this rule."
+        )
         logging.error(error_str)
         error_message = error_str
-        error_val = f"Args not allowed."
-    if error_type == 'incorrect_num_args':
-        rule_type=validation_rules.split(" ")[0]
-        
+        error_val = "Args not allowed."
+    if error_type == "incorrect_num_args":
+        rule_type = validation_rules.split(" ")[0]
+
         if rule_type in validation_rule_info():
-            no_allowed, no_required = validation_rule_info()[rule_type]['arguments']
+            arg_tuple = validation_rule_info()[rule_type]["arguments"]
+            assert isinstance(arg_tuple, tuple)
+            assert len(arg_tuple) == 2
+            number_allowed = str(arg_tuple[0])
+            number_required = str(arg_tuple[1])
         else:
-            no_allowed, no_required = ('', '')
+            number_allowed, number_required = ("", "")
 
-        error_str = (f"The {input_filetype}, has an error in the validation rule "
-            f"for the attribute: {attribute_name}, the provided validation rules ({validation_rules}) is not "
-            f"formatted properly. The number of provided arguments does not match the number allowed({no_allowed}) or required({no_required}).")
+        error_str = (
+            f"The {input_filetype}, has an error in the validation rule "
+            f"for the attribute: {attribute_name}, the provided validation rules "
+            f"({validation_rules}) is not "
+            "formatted properly. The number of provided arguments does not match the "
+            f"number allowed({number_allowed}) or required({number_required})."
+        )
         logging.error(error_str)
         error_message = error_str
-        error_val = f"Incorrect num arguments."
-        
-    return ['NA', error_col, error_message, error_val]
+        error_val = "Incorrect num arguments."
+
+    return ["NA", error_col, error_message, error_val]
+
 
-def validate_single_rule(validation_rule, attribute, input_filetype):
-    '''
-    Perform validation for a single rule to ensure it is specified correctly with an appropriate number of arguments
+def validate_single_rule(validation_rule: str, attribute: str, input_filetype: str):
+    """
+    Perform validation for a single rule to ensure it is specified
+      correctly with an appropriate number of arguments
     Inputs:
         validation_rule: single rule being validated
         attribute: attribute validation rule was specified for
@@ -172,49 +203,84 @@ def validate_single_rule(validation_rule, attribute, input_filetype):
 
     Returns:
         errors: List of errors
-    '''
+    """
     errors = []
     validation_types = validation_rule_info()
     validation_rule_with_args = [
-                val_rule.strip() for val_rule in validation_rule.strip().split(" ")]
+        val_rule.strip() for val_rule in validation_rule.strip().split(" ")
+    ]
 
     rule_type = validation_rule_with_args[0]
 
     # ensure rules are not delimited incorrectly
-    if ':' in validation_rule:
-        errors.append(get_error(validation_rule, attribute,
-            error_type = 'delimiter', input_filetype=input_filetype))
+    if ":" in validation_rule:
+        errors.append(
+            get_error(
+                validation_rule,
+                attribute,
+                error_type="delimiter",
+                input_filetype=input_filetype,
+            )
+        )
     # Check that the rule is actually a valid rule type.
-    elif rule_type not in validation_types.keys():
-        errors.append(get_error(validation_rule, attribute,
-            error_type = 'not_rule', input_filetype=input_filetype))
+    elif rule_type not in validation_types:
+        errors.append(
+            get_error(
+                validation_rule,
+                attribute,
+                error_type="not_rule",
+                input_filetype=input_filetype,
+            )
+        )
     # if the rule is indeed a rule and formatted correctly, check that arguments are appropriate
     else:
-        arguments_allowed, arguments_required = validation_types[rule_type]['arguments']
+        arg_tuple = validation_rule_info()[rule_type]["arguments"]
+        assert isinstance(arg_tuple, tuple)
+        assert len(arg_tuple) == 2
+        arguments_allowed, arguments_required = arg_tuple
         # Remove any fixed args from our calc.
-        if 'fixed_arg' in validation_types[rule_type].keys():
-            fixed_args = validation_types[rule_type]['fixed_arg']
-            num_args = len([vr for vr in validation_rule_with_args if vr not in fixed_args])-1 
+        if "fixed_arg" in validation_types[rule_type]:
+            fixed_args = validation_types[rule_type]["fixed_arg"]
+            assert isinstance(fixed_args, list)
+            num_args = (
+                len([vr for vr in validation_rule_with_args if vr not in fixed_args])
+                - 1
+            )
         else:
             num_args = len(validation_rule_with_args) - 1
-            
+
         # If arguments are provided but not allowed, raise an error.
         if num_args and not arguments_allowed:
-            errors.append(get_error(validation_rule, attribute,
-                error_type = 'args_not_allowed', input_filetype=input_filetype))
-        
+            errors.append(
+                get_error(
+                    validation_rule,
+                    attribute,
+                    error_type="args_not_allowed",
+                    input_filetype=input_filetype,
+                )
+            )
+
         # If arguments are allowed, check that the correct amount have been passed.
         # There must be at least the number of args required,
         # and not more than allowed
         elif arguments_allowed:
             if (num_args < arguments_required) or (num_args > arguments_allowed):
-                errors.append(get_error(validation_rule, attribute,
-                    error_type = 'incorrect_num_args', input_filetype=input_filetype))
+                errors.append(
+                    get_error(
+                        validation_rule,
+                        attribute,
+                        error_type="incorrect_num_args",
+                        input_filetype=input_filetype,
+                    )
+                )
 
     return errors
 
-def validate_schema_rules(validation_rules, attribute, input_filetype):
-    '''
+
+def validate_schema_rules(
+    validation_rules: list[str], attribute: str, input_filetype: str
+) -> None:
+    """
     validation_rules: list
     input_filetype: str, used in error generation to aid user in
         locating the source of the error.
@@ -222,19 +288,16 @@ def validate_schema_rules(validation_rules, attribute, input_filetype):
     Validation Rules Formatting rules:
     Single Rules:
         Specified with the correct required arguments with no more than what is allowed
-    '''
+    """
     errors = []
-        
+
     # validate each individual rule
     for rule in validation_rules:
-        errors.extend(validate_single_rule(rule,
-            attribute, input_filetype))                
+        errors.extend(validate_single_rule(rule, attribute, input_filetype))
 
     if errors:
         raise ValidationError(
-                        f"The {input_filetype} has an error in the validation_rules set "
-                        f"for attribute {attribute}. "
-                        f"Validation failed with the following errors: {errors}"
-                    )
-    
-    return 
\ No newline at end of file
+            f"The {input_filetype} has an error in the validation_rules set "
+            f"for attribute {attribute}. "
+            f"Validation failed with the following errors: {errors}"
+        )
diff --git a/schematic/utils/validate_utils.py b/schematic/utils/validate_utils.py
index 78c8277eb..fed5b422c 100644
--- a/schematic/utils/validate_utils.py
+++ b/schematic/utils/validate_utils.py
@@ -1,14 +1,19 @@
-import os
-import pandas as pd
+"""Validation utils"""
+
+# pylint: disable = anomalous-backslash-in-string
+
+import re
+from collections.abc import Mapping
+from typing import Pattern, Union, Iterable, Any, Optional
+from numbers import Number
 from jsonschema import validate
-from re import compile, search, IGNORECASE
+import numpy as np
+import pandas as pd
 from schematic.utils.io_utils import load_json
 from schematic import LOADER
-from typing import List
-import numpy as np
-from numbers import Number
 
-def validate_schema(schema):
+
+def validate_schema(schema: Union[Mapping, bool]) -> None:
     """Validate schema against schema.org standard"""
     data_path = "validation_schemas/model.schema.json"
     json_schema_path = LOADER.filename(data_path)
@@ -16,7 +21,7 @@ def validate_schema(schema):
     return validate(schema, json_schema)
 
 
-def validate_property_schema(schema):
+def validate_property_schema(schema: Union[Mapping, bool]) -> None:
     """Validate schema against SchemaORG property definition standard"""
     data_path = "validation_schemas/property.schema.json"
     json_schema_path = LOADER.filename(data_path)
@@ -24,74 +29,77 @@ def validate_property_schema(schema):
     return validate(schema, json_schema)
 
 
-def validate_class_schema(schema):
+def validate_class_schema(schema: Union[Mapping, bool]) -> None:
     """Validate schema against SchemaORG class definition standard"""
     data_path = "validation_schemas/class.schema.json"
     json_schema_path = LOADER.filename(data_path)
     json_schema = load_json(json_schema_path)
     return validate(schema, json_schema)
 
-def comma_separated_list_regex():
-    # Regex to match with comma separated list 
-    # Requires at least one element and a comma to be valid 
-    # Does not require a trailing comma
-    csv_list_regex=compile('([^\,]+\,)(([^\,]+\,?)*)')
+
+def comma_separated_list_regex() -> Pattern[str]:
+    """
+    Regex to match with comma separated list
+    Requires at least one element and a comma to be valid
+    Does not require a trailing comma
+
+    Returns:
+        Pattern[str]:
+    """
+    csv_list_regex = re.compile("([^\,]+\,)(([^\,]+\,?)*)")
 
     return csv_list_regex
 
-def rule_in_rule_list(rule: str, rule_list: List[str]):
-    # Function to standardize 
-    # checking to see if a rule is contained in a list of rules. 
-    # Uses regex to avoid issues arising from validation rules with arguments 
-    # or rules that have arguments updated.
 
-    # seperate rule type if arguments are specified
+def rule_in_rule_list(rule: str, rule_list: list[str]) -> Optional[re.Match[str]]:
+    """
+    Function to standardize
+    checking to see if a rule is contained in a list of rules.
+    Uses regex to avoid issues arising from validation rules with arguments
+    or rules that have arguments updated.
+    """
+    # separate rule type if arguments are specified
     rule_type = rule.split(" ")[0]
 
     # Process string and list of strings for regex comparison
-    rule_type = rule_type + '[^\|]*'
-    rule_list = '|'.join(rule_list)
+    rule_type = rule_type + "[^\|]*"
+    rule_list_str = "|".join(rule_list)
+    return re.search(rule_type, rule_list_str, flags=re.IGNORECASE)
 
-    return search(rule_type, rule_list, flags=IGNORECASE)
 
-def parse_str_series_to_list(col: pd.Series):
+def parse_str_series_to_list(col: pd.Series) -> pd.Series:
     """
     Parse a pandas series of comma delimited strings
-    into a series with values that are lists of strings 
-    ex. 
+    into a series with values that are lists of strings
+    ex.
         Input:  'a,b,c'
-        Output: ['a','b','c']     
+        Output: ['a','b','c']
 
     """
-    col = col.apply(
-        lambda x: [s.strip() for s in str(x).split(",")]
-    )
+    col = col.apply(lambda x: [s.strip() for s in str(x).split(",")])
 
     return col
 
-def np_array_to_str_list(np_array):
+
+def np_array_to_str_list(np_array: Any) -> list[str]:
     """
     Parse a numpy array of ints to a list of strings
     """
-    return np.char.mod('%d', np_array).tolist()
+    return np.char.mod("%d", np_array).tolist()
+
 
-def iterable_to_str_list(iterable):
+def iterable_to_str_list(obj: Union[str, Number, Iterable]) -> list[str]:
     """
     Parse an object into a list of strings
     Accepts str, Number, and iterable inputs
     """
 
     # If object is a string, just return wrapped as a list
-    if isinstance(iterable, str):
-        return [iterable]
-    # If object is numberical, convert to string and wrap as a list
-    elif isinstance(iterable, Number):
-        return [str(iterable)]
-    # If the object is iterable and not a string, convert every element to string and wratp as a list
-    else:
-        strlist = []
-        for element in iterable:
-            strlist.append(str(element))
-
-    return strlist
-    
\ No newline at end of file
+    if isinstance(obj, str):
+        return [obj]
+    # If object is numerical, convert to string and wrap as a list
+    if isinstance(obj, Number):
+        return [str(obj)]
+    # If the object is iterable and not a string, convert every element
+    # to string and wrap as a list
+    return [str(item) for item in obj]
diff --git a/schematic/utils/viz_utils.py b/schematic/utils/viz_utils.py
index b62c9be47..58a904728 100644
--- a/schematic/utils/viz_utils.py
+++ b/schematic/utils/viz_utils.py
@@ -1,12 +1,24 @@
-import graphviz
+"""viz utils"""
 
+from typing import Optional
+import graphviz  # type: ignore
 
-def visualize(edges, size=None):
+
+def visualize(edges, size: Optional[float] = None) -> graphviz.Digraph:
+    """_summary_
+
+    Args:
+        edges (_type_): _description_
+        size (Optional[float], optional): _description_. Defaults to None.
+
+    Returns:
+        graphviz.Digraph: _description_
+    """
     if size:
-        d = graphviz.Digraph(graph_attr=[("size", size)])
+        digraph = graphviz.Digraph(graph_attr=[("size", size)])
     else:
-        d = graphviz.Digraph()
+        digraph = graphviz.Digraph()
 
     for _item in edges:
-        d.edge(_item[0], _item[1])
-    return d
+        digraph.edge(_item[0], _item[1])
+    return digraph
diff --git a/schematic/visualization/__init__.py b/schematic/visualization/__init__.py
index b5dbf3f05..d5526b1ad 100644
--- a/schematic/visualization/__init__.py
+++ b/schematic/visualization/__init__.py
@@ -1,2 +1,3 @@
+"""visualization imports"""
 from schematic.visualization.attributes_explorer import AttributesExplorer
-from schematic.visualization.tangled_tree import TangledTree
\ No newline at end of file
+from schematic.visualization.tangled_tree import TangledTree
diff --git a/schematic/visualization/attributes_explorer.py b/schematic/visualization/attributes_explorer.py
index 0917172dd..031fe5756 100644
--- a/schematic/visualization/attributes_explorer.py
+++ b/schematic/visualization/attributes_explorer.py
@@ -1,36 +1,41 @@
-import gc
+"""Attributes Explorer Class"""
 import json
 import logging
-import numpy as np
 import os
+
+import numpy as np
 import pandas as pd
-from typing import Any, Dict, Optional, Text, List
 
 from schematic.schemas.data_model_parser import DataModelParser
 from schematic.schemas.data_model_graph import DataModelGraph, DataModelGraphExplorer
 from schematic.schemas.data_model_json_schema import DataModelJSONSchema
-
 from schematic.utils.io_utils import load_json
 
 logger = logging.getLogger(__name__)
 
-class AttributesExplorer():
-    def __init__(self,
-                 path_to_jsonld: str,
-                 )-> None:
-        
+
+class AttributesExplorer:
+    """AttributesExplorer class"""
+
+    def __init__(
+        self,
+        path_to_jsonld: str,
+        data_model_labels: str,
+    ) -> None:
         self.path_to_jsonld = path_to_jsonld
 
         self.jsonld = load_json(self.path_to_jsonld)
 
         # Instantiate Data Model Parser
-        data_model_parser = DataModelParser(path_to_data_model = self.path_to_jsonld)
-        
-        #Parse Model
+        data_model_parser = DataModelParser(
+            path_to_data_model=self.path_to_jsonld,
+        )
+
+        # Parse Model
         parsed_data_model = data_model_parser.parse_model()
 
         # Instantiate DataModelGraph
-        data_model_grapher = DataModelGraph(parsed_data_model)
+        data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
         # Generate graph
         self.graph_data_model = data_model_grapher.generate_data_model_graph()
@@ -39,56 +44,68 @@ def __init__(self,
         self.dmge = DataModelGraphExplorer(self.graph_data_model)
 
         # Instantiate Data Model Json Schema
-        self.data_model_js = DataModelJSONSchema(jsonld_path=self.path_to_jsonld, graph=self.graph_data_model)
-        
-        self.output_path = self.create_output_path('merged_csv')
-    
-    def create_output_path(self, terminal_folder):
-        ''' Create output path to store Observable visualization data if it does not already exist.
-        
+        self.data_model_js = DataModelJSONSchema(
+            jsonld_path=self.path_to_jsonld, graph=self.graph_data_model
+        )
+
+        self.output_path = self.create_output_path("merged_csv")
+
+    def create_output_path(self, terminal_folder: str) -> str:
+        """Create output path to store Observable visualization data if it does not already exist.
+
         Args: self.path_to_jsonld
-        
-        Returns: output_path (str): path to store outputs 
-        '''
+
+        Returns: output_path (str): path to store outputs
+        """
         base_dir = os.path.dirname(self.path_to_jsonld)
-        self.schema_name = self.path_to_jsonld.split('/')[-1].split('.model.jsonld')[0]
-        output_path = os.path.join(base_dir, 'visualization', self.schema_name, terminal_folder)
+        self.schema_name = self.path_to_jsonld.split("/")[-1].split(".model.jsonld")[0]
+        output_path = os.path.join(
+            base_dir, "visualization", self.schema_name, terminal_folder
+        )
         if not os.path.exists(output_path):
             os.makedirs(output_path)
         return output_path
 
-    def convert_string_cols_to_json(self, df: pd.DataFrame, cols_to_modify: list):
-        """Converts values in a column from strings to JSON list 
+    def convert_string_cols_to_json(
+        self, dataframe: pd.DataFrame, cols_to_modify: list[str]
+    ) -> pd.DataFrame:
+        """Converts values in a column from strings to JSON list
         for upload to Synapse.
         """
-        for col in df.columns:
+        for col in dataframe.columns:
             if col in cols_to_modify:
-                df[col] = df[col].apply(lambda x: json.dumps([y.strip() for y in x]) if x != "NaN" and x  and x == np.nan else x)
-        return df
+                dataframe[col] = dataframe[col].apply(
+                    lambda x: json.dumps([y.strip() for y in x])
+                    if x != "NaN" and x and x == np.nan
+                    else x
+                )
+        return dataframe
 
-    def parse_attributes(self, save_file=True):
-        '''
+    def parse_attributes(self, save_file: bool = True) -> pd.DataFrame:
+        """
         Args: save_file (bool):
                 True: merged_df is saved locally to output_path.
                 False: merged_df is returned.
 
         Returns:
             merged_df (pd.DataFrame): dataframe containing data relating to attributes
-                for the provided data model for all components in the data model. 
+                for the provided data model for all components in the data model.
                 Dataframe is saved locally as a csv if save_file == True, or returned if
-                save_file == False. 
-                
-        '''
+                save_file == False.
+
+        """
         # get all components
-        component_dg = self.dmge.get_digraph_by_edge_type('requiresComponent')
+        component_dg = self.dmge.get_digraph_by_edge_type("requiresComponent")
         components = component_dg.nodes()
-        
-        # For each data type to be loaded gather all attribtes the user would
+
+        # For each data type to be loaded gather all attributes the user would
         # have to provide.
         return self._parse_attributes(components, save_file)
-    
-    def parse_component_attributes(self, component=None, save_file=True, include_index=True):
-        '''
+
+    def parse_component_attributes(
+        self, component=None, save_file: bool = True, include_index: bool = True
+    ) -> pd.DataFrame:
+        """
         Args: save_file (bool):
                 True: merged_df is saved locally to output_path.
                 False: merged_df is returned.
@@ -97,18 +114,19 @@ def parse_component_attributes(self, component=None, save_file=True, include_ind
 
         Returns:
             merged_df (pd.DataFrame): dataframe containing data relating to attributes
-                for the provided data model for the specified component in the data model. 
+                for the provided data model for the specified component in the data model.
                 Dataframe is saved locally as a csv if save_file == True, or returned if
-                save_file == False. 
-        '''        
+                save_file == False.
+        """
 
         if not component:
             raise ValueError("You must provide a component to visualize.")
-        else:
-            return self._parse_attributes([component], save_file, include_index)
+        return self._parse_attributes([component], save_file, include_index)
 
-    def _parse_attributes(self, components, save_file=True, include_index=True):
-        '''
+    def _parse_attributes(
+        self, components: list, save_file=True, include_index=True
+    ) -> pd.DataFrame:
+        """
         Args: save_file (bool):
                 True: merged_df is saved locally to output_path.
                 False: merged_df is returned.
@@ -119,109 +137,158 @@ def _parse_attributes(self, components, save_file=True, include_index=True):
 
         Returns:
             merged_df (pd.DataFrame): dataframe containing data relating to attributes
-                for the provided data model for specified components in the data model. 
+                for the provided data model for specified components in the data model.
                 Dataframe is saved locally as a csv if save_file == True, or returned if
-                save_file == False. 
+                save_file == False.
         Raises:
             ValueError:
-                If unable hits an error while attempting to get conditional requirements. 
+                If unable hits an error while attempting to get conditional requirements.
                 This error is likely to be found if there is a mismatch in naming.
-        '''
-        
-        # For each data type to be loaded gather all attribtes the user would
+        """
+        # This function needs to be refactored, temporarily disabling some pylint errors
+        # pylint: disable=too-many-locals
+        # pylint: disable=too-many-nested-blocks
+        # pylint: disable=too-many-branches
+        # pylint: disable=too-many-statements
+
+        # For each data type to be loaded gather all attributes the user would
         # have to provide.
         df_store = []
         for component in components:
-            data_dict = {}
+            data_dict: dict = {}
 
             # get the json schema
-            json_schema = self.data_model_js.get_json_validation_schema(source_node=component, schema_name=self.path_to_jsonld)
+            json_schema = self.data_model_js.get_json_validation_schema(
+                source_node=component, schema_name=self.path_to_jsonld
+            )
 
-            # Gather all attribues, their valid values and requirements
-            for key, value in json_schema['properties'].items():
+            # Gather all attributes, their valid values and requirements
+            for key, value in json_schema["properties"].items():
                 data_dict[key] = {}
-                for k, v in value.items():
-                    if k == 'enum':
-                        data_dict[key]['Valid Values'] = value['enum']
-                if key in json_schema['required']:
-                    data_dict[key]['Required'] = True
+                for inner_key in value.keys():
+                    if inner_key == "enum":
+                        data_dict[key]["Valid Values"] = value["enum"]
+                if key in json_schema["required"]:
+                    data_dict[key]["Required"] = True
                 else:
-                    data_dict[key]['Required'] = False
-                data_dict[key]['Component'] = component
+                    data_dict[key]["Required"] = False
+                data_dict[key]["Component"] = component
             # Add additional details per key (from the JSON-ld)
-            for dic in self.jsonld['@graph']:
-                if 'sms:displayName' in dic.keys():
-                    key = dic['sms:displayName']
-                    if key in data_dict.keys():
-                        data_dict[key]['Attribute'] = dic['sms:displayName']
-                        data_dict[key]['Label'] = dic['rdfs:label']
-                        data_dict[key]['Description'] = dic['rdfs:comment']
-                        if 'validationRules' in dic.keys():
-                            data_dict[key]['Validation Rules'] = dic['validationRules']
+            for dic in self.jsonld["@graph"]:
+                if "sms:displayName" in dic:
+                    key = dic["sms:displayName"]
+                    if key in data_dict:
+                        data_dict[key]["Attribute"] = dic["sms:displayName"]
+                        data_dict[key]["Label"] = dic["rdfs:label"]
+                        data_dict[key]["Description"] = dic["rdfs:comment"]
+                        if "validationRules" in dic.keys():
+                            data_dict[key]["Validation Rules"] = dic["validationRules"]
             # Find conditional dependencies
-            if 'allOf' in json_schema.keys():
-                for conditional_dependencies in json_schema['allOf']:
-                    key = list(conditional_dependencies['then']['properties'])[0]
+            if "allOf" in json_schema:
+                for conditional_dependencies in json_schema["allOf"]:
+                    key = list(conditional_dependencies["then"]["properties"])[0]
                     try:
-                        if key in data_dict.keys():
-                            if 'Cond_Req' not in data_dict[key].keys():
-                                data_dict[key]['Cond_Req'] = []
-                                data_dict[key]['Conditional Requirements'] = []
-                            attribute = list(conditional_dependencies['if']['properties'])[0]
-                            value = conditional_dependencies['if']['properties'][attribute]['enum']
-                            # Capitalize attribute if it begins with a lowercase letter, for aesthetics.
+                        if key in data_dict:
+                            if "Cond_Req" not in data_dict[key].keys():
+                                data_dict[key]["Cond_Req"] = []
+                                data_dict[key]["Conditional Requirements"] = []
+                            attribute = list(
+                                conditional_dependencies["if"]["properties"]
+                            )[0]
+                            value = conditional_dependencies["if"]["properties"][
+                                attribute
+                            ]["enum"]
+                            # Capitalize attribute if it begins with a lowercase
+                            # letter, for aesthetics.
                             if attribute[0].islower():
                                 attribute = attribute.capitalize()
 
-                            # Remove "Type" (i.e. turn "Biospecimen Type" to "Biospcimen")
-                            if "Type" in attribute: 
+                            # Remove "Type" (i.e. turn "Biospecimen Type" to "Biospecimen")
+                            if "Type" in attribute:
                                 attribute = attribute.split(" ")[0]
-                            
+
                             # Remove "Type" (i.e. turn "Tissue Type" to "Tissue")
                             if "Type" in value[0]:
                                 value[0] = value[0].split(" ")[0]
 
                             conditional_statement = f'{attribute} is "{value[0]}"'
-                            if conditional_statement not in data_dict[key]['Conditional Requirements']:
-                                data_dict[key]['Cond_Req'] = True
-                                data_dict[key]['Conditional Requirements'].extend([conditional_statement])
-                    except:
+                            if (
+                                conditional_statement
+                                not in data_dict[key]["Conditional Requirements"]
+                            ):
+                                data_dict[key]["Cond_Req"] = True
+                                data_dict[key]["Conditional Requirements"].extend(
+                                    [conditional_statement]
+                                )
+                    except Exception as exc:
                         raise ValueError(
-                            f"There is an error getting conditional requirements related "
-                            "to the attribute: {key}. The error is likely caused by naming inconsistencies (e.g. uppercase, camelcase, ...)"
-                        )
+                            (
+                                "There is an error getting conditional requirements related "
+                                f"to the attribute: {key}. The error is likely caused by naming "
+                                "inconsistencies (e.g. uppercase, camelcase, ...)"
+                            )
+                        ) from exc
 
-            for key, value in data_dict.items():
-                if 'Conditional Requirements' in value.keys():
+            for outer_dict_key, inner_dict in data_dict.items():
+                if "Conditional Requirements" in inner_dict.keys():
+                    ## reformat conditional requirement
+                    conditional_requirements = inner_dict["Conditional Requirements"]
 
-                    ## reformat conditional requirement 
+                    # get all attributes
+                    attr_lst = [i.split(" is ")[-1] for i in conditional_requirements]
 
-                    # get all attributes 
-                    attr_lst = [i.split(" is ")[-1] for i in data_dict[key]['Conditional Requirements']]
-                    
-                    # join a list of attributes by using OR 
+                    # join a list of attributes by using OR
                     attr_str = " OR ".join(attr_lst)
 
-                    # reformat the conditional requirement 
-                    component_name = data_dict[key]['Conditional Requirements'][0].split(' is ')[0]
-                    conditional_statement_str = f' If {component_name} is {attr_str} then "{key}" is required'
-
-                    data_dict[key]['Conditional Requirements'] = conditional_statement_str
-            df = pd.DataFrame(data_dict)
-            df = df.T
-            cols = ['Attribute', 'Label', 'Description', 'Required', 'Cond_Req', 'Valid Values', 'Conditional Requirements', 'Validation Rules', 'Component']
-            cols = [col for col in cols if col in df.columns]
-            df = df[cols]
-            df = self.convert_string_cols_to_json(df, ['Valid Values'])
-            #df.to_csv(os.path.join(csv_output_path, data_type + '.vis_data.csv'))
-            df_store.append(df)
-
-        merged_attributes_df = pd.concat(df_store, join='outer')
-        cols = ['Attribute', 'Label', 'Description', 'Required', 'Cond_Req', 'Valid Values', 'Conditional Requirements', 'Validation Rules', 'Component']
+                    # reformat the conditional requirement
+                    component_name = conditional_requirements[0].split(" is ")[0]
+
+                    conditional_statement_str = (
+                        f" If {component_name} is {attr_str} then "
+                        f'"{outer_dict_key}" is required'
+                    )
+                    conditional_requirements = conditional_statement_str
+
+            data_dict_df = pd.DataFrame(data_dict)
+            data_dict_df = data_dict_df.T
+            cols = [
+                "Attribute",
+                "Label",
+                "Description",
+                "Required",
+                "Cond_Req",
+                "Valid Values",
+                "Conditional Requirements",
+                "Validation Rules",
+                "Component",
+            ]
+            cols = [col for col in cols if col in data_dict_df.columns]
+            data_dict_df = data_dict_df[cols]
+            data_dict_df = self.convert_string_cols_to_json(
+                data_dict_df, ["Valid Values"]
+            )
+            df_store.append(data_dict_df)
+
+        merged_attributes_df = pd.concat(df_store, join="outer")
+        cols = [
+            "Attribute",
+            "Label",
+            "Description",
+            "Required",
+            "Cond_Req",
+            "Valid Values",
+            "Conditional Requirements",
+            "Validation Rules",
+            "Component",
+        ]
         cols = [col for col in cols if col in merged_attributes_df.columns]
 
         merged_attributes_df = merged_attributes_df[cols]
-        if save_file == True:
-            return merged_attributes_df.to_csv(os.path.join(self.output_path, self.schema_name + 'attributes_data.vis_data.csv'), index=include_index)
-        elif save_file == False:
-            return merged_attributes_df.to_csv(index=include_index)
+        if save_file:
+            return merged_attributes_df.to_csv(
+                os.path.join(
+                    self.output_path, self.schema_name + "attributes_data.vis_data.csv"
+                ),
+                index=include_index,
+            )
+        return merged_attributes_df.to_csv(index=include_index)
diff --git a/schematic/visualization/commands.py b/schematic/visualization/commands.py
index ad9670e2b..39bedc1c8 100644
--- a/schematic/visualization/commands.py
+++ b/schematic/visualization/commands.py
@@ -1,14 +1,20 @@
-#!/usr/bin/env python3
+"""visualization commands"""
+# pylint: disable=unused-argument
+# pylint: disable=useless-return
+# pylint: disable=unused-variable
+# pylint: disable=logging-fstring-interpolation
 
 import logging
 import sys
+from typing import Any
 
 import click
-import click_log
+import click_log  # type: ignore
 
 from schematic.visualization.attributes_explorer import AttributesExplorer
 from schematic.visualization.tangled_tree import TangledTree
 from schematic.utils.cli_utils import log_value_from_config, query_dict
+from schematic.utils.schema_utils import DisplayLabelType
 from schematic.help import viz_commands
 from schematic.help import model_commands
 from schematic.configuration.configuration import CONFIG
@@ -16,9 +22,11 @@
 logger = logging.getLogger(__name__)
 click_log.basic_config(logger)
 
-CONTEXT_SETTINGS = dict(help_option_names=["--help", "-h"])  # help options
+CONTEXT_SETTINGS = {"help_option_names": ["--help", "-h"]}  # help options
 
-# invoke_without_command=True -> forces the application not to show aids before losing them with a --h
+
+# invoke_without_command=True -> forces the application not to show aids before
+# losing them with a --h
 @click.group(context_settings=CONTEXT_SETTINGS, invoke_without_command=True)
 @click_log.simple_verbosity_option(logger)
 @click.option(
@@ -29,90 +37,126 @@
     help=query_dict(model_commands, ("model", "config")),
 )
 @click.pass_context
-def viz(ctx, config):  # use as `schematic model ...`
+def viz(ctx: Any, config: str) -> None:  # use as `schematic model ...`
     """
     Sub-commands for Visualization methods.
     """
     try:
         logger.debug(f"Loading config file contents in '{config}'")
         CONFIG.load_config(config)
-        ctx.obj =  CONFIG
-    except ValueError as e:
+        ctx.obj = CONFIG
+    except ValueError as exc:
         logger.error("'--config' not provided or environment variable not set.")
-        logger.exception(e)
+        logger.exception(exc)
         sys.exit(1)
 
+
 @viz.command(
     "attributes",
 )
 @click_log.simple_verbosity_option(logger)
-
+@click.option(
+    "--data_model_labels",
+    "-dml",
+    default="class_label",
+    type=click.Choice(["display_label", "class_label"], case_sensitive=True),
+    help=query_dict(
+        viz_commands, ("visualization", "tangled_tree", "data_model_labels")
+    ),
+)
 @click.pass_obj
-def get_attributes(ctx):
-    """
-    
-    """
+def get_attributes(
+    ctx: Any,
+    data_model_labels: DisplayLabelType,
+) -> None:
+    """Gets attributes"""
     # Get JSONLD file path
     path_to_jsonld = CONFIG.model_location
     log_value_from_config("jsonld", path_to_jsonld)
     # Run attributes explorer
-    AttributesExplorer(path_to_jsonld).parse_attributes(save_file=True)
+    AttributesExplorer(path_to_jsonld, data_model_labels).parse_attributes(
+        save_file=True
+    )
     return
 
-@viz.command(
-    "tangled_tree_text"
-)
+
+@viz.command("tangled_tree_text")
 @click_log.simple_verbosity_option(logger)
 @click.option(
     "-ft",
     "--figure_type",
-    type=click.Choice(['component', 'dependency'], case_sensitive=False),
+    required=True,
+    type=click.Choice(["component", "dependency"], case_sensitive=False),
     help=query_dict(viz_commands, ("visualization", "tangled_tree", "figure_type")),
 )
 @click.option(
     "-tf",
     "--text_format",
-    type=click.Choice(['plain', 'highlighted'], case_sensitive=False),
+    required=True,
+    type=click.Choice(["plain", "highlighted"], case_sensitive=False),
     help=query_dict(viz_commands, ("visualization", "tangled_tree", "text_format")),
 )
-
+@click.option(
+    "--data_model_labels",
+    "-dml",
+    default="class_label",
+    type=click.Choice(["display_label", "class_label"], case_sensitive=True),
+    help=query_dict(
+        viz_commands, ("visualization", "tangled_tree", "data_model_labels")
+    ),
+)
 @click.pass_obj
-def get_tangled_tree_text(ctx, figure_type, text_format):
-    """ Get text to be placed on the tangled tree visualization.
-    """
+def get_tangled_tree_text(
+    ctx: Any,
+    figure_type: str,
+    text_format: str,
+    data_model_labels: DisplayLabelType,
+) -> None:
+    """Get text to be placed on the tangled tree visualization."""
     # Get JSONLD file path
     path_to_jsonld = CONFIG.model_location
     log_value_from_config("jsonld", path_to_jsonld)
-    
+
     # Initialize TangledTree
-    tangled_tree = TangledTree(path_to_jsonld, figure_type)
+    tangled_tree = TangledTree(path_to_jsonld, figure_type, data_model_labels)
 
     # Get text for tangled tree.
     text_df = tangled_tree.get_text_for_tangled_tree(text_format, save_file=True)
     return
 
-@viz.command(
-    "tangled_tree_layers"
-)
+
+@viz.command("tangled_tree_layers")
 @click_log.simple_verbosity_option(logger)
 @click.option(
     "-ft",
     "--figure_type",
-    type=click.Choice(['component', 'dependency'], case_sensitive=False),
+    required=True,
+    type=click.Choice(["component", "dependency"], case_sensitive=False),
     help=query_dict(viz_commands, ("visualization", "tangled_tree", "figure_type")),
 )
-
+@click.option(
+    "--data_model_labels",
+    "-dml",
+    default="class_label",
+    type=click.Choice(["display_label", "class_label"], case_sensitive=True),
+    help=query_dict(
+        viz_commands, ("visualization", "tangled_tree", "data_model_labels")
+    ),
+)
 @click.pass_obj
-def get_tangled_tree_component_layers(ctx, figure_type):
-    ''' Get the components that belong in each layer of the tangled tree visualization.
-    '''
+def get_tangled_tree_component_layers(
+    ctx: Any,
+    figure_type: str,
+    data_model_labels: DisplayLabelType,
+) -> None:
+    """Get the components that belong in each layer of the tangled tree visualization."""
     # Get JSONLD file path
     path_to_jsonld = CONFIG.model_location
     log_value_from_config("jsonld", path_to_jsonld)
-    
+
     # Initialize Tangled Tree
-    tangled_tree = TangledTree(path_to_jsonld, figure_type)
-    
+    tangled_tree = TangledTree(path_to_jsonld, figure_type, data_model_labels)
+
     # Get tangled trees layers JSON.
     layers = tangled_tree.get_tangled_tree_layers(save_file=True)
 
diff --git a/schematic/visualization/tangled_tree.py b/schematic/visualization/tangled_tree.py
index 83635a39c..a91da9e17 100644
--- a/schematic/visualization/tangled_tree.py
+++ b/schematic/visualization/tangled_tree.py
@@ -1,41 +1,38 @@
+"""Tangled tree class"""
+
+# pylint: disable=logging-fstring-interpolation
+
 from io import StringIO
 import json
 import logging
-import networkx as nx
-import numpy as np
 import os
 from os import path
-import pandas as pd
+from typing import Optional, Any, Literal
 
-# allows specifying explicit variable types
-from typing import Any, Dict, Optional, Text, List
+import networkx as nx  # type: ignore
+from networkx.classes.reportviews import NodeView, EdgeDataView  # type: ignore
+import numpy as np
+import pandas as pd
 
-from schematic.utils.viz_utils import visualize
 from schematic.visualization.attributes_explorer import AttributesExplorer
-
 from schematic.schemas.data_model_parser import DataModelParser
 from schematic.schemas.data_model_graph import DataModelGraph, DataModelGraphExplorer
-from schematic.schemas.data_model_relationships import DataModelRelationships
-
-from schematic import LOADER
 from schematic.utils.io_utils import load_json
-from copy import deepcopy
-
-# Make sure to have newest version of decorator
+from schematic.utils.schema_utils import DisplayLabelType
 
 
 logger = logging.getLogger(__name__)
-#OUTPUT_DATA_DIR = str(Path('tests/data/visualization/AMPAD').resolve())
-#DATA_DIR = str(Path('tests/data').resolve())
 
-class TangledTree(object):
-    """
-    """
 
-    def __init__(self,
-                 path_to_json_ld: str,
-                 figure_type: str,
-                 ) -> None:
+class TangledTree:  # pylint: disable=too-many-instance-attributes
+    """Tangled tree class"""
+
+    def __init__(
+        self,
+        path_to_json_ld: str,
+        figure_type: str,
+        data_model_labels: DisplayLabelType,
+    ) -> None:
         # Load jsonld
         self.path_to_json_ld = path_to_json_ld
         self.json_data_model = load_json(self.path_to_json_ld)
@@ -44,13 +41,15 @@ def __init__(self,
         self.schema_name = path.basename(self.path_to_json_ld).split(".model.jsonld")[0]
 
         # Instantiate Data Model Parser
-        data_model_parser = DataModelParser(path_to_data_model = self.path_to_json_ld)
-        
-        #Parse Model
+        data_model_parser = DataModelParser(
+            path_to_data_model=self.path_to_json_ld,
+        )
+
+        # Parse Model
         parsed_data_model = data_model_parser.parse_model()
 
         # Instantiate DataModelGraph
-        data_model_grapher = DataModelGraph(parsed_data_model)
+        data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
         # Generate graph
         self.graph_data_model = data_model_grapher.generate_data_model_graph()
@@ -60,20 +59,34 @@ def __init__(self,
 
         # Set Parameters
         self.figure_type = figure_type.lower()
-        self.dependency_type = ''.join(('requires', self.figure_type.capitalize()))
+        self.dependency_type = "".join(("requires", self.figure_type.capitalize()))
 
         # Get names
         self.schema = load_json(self.path_to_json_ld)
-        self.schema_abbr = self.schema_name.split('_')[0]
+        self.schema_abbr = self.schema_name.split("_")[0]
 
         # Initialize AttributesExplorer
-        self.ae = AttributesExplorer(self.path_to_json_ld)
+        self.attributes_explorer = AttributesExplorer(
+            self.path_to_json_ld, data_model_labels
+        )
 
         # Create output paths.
-        self.text_csv_output_path = self.ae.create_output_path('text_csv')
-        self.json_output_path = self.ae.create_output_path('tangled_tree_json')
+        self.text_csv_output_path = self.attributes_explorer.create_output_path(
+            "text_csv"
+        )
+        self.json_output_path = self.attributes_explorer.create_output_path(
+            "tangled_tree_json"
+        )
+
+    def strip_double_quotes(self, string: str) -> str:
+        """Removes double quotes from string
 
-    def strip_double_quotes(self, string):
+        Args:
+            string (str): The string to remove quotes from
+
+        Returns:
+            str: The processed string
+        """
         # Remove double quotes from beginning and end of string.
         if string.startswith('"') and string.endswith('"'):
             string = string[1:-1]
@@ -81,8 +94,12 @@ def strip_double_quotes(self, string):
         string = "".join(string.split())
         return string
 
-    def get_text_for_tangled_tree(self, text_type, save_file=False):
-        '''Gather the text that needs to be either higlighted or plain for the tangled tree visualization.
+    def get_text_for_tangled_tree(
+        self, text_type: Literal["highlighted", "plain"], save_file: bool = False
+    ) -> Optional[str]:
+        """
+        Gather the text that needs to be either highlighted or plain for the
+          tangled tree visualization.
         Args:
             text_type (str): Choices = ['highlighted', 'plain'], determines the type of text
                 rendering to return.
@@ -90,184 +107,218 @@ def get_text_for_tangled_tree(self, text_type, save_file=False):
         Returns:
             If save_file==True: Saves plain or highlighted text as a CSV (to disk).
                save_file==False: Returns plain or highlighted text as a csv string.
-        '''
+        """
+        # pylint: disable=too-many-locals
         # Get nodes in the digraph, many more nodes returned if figure type is dependency
         cdg = self.dmge.get_digraph_by_edge_type(self.dependency_type)
         nodes = cdg.nodes()
 
-        if self.dependency_type == 'requiresComponent':
+        if self.dependency_type == "requiresComponent":
             component_nodes = nodes
         else:
             # get component nodes if making dependency figure
-            component_dg = self.dmge.get_digraph_by_edge_type('requiresComponent')
+            component_dg = self.dmge.get_digraph_by_edge_type("requiresComponent")
             component_nodes = component_dg.nodes()
 
         # Initialize lists
         highlighted = []
         plain = []
 
-        # For each component node in the tangled tree gather the plain and higlighted text.
+        # For each component node in the tangled tree gather the plain and highlighted text.
         for node in component_nodes:
             # Get the highlighted components based on figure_type
-            if self.figure_type == 'component':
-                highlight_descendants = self.dmge.get_descendants_by_edge_type(node, 'requiresComponent')
-            elif self.figure_type == 'dependency':
+            if self.figure_type == "component":
+                highlight_descendants = self.dmge.get_descendants_by_edge_type(
+                    node, "requiresComponent"
+                )
+            elif self.figure_type == "dependency":
                 highlight_descendants = [node]
 
-            
-            # Format text to be higlighted and gather text to be formated plain.
+            # Format text to be highlighted and gather text to be formatted plain.
             if not highlight_descendants:
-                # If there are no highlighted descendants just highlight the selected node (format for observable.)
+                # If there are no highlighted descendants just highlight the selected
+                # node (format for observable.)
                 highlighted.append([node, "id", node])
                 # Gather all the text as plain text.
                 plain_descendants = [n for n in nodes if n != node]
             else:
-                # Format higlighted text for Observable.
-                for hd in highlight_descendants:
-                    highlighted.append([node, "id", hd])
-                # Gather the non-higlighted text as plain text descendants.
-                plain_descendants = [node for node in nodes if node not in highlight_descendants]
-            
+                # Format highlighted text for Observable.
+                for descendant in highlight_descendants:
+                    highlighted.append([node, "id", descendant])
+                # Gather the non-highlighted text as plain text descendants.
+                plain_descendants = [
+                    node for node in nodes if node not in highlight_descendants
+                ]
+
             # Format all the plain text for observable.
-            for nd in plain_descendants:
-                plain.append([node, "id", nd])
+            for descendant in plain_descendants:
+                plain.append([node, "id", descendant])
 
         # Prepare df depending on what type of text we need.
-        df = pd.DataFrame(locals()[text_type.lower()], columns = ['Component', 'type', 'name'])
+        dataframe = pd.DataFrame(
+            locals()[text_type.lower()], columns=["Component", "type", "name"]
+        )
 
         # Depending on input either export csv locally to disk or as a string.
-        if save_file==True:
+        if save_file:
             file_name = f"{self.schema_abbr}_{self.figure_type}_{text_type}.csv"
-            df.to_csv(os.path.join(self.text_csv_output_path, file_name))
-            return
-        elif save_file==False:
-            return df.to_csv()
+            dataframe.to_csv(os.path.join(self.text_csv_output_path, file_name))
+            return None
+
+        return dataframe.to_csv()
 
-    def get_topological_generations(self):
-        ''' Gather topological_gen, nodes and edges based on figure type.
+    def get_topological_generations(
+        self,
+    ) -> tuple[list[list], NodeView, EdgeDataView, nx.DiGraph]:
+        """Gather topological_gen, nodes and edges based on figure type.
         Outputs:
             topological_gen (List(list)):list of lists. Indicates layers of nodes.
-            nodes: (Networkx NodeView) Nodes of the component or dependency graph. When iterated over it functions like a list.
-            edges: (Networkx EdgeDataView) Edges of component or dependency graph. When iterated over it works like a list of tuples.
-        '''
+            nodes: (Networkx NodeView) Nodes of the component or dependency graph.
+              When iterated over it functions like a list.
+            edges: (Networkx EdgeDataView) Edges of component or dependency graph.
+              When iterated over it works like a list of tuples.
+        """
         # Get nodes in the digraph
         digraph = self.dmge.get_digraph_by_edge_type(self.dependency_type)
         nodes = digraph.nodes()
 
         # Get subgraph
-        #mm_graph = self.sg.se.get_nx_schema()
-        #subg = self.sg.get_subgraph_by_edge_type(mm_graph, self.dependency_type)
-        subg = self.dmge.get_subgraph_by_edge_type(self.dependency_type)
+        subgraph = self.dmge.get_subgraph_by_edge_type(self.dependency_type)
 
         # Get edges and topological_gen based on figure type.
-        if self.figure_type == 'component':
+        if self.figure_type == "component":
             edges = digraph.edges()
-            topological_gen = list(reversed(list(nx.topological_generations(subg))))
+            topological_gen = list(reversed(list(nx.topological_generations(subgraph))))
 
-        elif self.figure_type == 'dependency':
+        elif self.figure_type == "dependency":
             rev_digraph = nx.DiGraph.reverse(digraph)
             edges = rev_digraph.edges()
-            topological_gen = list(nx.topological_generations(subg))
-        
-        return topological_gen, nodes, edges, subg
+            topological_gen = list(nx.topological_generations(subgraph))
+
+        return topological_gen, nodes, edges, subgraph
 
-    def remove_unwanted_characters_from_conditional_statement(self, cond_req: str) -> str:
-        '''Remove unwanted characters from conditional statement
-        Example of conditional requirement: If File Format IS "BAM" OR "CRAM" OR "CSV/TSV" then Genome Build is required
+    def remove_unwanted_characters_from_conditional_statement(
+        self, cond_req: str
+    ) -> str:
+        """Remove unwanted characters from conditional statement
+        Example of conditional requirement: If File Format IS "BAM" OR "CRAM" OR
+          "CSV/TSV" then Genome Build is required
         Example output: File Format IS "BAM" OR "CRAM" OR "CSV/TSV"
-        '''
+        """
         if "then" in cond_req:
             # remove everything after "then"
-            cond_req_new = cond_req.split('then')[0]
+            cond_req_new = cond_req.split("then")[0]
 
             # remove "If" and empty space
             cond_req = cond_req_new.replace("If", "").lstrip().rstrip()
         return cond_req
 
-    def get_ca_alias(self, conditional_requirements: list) -> dict:
-        '''Get the alias for each conditional attribute. 
+    def get_ca_alias(self, conditional_requirements: list) -> dict[str, str]:
+        """Get the alias for each conditional attribute.
 
-        NOTE: Obtaining attributes(attr) and aliases(ali) in this function is specific to how formatting
-            is set in AttributesExplorer. If that formatting changes, this section
-            will likely break or in the worst case have a silent error.         
+        NOTE: Obtaining attributes(attr) and aliases(ali) in this function is specific
+          to how formatting is set in AttributesExplorer. If that formatting changes,
+          this section will likely break or in the worst case have a silent error.
         Input:
-            conditional_requirements_list (list): list of strings of conditional requirements from outputs of AttributesExplorer.
+            conditional_requirements_list (list): list of strings of conditional
+              requirements from outputs of AttributesExplorer.
         Output:
             ca_alias (dict):
                 key: alias (attribute response)
                 value: attribute
-        '''
+        """
         ca_alias = {}
 
         # clean up conditional requirements
-        conditional_requirements = [self.remove_unwanted_characters_from_conditional_statement(req) for req in conditional_requirements]
+        conditional_requirements = [
+            self.remove_unwanted_characters_from_conditional_statement(req)
+            for req in conditional_requirements
+        ]
 
-        for i, req in enumerate(conditional_requirements):
+        for req in conditional_requirements:
             if "OR" not in req:
-                attr, ali = req.split(' is ')
+                attr, ali = req.split(" is ")
                 attr = "".join(attr.split())
                 ali = self.strip_double_quotes(ali)
                 ca_alias[ali] = attr
             else:
-                attr, alias_str = req.split(' is ')
-                alias_lst = alias_str.split(' OR ')
+                attr, alias_str = req.split(" is ")
+                alias_lst = alias_str.split(" OR ")
                 for elem in alias_lst:
                     elem = self.strip_double_quotes(elem)
                     ca_alias[elem] = attr
         return ca_alias
 
-    def gather_component_dependency_info(self, cn, attributes_df):
-        '''Gather all component dependency information.
+    def gather_component_dependency_info(
+        self, component_name: str, attributes_df: pd.DataFrame
+    ) -> tuple[list[str], dict[str, str], list[str]]:
+        """Gather all component dependency information.
         Inputs:
-            cn: (str) component name
-            attributes_df: (Pandas DataFrame) Details for all attributes across all components. From AttributesExplorer.
+            component name: (str) component name
+            attributes_df: (Pandas DataFrame) Details for all attributes across all components.
+              From AttributesExplorer.
         Outputs:
             conditional_attributes (list): List of conditional attributes for a particular component
             ca_alias (dict):
                 key: alias (attribute response)
                 value: attribute
             all_attributes (list): all attributes associated with a particular component.
-        '''
+        """
 
         # Gather all component dependency information
         component_attributes = self.dmge.get_descendants_by_edge_type(
-                                        cn,
-                                        self.dependency_type,
-                                        connected=True
-                                        )
-        
+            component_name, self.dependency_type, connected=True
+        )
+
         # Dont want to display `Component` in the figure so remove
-        if 'Component' in component_attributes:
-            component_attributes.remove('Component')
-        
+        if "Component" in component_attributes:
+            component_attributes.remove("Component")
+
         # Gather conditional attributes so they can be added to the figure.
-        if 'Cond_Req' in attributes_df.columns:
-            conditional_attributes = list(attributes_df[(attributes_df['Cond_Req']==True)
-                &(attributes_df['Component']==cn)]['Label'])
-            ca_df = attributes_df[(attributes_df['Cond_Req']==True)&(attributes_df['Component']==cn)]
-            conditional_requirements = list(attributes_df[(attributes_df['Cond_Req']==True)
-                &(attributes_df['Component']==cn)]['Conditional Requirements'])
+        if "Cond_Req" in attributes_df.columns:
+            conditional_attributes = list(
+                attributes_df[
+                    (attributes_df["Cond_Req"])
+                    & (attributes_df["Component"] == component_name)
+                ]["Label"]
+            )
+            conditional_requirements = list(
+                attributes_df[
+                    (attributes_df["Cond_Req"])
+                    & (attributes_df["Component"] == component_name)
+                ]["Conditional Requirements"]
+            )
             ca_alias = self.get_ca_alias(conditional_requirements)
         else:
             # If there are no conditional attributes/requirements, initialize blank lists.
             conditional_attributes = []
             ca_alias = {}
-        
+
         # Gather a list of all attributes for the current component.
-        all_attributes = list(np.append(component_attributes,conditional_attributes))
-        
+        all_attributes = list(np.append(component_attributes, conditional_attributes))
+
         return conditional_attributes, ca_alias, all_attributes
 
-    def find_source_nodes(self, nodes, edges, all_attributes=[]):
-        '''Find all nodes in the graph that do not have a parent node.
+    def find_source_nodes(
+        self,
+        nodes: NodeView,
+        edges: EdgeDataView,
+        all_attributes: Optional[list[str]] = None,
+    ) -> list[str]:
+        """Find all nodes in the graph that do not have a parent node.
         Inputs:
-            nodes: (Networkx NodeView) Nodes of the component or dependency graph. When iterated over it functions like a list.
-            edges: (Networkx EdgeDataView) Edges of component or dependency graph. When iterated over it works like a list of tuples.
-            attributes_df: (Pandas DataFrame) Details for all attributes across all components. From AttributesExplorer.
+            nodes: (Networkx NodeView) Nodes of the component or dependency graph.
+              When iterated over it functions like a list.
+            edges: (Networkx EdgeDataView) Edges of component or dependency graph.
+              When iterated over it works like a list of tuples.
+            attributes_df: (Pandas DataFrame) Details for all attributes across all
+              components. From AttributesExplorer.
 
         Outputs:
-            source_nodes (list(str)): List of parentless nodes in 
-        '''
+            source_nodes (list(str)): List of parentless nodes in
+        """
+        if all_attributes is None:
+            all_attributes = []
         # Find edges that are not source nodes.
         not_source = []
         for node in nodes:
@@ -278,7 +329,7 @@ def find_source_nodes(self, nodes, edges, all_attributes=[]):
         # Find source nodes as nodes that are not in not_source.
         source_nodes = []
         for node in nodes:
-            if self.figure_type == 'dependency':
+            if self.figure_type == "dependency":
                 if node not in not_source and node in all_attributes:
                     source_nodes.append(node)
             else:
@@ -286,118 +337,117 @@ def find_source_nodes(self, nodes, edges, all_attributes=[]):
                     source_nodes.append(node)
         return source_nodes
 
-    def get_parent_child_dictionary(self, nodes, edges, all_attributes=[]):
-        '''Based on the dependency type, create dictionaries between parent and child and child and parent attributes.
+    def get_parent_child_dictionary(
+        self, edges: EdgeDataView, all_attributes: Optional[list[str]] = None
+    ) -> tuple[dict[str, list[str]], dict[str, list[str]]]:
+        """
+        Based on the dependency type, create dictionaries between parent and
+          child and child and parent attributes.
         Input:
-            nodes: (Networkx NodeView) Nodes of the component or dependency graph.
             edges: (Networkx EdgeDataView (component figure) or List(list) (dependency figure))
                 Edges of component or dependency graph.
             all_attributes:
         Output:
             child_parents (dict):
                 key: child
-                value: list of the childs parents
+                value: list of the child's parents
             parent_children (dict):
                 key: parent
                 value: list of the parents children
-        '''
-        child_parents = {}
-        parent_children = {}
+        """
+        # pylint: disable=too-many-branches
+        all_attributes_list = [] if all_attributes is None else all_attributes
+        child_parents: dict[str, list[str]] = {}
+        parent_children: dict[str, list[str]] = {}
 
-        if self.dependency_type == 'requiresComponent':
-            
+        if self.dependency_type == "requiresComponent":
             # Construct child_parents dictionary
             for edge in edges:
-                
                 # Add child as a key
-                if edge[0] not in child_parents.keys():
+                if edge[0] not in child_parents:
                     child_parents[edge[0]] = []
-                
+
                 # Add parents to list
                 child_parents[edge[0]].append(edge[1])
-            
+
             # Construct parent_children dictionary
             for edge in edges:
-                
                 # Add parent as a key
-                if edge[1] not in parent_children.keys():
+                if edge[1] not in parent_children:
                     parent_children[edge[1]] = []
-                
+
                 # Add children to list
                 parent_children[edge[1]].append(edge[0])
-        
-        elif self.dependency_type == 'requiresDependency':
-            
+
+        elif self.dependency_type == "requiresDependency":
             # Construct child_parents dictionary
             for edge in edges:
-                
                 # Check if child is an attribute for the current component
-                if edge[0] in all_attributes:
-                    
+                if edge[0] in all_attributes_list:
                     # Add child as a key
-                    if edge[0] not in child_parents.keys():
+                    if edge[0] not in child_parents:
                         child_parents[edge[0]] = []
-                    
-                    # Add parent to list if it is an attriute for the current component
-                    if edge[1] in all_attributes:
+
+                    # Add parent to list if it is an attribute for the current component
+                    if edge[1] in all_attributes_list:
                         child_parents[edge[0]].append(edge[1])
-            
+
             # Construct parent_children dictionary
             for edge in edges:
-                
                 # Check if parent is an attribute for the current component
-                if edge[1] in all_attributes:
-                    
+                if edge[1] in all_attributes_list:
                     # Add parent as a key
-                    if edge[1] not in parent_children.keys():
+                    if edge[1] not in parent_children:
                         parent_children[edge[1]] = []
-                    
-                    # Add child to list if it is an attriute for the current component
-                    if edge[0] in all_attributes:
+
+                    # Add child to list if it is an attribute for the current component
+                    if edge[0] in all_attributes_list:
                         parent_children[edge[1]].append(edge[0])
 
         return child_parents, parent_children
 
-    def alias_edges(self, ca_alias:dict, edges) -> List[list]:
-        '''Create new edges based on aliasing between an attribute and its response.
+    def alias_edges(self, ca_alias: dict[str, str], edges: EdgeDataView) -> list[list]:
+        """Create new edges based on aliasing between an attribute and its response.
         Purpose:
             Create aliased edges.
-            For example: 
+            For example:
                 If BiospecimenType (attribute) is AnalyteBiospecimenType (response)
                 Then ShippingConditionType (conditional requirement) is now required.
             In the model the edges that connect these options are:
                 (AnalyteBiospecimenType, BiospecimenType)
                 (ShippingConditionType, AnalyteBiospecimenType)
-            Use alias defined in self.get_ca_alias along to define new edges that would 
-            directly link attributes to their conditional requirements, in this 
+            Use alias defined in self.get_ca_alias along to define new edges that would
+            directly link attributes to their conditional requirements, in this
             example the new edge would be:
                 [ShippingConditionType, BiospecimenType]
         Inputs:
             ca_alias (dict):
                 key: alias (attribute response)
                 value: attribute
-            edges (Networkx EdgeDataView): Edges of component or dependency graph. When iterated over it works like a list of tuples.
+            edges (Networkx EdgeDataView): Edges of component or dependency graph.
+              When iterated over it works like a list of tuples.
         Output:
-            aliased_edges (List[lists]) of aliased edges.
-        '''
+            aliased_edges (list[list]) of aliased edges.
+        """
         aliased_edges = []
-        for i, edge in enumerate(edges):
-            
+        for edge in edges:
             # construct one set of edges at a time
             edge_set = []
-            
-            # If the first edge has an alias add alias to the first position in the current edge set
+
+            # If the first edge has an alias add alias to the first
+            # position in the current edge set
             if edge[0] in ca_alias.keys():
                 edge_set.append(ca_alias[edge[0]])
-            
+
             # Else add the non-aliased edge
             else:
                 edge_set.append(edge[0])
 
-            # If the secod edge has an alias add alias to the first position in the current edge set
+            # If the second edge has an alias add alias to the first
+            # position in the current edge set
             if edge[1] in ca_alias.keys():
                 edge_set.append(ca_alias[edge[1]])
-            
+
             # Else add the non-aliased edge
             else:
                 edge_set.append(edge[1])
@@ -407,11 +457,16 @@ def alias_edges(self, ca_alias:dict, edges) -> List[list]:
 
         return aliased_edges
 
-    def prune_expand_topological_gen(self, topological_gen, all_attributes, conditional_attributes):
-        '''
+    def prune_expand_topological_gen(
+        self,
+        topological_gen: list[list[str]],
+        all_attributes: list[str],
+        conditional_attributes: list[str],
+    ) -> list[list[str]]:
+        """
         Purpose:
             Remake topological_gen with only relevant nodes.
-                This is necessary since for the figure this function is being used in we 
+                This is necessary since for the figure this function is being used in we
                 only want to display a portion of the graph data.
             In addition to only displaying relevant nodes, we want to add conditional
                 attributes to topological_gen so we can visualize them in the tangled tree
@@ -423,23 +478,22 @@ def prune_expand_topological_gen(self, topological_gen, all_attributes, conditio
         Output:
             new_top_gen (List[list]): mimics structure of topological_gen but only
                 includes the nodes we want
-        '''
+        """
 
         pruned_topological_gen = []
 
         # For each layer(gen) in the topological generation list
-        for i, layer in enumerate(topological_gen):
-            
+        for layer in topological_gen:
             current_layer = []
             next_layer = []
-            
+
             # For each node in the layer
             for node in layer:
-                
-                # If the node is relevant to this component and is not a conditional attribute add it to the current layer.
+                # If the node is relevant to this component and is not a conditional
+                # attribute add it to the current layer.
                 if node in all_attributes and node not in conditional_attributes:
                     current_layer.append(node)
-                
+
                 # If its a conditional attribute add it to a followup layer.
                 if node in conditional_attributes:
                     next_layer.append(node)
@@ -452,20 +506,26 @@ def prune_expand_topological_gen(self, topological_gen, all_attributes, conditio
 
         return pruned_topological_gen
 
-    def get_base_layers(self, topological_gen, child_parents, source_nodes, cn):
-        '''
+    def get_base_layers(
+        self,
+        topological_gen: list[list],
+        child_parents: dict,
+        source_nodes: list,
+        component_name: str,
+    ) -> tuple[dict[str, Any], dict[str, Any]]:
+        """
         Purpose:
-            Reconfigure topological gen to move things back appropriate layers if 
+            Reconfigure topological gen to move things back appropriate layers if
             they would have a back reference.
 
-            The Tangle Tree figure requrires an acyclic directed graph that has additional 
+            The Tangle Tree figure requires an acyclic directed graph that has additional
                 layering rules between connected nodes.
                 - If there is a backward connection then the line connecting them will
                     break (this would suggest a cyclic connection.)
-                - Additionally if two or more nodes are connecting to a downstream node it is 
-                    best to put both parent nodes at the same level, if possible, to 
+                - Additionally if two or more nodes are connecting to a downstream node it is
+                    best to put both parent nodes at the same level, if possible, to
                     prevent line breaks.
-                - Also want to move any children nodes one layer below 
+                - Also want to move any children nodes one layer below
                     the parent node(s). If there are multiple parents, put one layer below the
                     parent that is furthest from the origin.
 
@@ -475,344 +535,437 @@ def get_base_layers(self, topological_gen, child_parents, source_nodes, cn):
             topological_gen: list of lists. Indicates layers of nodes.
             child_parents (dict):
                 key: child
-                value: list of the childs parents
+                value: list of the child's parents
             source_nodes: list, list of nodes that do not have a parent.
-            cn: str, component name, default=''
+            component_name: str, component name, default=''
         Output:
             base_layers: dict, key: component name, value: layer
-                represents initial layering of toplogical_gen
+                represents initial layering of topological_gen
             base_layers_copy_copy: dict, key: component name, value: layer
                 represents the final layering after moving the components/attributes to
                 their desired layer.c
-        '''
+        """
         # Convert topological_gen to a dictionary
-        base_layers = {com:i for i, lev in enumerate(topological_gen)
-                                for com in lev}
-        
+        base_layers = {com: i for i, lev in enumerate(topological_gen) for com in lev}
+
         # Make another version to iterate on -- Cant set to equal or will overwrite the original.
-        base_layers_copy = {com:i for i, lev in enumerate(topological_gen)
-                                for com in lev}
+        base_layers_copy = {
+            com: i for i, lev in enumerate(topological_gen) for com in lev
+        }
 
         # Move child nodes one node downstream of their parents.
         for level in topological_gen:
             for node in level:
-                
                 # Check if node has a parent.
                 if node in child_parents.keys():
-                    
-                    #node_level = base_layers[node]
+                    # node_level = base_layers[node]
                     # Look at the parents for the node.
                     parent_levels = []
                     for par in child_parents[node]:
-                        
                         # Get the layer the parent is located at.
                         parent_levels.append(base_layers[par])
-                        
+
                         # Get the max layer a parent of the node can be found.
                         max_parent_level = max(parent_levels)
 
-                        # Move the node one layer beyond the max parent node position, so it will be downstream of its parents.
+                        # Move the node one layer beyond the max parent node position,
+                        # so it will be downstream of its parents.
                         base_layers_copy[node] = max_parent_level + 1
-        
+
         # Make another version of updated positions iterate on further.
         base_layers_copy_copy = base_layers_copy
 
         # Move parental source nodes if necessary.
         for level in topological_gen:
             for node in level:
-                
                 # Check if node has any parents.
                 if node in child_parents.keys():
                     parent_levels = []
                     modify_par = []
-                    
+
                     # For each parent get their position.
                     for par in child_parents[node]:
                         parent_levels.append(base_layers_copy[par])
-                    
-                    # If one of the parents is a source node move 
+
+                    # If one of the parents is a source node move
                     # it to the same level as the other nodes the child connects to so
                     # that the connections will not be backwards (and result in a broken line)
                     for par in child_parents[node]:
-                        
-                        # For a given parent determine if its a source node and that the parents 
-                        # are not already at level 0, and the parent is not the current component node.
-                        if (par in source_nodes and 
-                            (parent_levels.count(parent_levels[0]) != len(parent_levels))
-                            and par != cn):
-
+                        # For a given parent determine if its a source node and that the parents
+                        # are not already at level 0, and the parent is not the current component
+                        # node.
+                        if (
+                            par in source_nodes
+                            and (
+                                parent_levels.count(parent_levels[0])
+                                != len(parent_levels)
+                            )
+                            and par != component_name
+                        ):
                             # If so, remove its position from parent_levels
                             parent_levels.remove(base_layers_copy[par])
-                            
+
                             # Add this parent to a list of parental positions to modify later.
                             modify_par.append(par)
-                        
+
                         # Get the new max parent level for this node.
                         max_parent_level = max(parent_levels)
-                        
+
                         # Move the node one position downstream of its max parent level.
                         base_layers_copy_copy[node] = max_parent_level + 1
-                    
-                    # For each parental position to modify, move the parents level up to the max_parent_level.
+
+                    # For each parental position to modify, move the parents level up to
+                    # the max_parent_level.
                     for par in modify_par:
                         base_layers_copy_copy[par] = max_parent_level
-        
+
         return base_layers, base_layers_copy_copy
 
-    def adjust_node_placement(self, base_layers_copy_copy, base_layers, topological_gen):
-        '''Reorder nodes within topological_generations to match how they were ordered in base_layers_copy_copy
+    def adjust_node_placement(
+        self,
+        base_layers_copy_copy: dict[str, Any],
+        base_layers: dict[str, Any],
+        topological_gen: list[list],
+    ) -> list[list]:
+        """Reorder nodes within topological_generations to match how they were ordered in
+         base_layers_copy_copy
         Input:
             topological_gen: list of lists. Indicates layers of nodes.
             base_layers: dict, key: component name, value: layer
-                represents initial layering of toplogical_gen
+                represents initial layering of topological_gen
             base_layers_copy_copy: dict, key: component name, value: layer
                 represents the final layering after moving the components/attributes to
                 their desired layer.
         Output:
-            topological_gen: same format but as the incoming topologial_gen but
+            topological_gen: same format but as the incoming topological_gen but
                 ordered to match base_layers_copy_copy.
-        '''
-        if self.figure_type == 'component':
+        """
+        if self.figure_type == "component":
             # For each node get its new layer in the tangled tree
             for node, i in base_layers_copy_copy.items():
-                
                 # Check if node is not already in the proper layer
                 if node not in topological_gen[i]:
-
                     # If not put it in the appropriate layer
                     topological_gen[i].append(node)
-                    
+
                     # Remove from inappropriate layer.
                     topological_gen[base_layers[node]].remove(node)
-        
-        elif self.figure_type == 'dependency':
+
+        elif self.figure_type == "dependency":
             for node, i in base_layers_copy_copy.items():
-                
-                # Check if the location of the node is more than the number of 
+                # Check if the location of the node is more than the number of
                 # layers topological gen current handles
                 if i > len(topological_gen) - 1:
-
                     # If so, add node to new node at the end of topological_gen
                     topological_gen.append([node])
-                    
+
                     # Remove the node from its previous position.
                     topological_gen[base_layers[node]].remove(node)
-                
+
                 # Else, check if node is not already in the proper layer
                 elif node not in topological_gen[i]:
-
                     # If not put it in the appropriate layer
                     topological_gen[i].append(node)
-                    
+
                     # Remove from inappropriate layer.
                     topological_gen[base_layers[node]].remove(node)
         return topological_gen
 
-    def move_source_nodes_to_bottom_of_layer(self, node_layers, source_nodes):
-        '''For aesthetic purposes move source nodes to the bottom of their respective layers.
+    def move_source_nodes_to_bottom_of_layer(
+        self, node_layers: list[list], source_nodes: list
+    ) -> list[list]:
+        """For aesthetic purposes move source nodes to the bottom of their respective layers.
         Input:
-            node_layers (List(list)): Lists of lists of each layer and the nodes contained in that layer as strings.
+            node_layers (List(list)): Lists of lists of each layer and the nodes contained
+              in that layer as strings.
             source_nodes (list): list of nodes that do not have a parent.
         Output:
             node_layers (List(list)): modified to move source nodes to the bottom of each layer.
-        '''
-        for i, layer in enumerate(node_layers):
+        """
+        for layer in node_layers:
             nodes_to_move = []
             for node in layer:
                 if node in source_nodes:
                     nodes_to_move.append(node)
             for node in nodes_to_move:
-                node_layers[i].remove(node)
-                node_layers[i].append(node)
+                layer.remove(node)
+                layer.append(node)
         return node_layers
 
-    def get_layers_dict_list(self, node_layers, child_parents, parent_children, all_parent_children):
-        '''Convert node_layers to a list of lists of dictionaries that specifies each node and its parents (if applicable).
+    def get_layers_dict_list(
+        self,
+        node_layers: list[list],
+        child_parents: dict,
+        parent_children: dict,
+        all_parent_children: dict,
+    ) -> list[list[dict[str, list[str]]]]:
+        """Convert node_layers to a list of lists of dictionaries that specifies each node and
+         its parents (if applicable).
         Inputs:
-            node_layers: list of lists of each layer and the nodes contained in that layer as strings.
+            node_layers: list of lists of each layer and the nodes contained in that layer
+              as strings.
             child_parents (dict):
                 key: child
-                value: list of the childs parents
+                value: list of the child's parents
             parent_children (dict):
                 key: parent
                 value: list of the parents children
         Outputs:
-            layers_list (List(list): list of lists of dictionaries that specifies each node and its parents (if applicable)
-        '''
+            layers_list (List(list): list of lists of dictionaries that specifies each node and its
+             parents (if applicable)
+        """
         num_layers = len(node_layers)
-        layers_list = [[] for i in range(0, num_layers)]
+        layers_list: list[list[dict[str, list[str]]]] = [
+            [] for i in range(0, num_layers)
+        ]
         for i, layer in enumerate(node_layers):
             for node in layer:
                 if node in child_parents.keys():
                     parents = child_parents[node]
-                else: 
+                else:
                     parents = []
 
                 if node in parent_children.keys():
                     direct_children = parent_children[node]
-                else: 
+                else:
                     direct_children = []
 
                 if node in all_parent_children.keys():
                     all_children = all_parent_children[node]
-                else: 
+                else:
                     all_children = []
-                layers_list[i].append({'id': node, 'parents': parents, 'direct_children': direct_children, 'children': all_children})
+                layers_list[i].append(
+                    {
+                        "id": node,
+                        "parents": parents,
+                        "direct_children": direct_children,
+                        "children": all_children,
+                    }
+                )
 
         return layers_list
 
-    def get_node_layers_json(self, topological_gen, source_nodes, child_parents, parent_children, cn='', all_parent_children=None):
-        '''Return all the layers of a single tangled tree as a JSON String.
+    def get_node_layers_json(  # pylint: disable=too-many-arguments
+        self,
+        topological_gen: list[list],
+        source_nodes: list[str],
+        child_parents: dict,
+        parent_children: dict,
+        component_name: str = "",
+        all_parent_children: Optional[dict] = None,
+    ) -> str:
+        """Return all the layers of a single tangled tree as a JSON String.
         Inputs:
             topological_gen:list of lists. Indicates layers of nodes.
             source_nodes: list of nodes that do not have a parent.
             child_parents (dict):
                 key: child
-                value: list of the childs parents
+                value: list of the child's parents
             parent_children (dict):
                 key: parent
                 value: list of the parents children
             all_parent_children (dict):
                 key: parent
-                value: list of the parents children (including all downstream nodes). Default to an empty dictionary
+                value: list of the parents children (including all downstream nodes).
+                  Default to an empty dictionary
         Outputs:
             layers_json (JSON String): Layers of nodes in the tangled tree as a json string.
-        '''
+        """
 
-        base_layers, base_layers_copy_copy = self.get_base_layers(topological_gen, 
-                child_parents, source_nodes, cn)
+        base_layers, base_layers_copy_copy = self.get_base_layers(
+            topological_gen, child_parents, source_nodes, component_name
+        )
 
         # Rearrange node_layers to follow the pattern laid out in component layers.
-        node_layers = self.adjust_node_placement(base_layers_copy_copy, 
-            base_layers, topological_gen)
+        node_layers = self.adjust_node_placement(
+            base_layers_copy_copy, base_layers, topological_gen
+        )
 
         # Move source nodes to the bottom of each layer.
-        node_layers = self.move_source_nodes_to_bottom_of_layer(node_layers, source_nodes)
+        node_layers = self.move_source_nodes_to_bottom_of_layer(
+            node_layers, source_nodes
+        )
 
         # Convert layers to a list of dictionaries
         if not all_parent_children:
-            # default to an empty dictionary 
-            all_parent_children = dict()
-            
-        layers_dicts = self.get_layers_dict_list(node_layers, child_parents, parent_children, all_parent_children)
+            # default to an empty dictionary
+            all_parent_children = {}
+
+        layers_dicts = self.get_layers_dict_list(
+            node_layers, child_parents, parent_children, all_parent_children
+        )
 
         # Convert dictionary to a JSON string
         layers_json = json.dumps(layers_dicts)
 
         return layers_json
 
-    def save_outputs(self, save_file, layers_json, cn='', all_layers=None):
-        '''
+    def save_outputs(
+        self,
+        save_file: bool,
+        layers_json,
+        component_name: str = "",
+        all_layers: Optional[list[str]] = None,
+    ) -> list[str]:
+        """
         Inputs:
             save_file (bool): Indicates whether to save a file locally or not.:
             layers_json (JSON String): Layers of nodes in the tangled tree as a json string.
-            cn (str): component name, default=''
-            all_layers (list of json strings): Each string represents contains the layers for a single tangled tree.
-                If a dependency figure the list is added to each time this function is called, so starts incomplete.
-                default=[].
+            component_name (str): component name, default=''
+            all_layers (list of json strings): Each string represents contains the layers for
+                a single tangled tree. If a dependency figure the list is added to each time
+                this function is called, so starts incomplete. default=[].
         Outputs:
-            all_layers (list of json strings): 
-                If save_file == False: Each string represents contains the layers for a single tangled tree.
+            all_layers (list of json strings):
+                If save_file == False: Each string represents contains the layers for a single
+                 tangled tree.
                 If save_file ==True: is an empty list.
-        '''
-        if all_layers is None:
-            all_layers = []
-        if save_file == True:
-            if cn:
-                output_file_name = f"{self.schema_abbr}_{self.figure_type}_{cn}_tangled_tree.json"
+        """
+        all_layers_list = [] if all_layers is None else all_layers
+        if save_file:
+            if component_name:
+                output_file_name = (
+                    f"{self.schema_abbr}_{self.figure_type}_"
+                    f"{component_name}_tangled_tree.json"
+                )
             else:
-                output_file_name = f"{self.schema_abbr}_{self.figure_type}_tangled_tree.json"
-            with open(os.path.join(self.json_output_path, output_file_name), 'w') as outfile:
+                output_file_name = (
+                    f"{self.schema_abbr}_{self.figure_type}_tangled_tree.json"
+                )
+            with open(
+                os.path.join(self.json_output_path, output_file_name),
+                mode="w",
+                encoding="utf-8",
+            ) as outfile:
                 outfile.write(layers_json)
-            logger.info(f"Tangled Tree JSON String saved to {os.path.join(self.json_output_path, output_file_name)}.")
-            all_layers = layers_json
-        elif save_file == False:
-            all_layers.append(layers_json)
-        return all_layers
 
-    def get_ancestors_nodes(self, subgraph, components):
+            logger.info(
+                (
+                    "Tangled Tree JSON String saved to "
+                    f"{os.path.join(self.json_output_path, output_file_name)}"
+                )
+            )
+            all_layers_list = layers_json
+        else:
+            all_layers_list.append(layers_json)
+        return all_layers_list
+
+    def get_ancestors_nodes(
+        self, subgraph: nx.DiGraph, components: list[str]
+    ) -> dict[str, list[str]]:
         """
-        Inputs: 
+        Inputs:
             subgraph: networkX graph object
-            components: a list of nodes 
-        outputs: 
-            all_parent_children: a dictionary that indicates a list of children (including all the intermediate children) of a given node
+            components: a list of nodes
+        outputs:
+            all_parent_children: a dictionary that indicates a list of children
+              (including all the intermediate children) of a given node
         """
         all_parent_children = {}
-        for component in components: 
-            all_ancestors = self.dmge.get_nodes_ancestors(subgraph=subgraph, node_label=component)
+        for component in components:
+            all_ancestors = self.dmge.get_nodes_ancestors(
+                subgraph=subgraph, node_label=component
+            )
             all_parent_children[component] = all_ancestors
 
         return all_parent_children
 
-    def get_tangled_tree_layers(self, save_file=True):
-        '''Based on user indicated figure type, construct the layers of nodes of a tangled tree.
+    def get_tangled_tree_layers(self, save_file: bool = True):
+        """Based on user indicated figure type, construct the layers of nodes of a tangled tree.
         Inputs:
             save_file (bool): Indicates whether to save a file locally or not.
         Outputs:
-            all_layers (list of json strings): 
-                If save_file == False: Each string represents contains the layers for a single tangled tree.
+            all_layers (list of json strings):
+                If save_file == False: Each string represents contains the layers
+                  for a single tangled tree.
                 If save_file ==True: is an empty list.
 
         Note on Dependency Tangled Tree:
-            If there are many conditional requirements associated with a depependency, and those
+            If there are many conditional requirements associated with a dependency, and those
             conditional requirements have overlapping attributes associated with them
             the tangled tree will only report one
-        
-        '''
+
+        """
+        # pylint: disable=too-many-locals
         # Gather the data model's, topological generations, nodes and edges
-        topological_gen, nodes, edges, subg = self.get_topological_generations()
+        topological_gen, nodes, edges, subgraph = self.get_topological_generations()
 
-        if self.figure_type == 'component':
+        if self.figure_type == "component":
             # Gather all source nodes
             source_nodes = self.find_source_nodes(nodes, edges)
-            
+
             # Map all children to their parents and vice versa
-            child_parents, parent_children = self.get_parent_child_dictionary(nodes, edges)
+            child_parents, parent_children = self.get_parent_child_dictionary(
+                edges=edges
+            )
 
             # find all the downstream nodes
-            all_parent_children = self.get_ancestors_nodes(subg, parent_children.keys())
-            
+            all_parent_children = self.get_ancestors_nodes(
+                subgraph, parent_children.keys()
+            )
+
             # Get the layers that each node belongs to.
-            layers_json = self.get_node_layers_json(topological_gen, source_nodes, child_parents, parent_children, all_parent_children=all_parent_children)
+            layers_json = self.get_node_layers_json(
+                topological_gen,
+                source_nodes,
+                child_parents,
+                parent_children,
+                all_parent_children=all_parent_children,
+            )
 
             # If indicated save outputs locally else gather all layers.
-            all_layers = self.save_outputs(save_file, layers_json)         
+            all_layers = self.save_outputs(save_file, layers_json)
 
-        if self.figure_type == 'dependency':
+        if self.figure_type == "dependency":
             # Get component digraph and nodes.
-            component_dg = self.dmge.get_digraph_by_edge_type('requiresComponent')
+            component_dg = self.dmge.get_digraph_by_edge_type("requiresComponent")
             component_nodes = component_dg.nodes()
 
             # Get table of attributes.
-            attributes_csv_str = self.ae.parse_attributes(save_file=False)
+            attributes_csv_str = self.attributes_explorer.parse_attributes(
+                save_file=False
+            )
             attributes_df = pd.read_table(StringIO(attributes_csv_str), sep=",")
 
-            
-            all_layers =[]
-            for cn in component_nodes:
+            all_layers = []
+            for component_name in component_nodes:
                 # Gather attribute and dependency information per node
-                conditional_attributes, ca_alias, all_attributes = self.gather_component_dependency_info(cn, attributes_df)
+                (
+                    conditional_attributes,
+                    ca_alias,
+                    all_attributes,
+                ) = self.gather_component_dependency_info(component_name, attributes_df)
 
                 # Gather all source nodes
-                source_nodes = self.find_source_nodes(component_nodes, edges, all_attributes)
+                source_nodes = self.find_source_nodes(
+                    component_nodes, edges, all_attributes
+                )
 
                 # Alias the conditional requirement edge back to its actual parent label,
                 # then apply aliasing back to the edges
                 aliased_edges = self.alias_edges(ca_alias, edges)
 
                 # Gather relationships between children and their parents.
-                child_parents, parent_children = self.get_parent_child_dictionary(nodes,
-                    aliased_edges, all_attributes)
+                child_parents, parent_children = self.get_parent_child_dictionary(
+                    aliased_edges, all_attributes
+                )
 
                 # Remake topological_gen so it has only relevant nodes.
-                pruned_topological_gen = self.prune_expand_topological_gen(topological_gen, all_attributes, conditional_attributes)
+                pruned_topological_gen = self.prune_expand_topological_gen(
+                    topological_gen, all_attributes, conditional_attributes
+                )
 
                 # Get the layers that each node belongs to.
-                layers_json = self.get_node_layers_json(pruned_topological_gen, source_nodes, child_parents, parent_children, cn)
+                layers_json = self.get_node_layers_json(
+                    pruned_topological_gen,
+                    source_nodes,
+                    child_parents,
+                    parent_children,
+                    component_name,
+                )
 
                 # If indicated save outputs locally else, gather all layers.
-                all_layers = self.save_outputs(save_file, layers_json, cn, all_layers)
+                all_layers = self.save_outputs(
+                    save_file, layers_json, component_name, all_layers
+                )
         return all_layers
-
-   
\ No newline at end of file
diff --git a/schematic_api/api/README.md b/schematic_api/api/README.md
index 8e8f27fa5..0abddc730 100644
--- a/schematic_api/api/README.md
+++ b/schematic_api/api/README.md
@@ -22,7 +22,7 @@ docker compose up --build --remove-orphans
 ### install uWSGI
 Install uWSGI by doing: 
 ```
-poetry install --with aws
+poetry install --all-extras
 ```
 Note: this approach only works for unix OSs users or windows user with WSL
 
diff --git a/schematic_api/api/openapi/api.yaml b/schematic_api/api/openapi/api.yaml
index 7e4912e2c..50c0e3dc0 100644
--- a/schematic_api/api/openapi/api.yaml
+++ b/schematic_api/api/openapi/api.yaml
@@ -98,6 +98,18 @@ paths:
             default: True
           description: If using Google Sheets, can set the strictness of Google Sheets regex match validation. True (default) will block users from entering incorrect values, False will throw a warning to users.
           required: false
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
       operationId: schematic_api.api.routes.get_manifest_route
       responses:
         "200":
@@ -238,6 +250,18 @@ paths:
           description: Data Model Component
           example: Patient
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
         - in: query
           name: restrict_rules
           schema:
@@ -324,6 +348,18 @@ paths:
           example: >-
             https://raw.githubusercontent.com/Sage-Bionetworks/schematic/develop/tests/data/example.model.jsonld
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
         - in: query
           name: data_type
           schema:
@@ -374,7 +410,7 @@ paths:
             type: string
             nullable: false
           description: A JSON object
-          example: '[{
+          example: [{
           "Patient ID": 123,
           "Sex": "Female",
           "Year of Birth": "",
@@ -382,7 +418,7 @@ paths:
           "Component": "Patient",
           "Cancer Type": "Breast",
           "Family History": "Breast, Lung",
-          }]'
+          }]
         - in: query
           name: table_manipulation
           description: Specify the way the manifest tables should be store as on Synapse when one with the same name already exists. Options are 'replace' and 'upsert'.replace' will remove the rows and columns from the existing table and store the new rows and columns, preserving the name and synID.'upsert' will add the new rows to the table and preserve the exisitng rows and columns in the existing table. If nothing is selected, the default is "replace"
@@ -391,11 +427,20 @@ paths:
             enum: ["replace", "upsert"]
           required: false
         - in: query
-          name: use_schema_label
-          description: "Store attributes using the schema label (true, default) or store attributes using the display label (false). Attribute display names in the schema must not only include characters that are not accepted by Synapse. Annotation names may only contain: letters, numbers, '_' and '.'"
+          name: table_column_names
+          description: Specify how table column names should be formatted. display_name would use the raw attribute display name as the column name. display_label, would strip all blacklisted characters (including spaces) from the display name, while retaining the rest of the display name formatting (best used when display name is already in camelcase), class_label (default) converts the display name to upper camelcase and strips blacklisted characters.
           schema:
-            type: boolean
-            default: true
+            type: string
+            enum: ["display_name", "display_label", "class_label"]
+            default: "class_label"
+          required: false
+        - in: query
+          name: annotation_keys
+          description: Specify how table column names should be formatted. display_label, would strip all blacklisted characters (including spaces) from the display name, while retaining the rest of the display name formatting (best used when display name is already in camelcase), class_label (default) converts the display name to upper camelcase and strips blacklisted characters.
+          schema:
+            type: string
+            enum: ["display_label", "class_label"]
+            default: "class_label"
           required: false
         - in: query
           name: project_scope
@@ -446,6 +491,18 @@ paths:
             default: false
           description: if False return component requirements as a list; if True return component requirements as a dependency graph (i.e. a DAG)
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
       operationId: schematic_api.api.routes.get_component_requirements
       responses:
         "200":
@@ -479,6 +536,18 @@ paths:
           example: >-
             https://raw.githubusercontent.com/Sage-Bionetworks/schematic/develop/tests/data/example.model.jsonld
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
         - in: query
           name: data_type
           schema:
@@ -690,7 +759,7 @@ paths:
             type: string
             nullable: false
           description: Project ID
-          example: syn30988314
+          example: syn23643250
           required: true
         - in: query
           name: asset_view
@@ -787,6 +856,18 @@ paths:
           example: >-
             https://raw.githubusercontent.com/Sage-Bionetworks/schematic/develop/tests/data/example.model.jsonld
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
       responses:
         "200":
           description: A pickle file gets downloaded and local file path of the pickle file gets returned.
@@ -821,6 +902,18 @@ paths:
           description: schema class
           example: MolecularEntity
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
       responses:
         "200":
           description: A list of properties of a given class. 
@@ -849,7 +942,18 @@ paths:
             nullable: false
           description: Relationship (i.e. parentOf, requiresDependency, rangeValue, domainValue)
           example: requiresDependency
-          required: true        
+          required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
       responses:
         "200":
           description: A list of tuples.
@@ -890,6 +994,15 @@ paths:
           description: Display label of a node
           example: FamilyHistory
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.nclass_label, default, use standard class or property label. Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
       responses:
         "200":
           description: return a boolean 
@@ -922,6 +1035,18 @@ paths:
           description: List of node labels.
           example: ['FamilyHistory', 'Biospecimen']
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: false
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
       responses:
         "200":
           description: return List[str]
@@ -953,6 +1078,18 @@ paths:
           description: Display label of node
           example: CheckRegexList
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
       responses:
         "200":
           description: return a list
@@ -983,6 +1120,18 @@ paths:
           description: The node whose dependencies are needed
           example: Patient
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
         - in: query
           name: return_display_names
           schema:
@@ -1058,6 +1207,18 @@ paths:
           description: Node / term for which you need to retrieve the range.
           example: FamilyHistory
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
         - in: query
           name: return_display_names
           schema:
@@ -1096,6 +1257,18 @@ paths:
           description: Figure type to generate.
           example: 'component'
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
       responses:
         "200":
           description: Returns a dataframe as a JSON String.
@@ -1136,6 +1309,18 @@ paths:
           description: Text formatting type.
           example: 'plain'
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
       responses:
         "200":
           description: Returns a dataframe as a JSON String.
@@ -1161,6 +1346,18 @@ paths:
           example: >-
             https://raw.githubusercontent.com/Sage-Bionetworks/schematic/develop/tests/data/example.model.jsonld
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
       responses:
         "200":
           description: Returns a CSV as a JSON String.
@@ -1201,6 +1398,18 @@ paths:
             default: false
           description: Whether to include the indexes of the datafram in the returned JSON string (true) or not (false).
           required: true
+        - in: query
+          name: data_model_labels
+          schema:
+            type: string
+            nullable: true
+            enum: ["display_label", "class_label"]
+            default: 'class_label'
+          description: Choose how to set the label in the data model. 
+                  display_label, use the display name as a label, if it is valid (contains no blacklisted characters) otherwise will default to class_label.
+                  class_label, default, use standard class or property label.
+                  Do not change from default unless there is a real need, using 'display_label' can have consequences if not used properly.
+          required: false
       responses:
         "200":
           description: Returns a CSV as a JSON String.
@@ -1242,5 +1451,4 @@ paths:
         "500":
           description: Schematic version was not able to be identified.
       tags:
-        - Version
-        
\ No newline at end of file
+        - Version
\ No newline at end of file
diff --git a/schematic_api/api/routes.py b/schematic_api/api/routes.py
index 736a0c2db..c1b0f31c9 100644
--- a/schematic_api/api/routes.py
+++ b/schematic_api/api/routes.py
@@ -28,17 +28,23 @@
 
 from schematic.schemas.data_model_parser import DataModelParser
 from schematic.schemas.data_model_graph import DataModelGraph, DataModelGraphExplorer
-#from schematic.schemas.data_model_relationships import DataModelRelationships
 
 from schematic.store.synapse import SynapseStorage, ManifestDownload
-from synapseclient.core.exceptions import SynapseHTTPError, SynapseAuthenticationError, SynapseUnmetAccessRestrictions, SynapseNoCredentialsError, SynapseTimeoutError
+from synapseclient.core.exceptions import (
+    SynapseHTTPError,
+    SynapseAuthenticationError,
+    SynapseUnmetAccessRestrictions,
+    SynapseNoCredentialsError,
+    SynapseTimeoutError,
+)
 from schematic.utils.general import entity_type_mapping
-from schematic.utils.schema_utils import get_property_label_from_display_name
+from schematic.utils.schema_utils import get_property_label_from_display_name, DisplayLabelType
 
 logger = logging.getLogger(__name__)
 logging.basicConfig(level=logging.DEBUG)
 
-def config_handler(asset_view: str=None):
+
+def config_handler(asset_view: str = None):
     # check if path to config is provided
     path_to_config = app.config["SCHEMATIC_CONFIG"]
     if path_to_config is not None and os.path.isfile(path_to_config):
@@ -46,81 +52,83 @@ def config_handler(asset_view: str=None):
     if asset_view is not None:
         CONFIG.synapse_master_fileview_id = asset_view
 
+
 class JsonConverter:
-    '''
+    """
     Mainly handle converting json str or json file to csv
-    '''
+    """
+
     def readJson(self, json_str=None, manifest_file=None):
-        '''
+        """
         The purpose of this function is to read either json str or json file
-        input: 
+        input:
             json_str: json object
-            manifest_file: manifest file object 
-        output: 
+            manifest_file: manifest file object
+        output:
             return a dataframe
-        '''
+        """
         if json_str:
             df = pd.read_json(json_str)
-        elif manifest_file: 
+        elif manifest_file:
             df = pd.read_json(manifest_file.read())
         return df
-    
+
     def get_file(self, file_key):
-        '''
+        """
         The purpose of this function is to get the file uploaded by user
-        input: 
-            file_key: Defined in api.yaml. This key refers to the files uploaded. 
-            manifest_file: manifest file object 
-        output: 
+        input:
+            file_key: Defined in api.yaml. This key refers to the files uploaded.
+            manifest_file: manifest file object
+        output:
             return file object
-        '''
+        """
 
         manifest_file = connexion.request.files[file_key]
         return manifest_file
 
     def IsJsonFile(self, manifest_file):
-        '''
+        """
         The purpose of this function is check if the manifest file that gets uploaded is a json or not
-        input: 
-            manifest_file: manifest file object 
-        output: 
+        input:
+            manifest_file: manifest file object
+        output:
             return True if it is json
-        '''
+        """
 
         file_type = manifest_file.content_type
-        if file_type == 'application/json':
+        if file_type == "application/json":
             return True
-        else: 
+        else:
             return False
 
     def convert_df_to_csv(self, df, file_name):
-        '''
+        """
         The purpose of this function is to convert dataframe to a temporary CSV file
-        input: 
+        input:
             df: dataframe
             file_name: file name of the output csv
-        output: 
+        output:
             return temporary file path of the output csv
-        '''
+        """
 
         # convert dataframe to a temporary csv file
         temp_dir = tempfile.gettempdir()
         temp_path = os.path.join(temp_dir, file_name)
-        df.to_csv(temp_path, encoding = 'utf-8', index=False)
+        df.to_csv(temp_path, encoding="utf-8", index=False)
         return temp_path
 
     def convert_json_str_to_csv(self, json_str, file_name):
-        '''
+        """
         The purpose of this function is to convert json str to a temporary csv file
-        input: 
+        input:
             json_str: json object
             file_name: file name of the output csv
-        output: 
+        output:
             return temporary file path of the output csv
-        '''
+        """
 
         # convert json to df
-        df = self.readJson(json_str = json_str)
+        df = self.readJson(json_str=json_str)
 
         # convert dataframe to a temporary csv file
         temp_path = self.convert_df_to_csv(df, file_name)
@@ -128,31 +136,32 @@ def convert_json_str_to_csv(self, json_str, file_name):
         return temp_path
 
     def convert_json_file_to_csv(self, file_key):
-        '''
+        """
         The purpose of this function is to convert json str to a temporary csv file
-        input: 
-            file_key: Defined in api.yaml. This key refers to the files uploaded. 
-        output: 
+        input:
+            file_key: Defined in api.yaml. This key refers to the files uploaded.
+        output:
             return temporary file path of the output csv
-        '''
+        """
 
         # get manifest file
         manifest_file = self.get_file(file_key)
 
         if self.IsJsonFile(manifest_file):
             # read json as dataframe
-            df = self.readJson(manifest_file = manifest_file)
+            df = self.readJson(manifest_file=manifest_file)
             # get base file name
             base = os.path.splitext(manifest_file.filename)[0]
-            # name the new csv file 
-            new_file_name = base + '.csv'
+            # name the new csv file
+            new_file_name = base + ".csv"
             # convert to csv
             temp_path = self.convert_df_to_csv(df, new_file_name)
             return temp_path
-        else: 
-            temp_path = save_file(file_key='file_name')
+        else:
+            temp_path = save_file(file_key="file_name")
             return temp_path
 
+
 def get_access_token() -> str:
     """Get access token from header"""
     bearer_token = None
@@ -164,28 +173,31 @@ def get_access_token() -> str:
         if auth_header.startswith("Bearer "):
             bearer_token = auth_header.split(" ")[1]
     return bearer_token
-        
+
+
 def parse_bool(str_bool):
-    if str_bool.lower().startswith('t'):
+    if str_bool.lower().startswith("t"):
         return True
-    elif str_bool.lower().startswith('f'):
+    elif str_bool.lower().startswith("f"):
         return False
     else:
         raise ValueError(
             "String boolean does not appear to be true or false. Please verify input."
         )
 
+
 def return_as_json(manifest_local_file_path):
     manifest_csv = pd.read_csv(manifest_local_file_path)
     manifest_json = manifest_csv.to_dict(orient="records")
     return manifest_json
 
+
 def save_file(file_key="csv_file"):
-    '''
-    input: 
+    """
+    input:
         file_key: Defined in api.yaml. This key refers to the files uploaded. By default, set to "csv_file"
     Return a temporary file path for the uploaded a given file
-    '''
+    """
     manifest_file = connexion.request.files[file_key]
 
     # save contents of incoming manifest CSV file to temp file
@@ -197,25 +209,31 @@ def save_file(file_key="csv_file"):
 
     return temp_path
 
-def initalize_metadata_model(schema_url):
+
+def initalize_metadata_model(schema_url, data_model_labels):
     # get path to temp data model file (csv or jsonld) as appropriate
     data_model = get_temp_model_path(schema_url)
 
-    
     metadata_model = MetadataModel(
-        inputMModelLocation=data_model, inputMModelLocationType="local"
+        inputMModelLocation=data_model,
+        inputMModelLocationType="local",
+        data_model_labels=data_model_labels,
     )
     return metadata_model
 
+
 def get_temp_jsonld(schema_url):
     # retrieve a JSON-LD via URL and store it in a temporary location
     with urllib.request.urlopen(schema_url) as response:
-        with tempfile.NamedTemporaryFile(delete=False, suffix=".model.jsonld") as tmp_file:
+        with tempfile.NamedTemporaryFile(
+            delete=False, suffix=".model.jsonld"
+        ) as tmp_file:
             shutil.copyfileobj(response, tmp_file)
 
     # get path to temporary JSON-LD file
     return tmp_file.name
 
+
 def get_temp_csv(schema_url):
     # retrieve a CSV via URL and store it in a temporary location
     with urllib.request.urlopen(schema_url) as response:
@@ -225,187 +243,221 @@ def get_temp_csv(schema_url):
     # get path to temporary csv file
     return tmp_file.name
 
+
 def get_temp_model_path(schema_url):
     # Get model type:
-    model_extension = pathlib.Path(schema_url).suffix.replace('.', '').upper()
-    if model_extension == 'CSV':
+    model_extension = pathlib.Path(schema_url).suffix.replace(".", "").upper()
+    if model_extension == "CSV":
         temp_path = get_temp_csv(schema_url)
-    elif model_extension == 'JSONLD':
+    elif model_extension == "JSONLD":
         temp_path = get_temp_jsonld(schema_url)
     else:
-        raise ValueError("Did not provide a valid model type CSV or JSONLD, please check submission and try again.")
+        raise ValueError(
+            "Did not provide a valid model type CSV or JSONLD, please check submission and try again."
+        )
     return temp_path
 
 
 # @before_request
-def get_manifest_route(schema_url: str, use_annotations: bool, dataset_ids=None, asset_view = None, output_format=None, title=None, strict_validation:bool=True):
+def get_manifest_route(
+    schema_url: str,
+    use_annotations: bool,
+    dataset_id=None,
+    asset_view=None,
+    output_format=None,
+    title=None,
+    strict_validation: bool = True,
+    data_model_labels: DisplayLabelType = "class_label",
+    data_type: str = None,
+):
     """Get the immediate dependencies that are related to a given source node.
-        Args:
-            schema_url: link to data model in json ld or csv format
-            title: title of a given manifest. 
-            dataset_id: Synapse ID of the "dataset" entity on Synapse (for a given center/project).
-            output_format: contains three option: "excel", "google_sheet", and "dataframe". if set to "excel", return an excel spreadsheet
-            use_annotations: Whether to use existing annotations during manifest generation
-            asset_view: ID of view listing all project data assets. For example, for Synapse this would be the Synapse ID of the fileview listing all data assets for a given project.
-            strict: bool, strictness with which to apply validation rules to google sheets.
-        Returns:
-            Googlesheet URL (if sheet_url is True), or pandas dataframe (if sheet_url is False).
+    Args:
+        schema_url: link to data model in json ld or csv format
+        title: title of a given manifest.
+        dataset_id: Synapse ID of the "dataset" entity on Synapse (for a given center/project).
+        data_type: data model components.
+        output_format: contains three option: "excel", "google_sheet", and "dataframe". if set to "excel", return an excel spreadsheet
+        use_annotations: Whether to use existing annotations during manifest generation
+        asset_view: ID of view listing all project data assets. For example, for Synapse this would be the Synapse ID of the fileview listing all data assets for a given project.
+        strict: bool, strictness with which to apply validation rules to google sheets.
+    Returns:
+        Googlesheet URL (if sheet_url is True), or pandas dataframe (if sheet_url is False).
     """
 
     # Get access token from request header
     access_token = get_access_token()
 
-    # call config_handler()
-    config_handler(asset_view = asset_view)
-    
-    temp_path = get_temp_model_path(schema_url=schema_url)
+    config_handler(asset_view=asset_view)
 
-    # Gather all data_types to make manifests for.
-    all_args = connexion.request.args
-    args_dict = dict(all_args.lists())
-    data_type = args_dict['data_type']
+    all_results = ManifestGenerator.create_manifests(
+        path_to_data_model=schema_url,
+        output_format=output_format,
+        data_types=data_type,
+        title=title,
+        access_token=access_token,
+        dataset_ids=dataset_id,
+        strict=strict_validation,
+        use_annotations=use_annotations,
+        data_model_labels=data_model_labels,
+    )
+
+    # return an excel file if output_format is set to "excel"
+    if output_format == "excel":
+        # should only contain one excel spreadsheet path
+        if len(all_results) > 0:
+            result = all_results[0]
+            dir_name = os.path.dirname(result)
+            file_name = os.path.basename(result)
+            mimetype = (
+                "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+            )
+            return send_from_directory(
+                directory=dir_name,
+                path=file_name,
+                as_attachment=True,
+                mimetype=mimetype,
+                max_age=0,
+            )
 
-    # Gather all dataset_ids
-    try:
-        dataset_ids = args_dict['dataset_id']
-    except:
-        pass
-    
-    if dataset_ids:
-        # Check that the number of submitted data_types matches
-        # the number of dataset_ids (if applicable)
-        len_data_types = len(data_type)
-        len_dataset_ids = len(dataset_ids)
-        
-        try:
-            len_data_types == len_dataset_ids
-        except:
-            raise ValueError(
-                    f"There is a mismatch in the number of data_types and dataset_id's that "
-                    f"submitted. Please check your submission and try again."
-                )
-        
-        # Raise an error if used in conjunction with datatype = 'all_manifests'
-        try:
-            data_type[0] != 'all manifests'
-        except:
-            raise ValueError(
-                    f"When submitting 'all manifests' as the data_type cannot also submit dataset_id. "
-                    f"Please check your submission and try again."
-                )
-      
-    all_results = ManifestGenerator.create_manifests(path_to_data_model=schema_url, output_format=output_format, data_types=data_type, title=title, access_token=access_token, dataset_ids=dataset_ids, strict=strict_validation, use_annotations=use_annotations)
-    
     return all_results
 
-#####profile validate manifest route function 
-#@profile(sort_by='cumulative', strip_dirs=True)
-def validate_manifest_route(schema_url, data_type, restrict_rules=None, json_str=None, asset_view=None, project_scope = None):
+
+#####profile validate manifest route function
+# @profile(sort_by='cumulative', strip_dirs=True)
+def validate_manifest_route(
+    schema_url,
+    data_type,
+    data_model_labels,
+    restrict_rules=None,
+    json_str=None,
+    asset_view=None,
+    project_scope=None,
+):
     # Access token now stored in request header
     access_token = get_access_token()
-    
+
     # if restrict rules is set to None, default it to False
     if not restrict_rules:
-        restrict_rules=False
-        
+        restrict_rules = False
+
     # call config_handler()
-    config_handler(asset_view = asset_view)
+    config_handler(asset_view=asset_view)
 
-    #If restrict_rules parameter is set to None, then default it to False 
+    # If restrict_rules parameter is set to None, then default it to False
     if not restrict_rules:
         restrict_rules = False
 
-    #Get path to temp file where manifest file contents will be saved
+    # Get path to temp file where manifest file contents will be saved
     jsc = JsonConverter()
 
     if json_str:
-        temp_path = jsc.convert_json_str_to_csv(json_str = json_str, file_name = "example_json")
-    else: 
+        temp_path = jsc.convert_json_str_to_csv(
+            json_str=json_str, file_name="example_json"
+        )
+    else:
         temp_path = jsc.convert_json_file_to_csv("file_name")
 
     # get path to temp data model file (csv or jsonld) as appropriate
     data_model = get_temp_model_path(schema_url)
 
     metadata_model = MetadataModel(
-        inputMModelLocation=data_model, inputMModelLocationType="local"
+        inputMModelLocation=data_model,
+        inputMModelLocationType="local",
+        data_model_labels=data_model_labels,
     )
 
     errors, warnings = metadata_model.validateModelManifest(
-        manifestPath=temp_path, rootNode=data_type, restrict_rules=restrict_rules, project_scope=project_scope, access_token=access_token
+        manifestPath=temp_path,
+        rootNode=data_type,
+        restrict_rules=restrict_rules,
+        project_scope=project_scope,
+        access_token=access_token,
     )
-    
+
     res_dict = {"errors": errors, "warnings": warnings}
 
     return res_dict
 
-#####profile validate manifest route function 
-#@profile(sort_by='cumulative', strip_dirs=True)
-def submit_manifest_route(schema_url, 
-                          asset_view=None, 
-                          manifest_record_type=None, 
-                          json_str=None, 
-                          table_manipulation=None, 
-                          data_type=None, 
-                          hide_blanks=False, 
-                          project_scope=None,
-                          ):
+
+#####profile validate manifest route function
+# @profile(sort_by='cumulative', strip_dirs=True)
+def submit_manifest_route(
+    schema_url,
+    data_model_labels: str,
+    asset_view=None,
+    manifest_record_type=None,
+    json_str=None,
+    table_manipulation=None,
+    data_type=None,
+    hide_blanks=False,
+    project_scope=None,
+    table_column_names=None,
+    annotation_keys=None,
+):
     # call config_handler()
-    config_handler(asset_view = asset_view)
+    config_handler(asset_view=asset_view)
 
     # convert Json file to CSV if applicable
     jsc = JsonConverter()
     if json_str:
-        temp_path = jsc.convert_json_str_to_csv(json_str = json_str, file_name = "example_json.csv")
-    else: 
+        temp_path = jsc.convert_json_str_to_csv(
+            json_str=json_str, file_name="example_json.csv"
+        )
+    else:
         temp_path = jsc.convert_json_file_to_csv("file_name")
 
+    # Get/parse parameters from the API
+
     dataset_id = connexion.request.args["dataset_id"]
 
     restrict_rules = parse_bool(connexion.request.args["restrict_rules"])
 
-    metadata_model = initalize_metadata_model(schema_url)
-
-    # Access token now stored in request header
-    access_token = get_access_token()
-
-
-    use_schema_label = connexion.request.args["use_schema_label"]
-    if use_schema_label == 'None':
-        use_schema_label = True
-    else:
-        use_schema_label = parse_bool(use_schema_label)
-
-    if not table_manipulation: 
+    if not table_manipulation:
         table_manipulation = "replace"
 
     if not manifest_record_type:
         manifest_record_type = "table_file_and_entities"
 
-    if data_type == 'None':
+    if data_type == "None":
         validate_component = None
     else:
         validate_component = data_type
-    
+
     # get path to temp data model file (csv or jsonld) as appropriate
     data_model = get_temp_model_path(schema_url)
 
+    if not table_column_names:
+        table_column_names = "class_label"
+
+    if not annotation_keys:
+        annotation_keys = "class_label"
+
+    metadata_model = initalize_metadata_model(schema_url, data_model_labels)
+
+    # Access token now stored in request header
+    access_token = get_access_token()
+
     manifest_id = metadata_model.submit_metadata_manifest(
-        path_to_json_ld = data_model, 
-        manifest_path=temp_path, 
-        dataset_id=dataset_id, 
-        validate_component=validate_component, 
-        access_token=access_token, 
-        manifest_record_type = manifest_record_type, 
-        restrict_rules = restrict_rules, 
+        path_to_json_ld=data_model,
+        manifest_path=temp_path,
+        dataset_id=dataset_id,
+        validate_component=validate_component,
+        access_token=access_token,
+        manifest_record_type=manifest_record_type,
+        restrict_rules=restrict_rules,
         hide_blanks=hide_blanks,
-        table_manipulation = table_manipulation, 
-        use_schema_label=use_schema_label,
+        table_manipulation=table_manipulation,
         project_scope=project_scope,
-        )
+        table_column_names=table_column_names,
+        annotation_keys=annotation_keys,
+    )
 
     return manifest_id
 
-def populate_manifest_route(schema_url, title=None, data_type=None, return_excel=None):
+
+def populate_manifest_route(
+    schema_url, data_model_labels: str, title=None, data_type=None, return_excel=None
+):
     # call config_handler()
     config_handler()
 
@@ -414,30 +466,41 @@ def populate_manifest_route(schema_url, title=None, data_type=None, return_excel
 
     # get path to temp data model file (csv or jsonld) as appropriate
     data_model = get_temp_model_path(schema_url)
-   
-    #Initalize MetadataModel
-    metadata_model = MetadataModel(inputMModelLocation=data_model, inputMModelLocationType='local')
 
-    #Call populateModelManifest class
-    populated_manifest_link = metadata_model.populateModelManifest(title=title, manifestPath=temp_path, rootNode=data_type, return_excel=return_excel)
+    # Initalize MetadataModel
+    metadata_model = MetadataModel(
+        inputMModelLocation=data_model,
+        inputMModelLocationType="local",
+        data_model_labels=data_model_labels,
+    )
+
+    # Call populateModelManifest class
+    populated_manifest_link = metadata_model.populateModelManifest(
+        title=title,
+        manifestPath=temp_path,
+        rootNode=data_type,
+        return_excel=return_excel,
+    )
 
     return populated_manifest_link
 
+
 def get_storage_projects(asset_view):
     # Access token now stored in request header
     access_token = get_access_token()
 
-    # call config handler 
+    # call config handler
     config_handler(asset_view=asset_view)
 
-    # use Synapse storage 
+    # use Synapse storage
     store = SynapseStorage(access_token=access_token)
 
     # call getStorageProjects function
     lst_storage_projects = store.getStorageProjects()
-    
+
     return lst_storage_projects
 
+
 def get_storage_projects_datasets(asset_view, project_id):
     # Access token now stored in request header
     access_token = get_access_token()
@@ -449,10 +512,11 @@ def get_storage_projects_datasets(asset_view, project_id):
     store = SynapseStorage(access_token=access_token)
 
     # call getStorageDatasetsInProject function
-    sorted_dataset_lst = store.getStorageDatasetsInProject(projectId = project_id)
-    
+    sorted_dataset_lst = store.getStorageDatasetsInProject(projectId=project_id)
+
     return sorted_dataset_lst
 
+
 def get_files_storage_dataset(asset_view, dataset_id, full_path, file_names=None):
     # Access token now stored in request header
     access_token = get_access_token()
@@ -464,18 +528,21 @@ def get_files_storage_dataset(asset_view, dataset_id, full_path, file_names=None
     store = SynapseStorage(access_token=access_token)
 
     # no file names were specified (file_names = [''])
-    if file_names and not all(file_names): 
-        file_names=None
-    
+    if file_names and not all(file_names):
+        file_names = None
+
     # call getFilesInStorageDataset function
-    file_lst = store.getFilesInStorageDataset(datasetId=dataset_id, fileNames=file_names, fullpath=full_path)
+    file_lst = store.getFilesInStorageDataset(
+        datasetId=dataset_id, fileNames=file_names, fullpath=full_path
+    )
     return file_lst
 
+
 def check_if_files_in_assetview(asset_view, entity_id):
     # Access token now stored in request header
     access_token = get_access_token()
-    
-    # call config handler 
+
+    # call config handler
     config_handler(asset_view=asset_view)
 
     # use Synapse Storage
@@ -486,65 +553,80 @@ def check_if_files_in_assetview(asset_view, entity_id):
 
     return if_exists
 
+
 def check_entity_type(entity_id):
     # Access token now stored in request header
     access_token = get_access_token()
-        
-    # call config handler 
+
+    # call config handler
     config_handler()
 
-    syn = SynapseStorage.login(access_token = access_token)
+    syn = SynapseStorage.login(access_token=access_token)
     entity_type = entity_type_mapping(syn, entity_id)
 
-    return entity_type 
+    return entity_type
 
-def get_component_requirements(schema_url, source_component, as_graph):
-    metadata_model = initalize_metadata_model(schema_url)
 
-    req_components = metadata_model.get_component_requirements(source_component=source_component, as_graph = as_graph)
+def get_component_requirements(
+    schema_url, source_component, as_graph, data_model_labels
+):
+    metadata_model = initalize_metadata_model(schema_url, data_model_labels)
+    req_components = metadata_model.get_component_requirements(
+        source_component=source_component, as_graph=as_graph
+    )
 
     return req_components
 
+
 @cross_origin(["http://localhost", "https://sage-bionetworks.github.io"])
-def get_viz_attributes_explorer(schema_url):
+def get_viz_attributes_explorer(schema_url, data_model_labels):
     # call config_handler()
     config_handler()
 
     # get path to temp data model file (csv or jsonld) as appropriate
     data_model = get_temp_model_path(schema_url)
 
-    attributes_csv = AttributesExplorer(data_model).parse_attributes(save_file=False)
+    attributes_csv = AttributesExplorer(data_model, data_model_labels).parse_attributes(
+        save_file=False
+    )
 
     return attributes_csv
 
-def get_viz_component_attributes_explorer(schema_url, component, include_index):
+
+def get_viz_component_attributes_explorer(
+    schema_url, component, include_index, data_model_labels
+):
     # call config_handler()
     config_handler()
 
-     # get path to temp data model file (csv or jsonld) as appropriate
+    # get path to temp data model file (csv or jsonld) as appropriate
     data_model = get_temp_model_path(schema_url)
 
-    attributes_csv = AttributesExplorer(data_model).parse_component_attributes(component, save_file=False, include_index=include_index)
+    attributes_csv = AttributesExplorer(
+        data_model, data_model_labels
+    ).parse_component_attributes(
+        component, save_file=False, include_index=include_index
+    )
 
     return attributes_csv
 
+
 @cross_origin(["http://localhost", "https://sage-bionetworks.github.io"])
-def get_viz_tangled_tree_text(schema_url, figure_type, text_format):
-   
-     # get path to temp data model file (csv or jsonld) as appropriate
+def get_viz_tangled_tree_text(schema_url, figure_type, text_format, data_model_labels):
+    # get path to temp data model file (csv or jsonld) as appropriate
     data_model = get_temp_model_path(schema_url)
 
     # Initialize TangledTree
-    tangled_tree = TangledTree(data_model, figure_type)
+    tangled_tree = TangledTree(data_model, figure_type, data_model_labels)
 
     # Get text for tangled tree.
     text_df = tangled_tree.get_text_for_tangled_tree(text_format, save_file=False)
-    
+
     return text_df
 
-@cross_origin(["http://localhost", "https://sage-bionetworks.github.io"])
-def get_viz_tangled_tree_layers(schema_url, figure_type):
 
+@cross_origin(["http://localhost", "https://sage-bionetworks.github.io"])
+def get_viz_tangled_tree_layers(schema_url, figure_type, data_model_labels):
     # call config_handler()
     config_handler()
 
@@ -552,21 +634,22 @@ def get_viz_tangled_tree_layers(schema_url, figure_type):
     data_model = get_temp_model_path(schema_url)
 
     # Initialize Tangled Tree
-    tangled_tree = TangledTree(data_model, figure_type)
-    
+    tangled_tree = TangledTree(data_model, figure_type, data_model_labels)
+
     # Get tangled trees layers JSON.
     layers = tangled_tree.get_tangled_tree_layers(save_file=False)
 
     return layers[0]
 
-def download_manifest(manifest_id, new_manifest_name='', as_json=True):
+
+def download_manifest(manifest_id, new_manifest_name="", as_json=True):
     """
-    Download a manifest based on a given manifest id. 
+    Download a manifest based on a given manifest id.
     Args:
         manifest_syn_id: syn id of a manifest
         newManifestName: new name of a manifest that gets downloaded.
         as_json: boolean; If true, return a manifest as a json. Default to True
-    Return: 
+    Return:
         file path of the downloaded manifest
     """
     # Access token now stored in request header
@@ -577,24 +660,25 @@ def download_manifest(manifest_id, new_manifest_name='', as_json=True):
 
     # use login method in synapse storage
     syn = SynapseStorage.login(access_token=access_token)
-    try: 
+    try:
         md = ManifestDownload(syn, manifest_id)
         manifest_data = ManifestDownload.download_manifest(md, new_manifest_name)
-        #return local file path
-        manifest_local_file_path = manifest_data['path']
+        # return local file path
+        manifest_local_file_path = manifest_data["path"]
     except TypeError as e:
-        raise TypeError(f'Failed to download manifest {manifest_id}.')
+        raise TypeError(f"Failed to download manifest {manifest_id}.")
     if as_json:
         manifest_json = return_as_json(manifest_local_file_path)
         return manifest_json
     else:
         return manifest_local_file_path
 
-#@profile(sort_by='cumulative', strip_dirs=True)  
-def download_dataset_manifest(dataset_id, asset_view, as_json, new_manifest_name=''):
+
+# @profile(sort_by='cumulative', strip_dirs=True)
+def download_dataset_manifest(dataset_id, asset_view, as_json, new_manifest_name=""):
     # Access token now stored in request header
     access_token = get_access_token()
-        
+
     # call config handler
     config_handler(asset_view=asset_view)
 
@@ -602,22 +686,25 @@ def download_dataset_manifest(dataset_id, asset_view, as_json, new_manifest_name
     store = SynapseStorage(access_token=access_token)
 
     # download existing file
-    manifest_data = store.getDatasetManifest(datasetId=dataset_id, downloadFile=True, newManifestName=new_manifest_name)
+    manifest_data = store.getDatasetManifest(
+        datasetId=dataset_id, downloadFile=True, newManifestName=new_manifest_name
+    )
 
-    #return local file path
+    # return local file path
     try:
-        manifest_local_file_path = manifest_data['path']
+        manifest_local_file_path = manifest_data["path"]
 
     except KeyError as e:
-        raise KeyError(f'Failed to download manifest from dataset: {dataset_id}') from e
+        raise KeyError(f"Failed to download manifest from dataset: {dataset_id}") from e
 
-    #return a json (if as_json = True)
+    # return a json (if as_json = True)
     if as_json:
         manifest_json = return_as_json(manifest_local_file_path)
         return manifest_json
 
     return manifest_local_file_path
 
+
 def get_asset_view_table(asset_view, return_type):
     # Access token now stored in request header
     access_token = get_access_token()
@@ -637,30 +724,30 @@ def get_asset_view_table(asset_view, return_type):
         return json_res
     else:
         path = os.getcwd()
-        export_path = os.path.join(path, 'tests/data/file_view_table.csv')
+        export_path = os.path.join(path, "tests/data/file_view_table.csv")
         file_view_table_df.to_csv(export_path, index=False)
         return export_path
 
-
 def get_project_manifests(project_id, asset_view):
     # Access token now stored in request header
     access_token = get_access_token()
-        
+
     # use the default asset view from config
     config_handler(asset_view=asset_view)
 
     # use Synapse Storage
-    store = SynapseStorage(access_token=access_token)
+    store = SynapseStorage(access_token=access_token, project_scope=[project_id])
 
     # call getprojectManifest function
     lst_manifest = store.getProjectManifests(projectId=project_id)
 
     return lst_manifest
 
+
 def get_manifest_datatype(manifest_id, asset_view):
     # Access token now stored in request header
     access_token = get_access_token()
-    
+
     # use the default asset view from config
     config_handler(asset_view=asset_view)
 
@@ -668,48 +755,48 @@ def get_manifest_datatype(manifest_id, asset_view):
     store = SynapseStorage(access_token=access_token)
 
     # get data types of an existing manifest
-    manifest_dtypes_dict= store.getDataTypeFromManifest(manifest_id)
-
+    manifest_dtypes_dict = store.getDataTypeFromManifest(manifest_id)
 
     return manifest_dtypes_dict
 
-def get_schema_pickle(schema_url):
-    data_model_parser = DataModelParser(path_to_data_model = schema_url)
-    #Parse Model
+
+def get_schema_pickle(schema_url, data_model_labels):
+    data_model_parser = DataModelParser(path_to_data_model=schema_url)
+    # Parse Model
     parsed_data_model = data_model_parser.parse_model()
 
     # Instantiate DataModelGraph
-    data_model_grapher = DataModelGraph(parsed_data_model)
+    data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
     # Generate graph
     graph_data_model = data_model_grapher.generate_data_model_graph()
 
     # write to local pickle file
     path = os.getcwd()
-    export_path = os.path.join(path, 'tests/data/schema.gpickle')
+    export_path = os.path.join(path, "tests/data/schema.gpickle")
 
-    with open(export_path, 'wb') as file:
+    with open(export_path, "wb") as file:
         pickle.dump(graph_data_model, file)
     return export_path
 
 
-def get_subgraph_by_edge_type(schema_url, relationship):
-    data_model_parser = DataModelParser(path_to_data_model = schema_url)
-    
-    #Parse Model
+def get_subgraph_by_edge_type(schema_url, relationship, data_model_labels):
+    data_model_parser = DataModelParser(path_to_data_model=schema_url)
+
+    # Parse Model
     parsed_data_model = data_model_parser.parse_model()
 
     # Instantiate DataModelGraph
-    data_model_grapher = DataModelGraph(parsed_data_model)
+    data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
     # Generate graph
     graph_data_model = data_model_grapher.generate_data_model_graph()
 
     dmge = DataModelGraphExplorer(graph_data_model)
-    
+
     # relationship subgraph
     relationship_subgraph = dmge.get_subgraph_by_edge_type(relationship)
-    # return relationship 
+    # return relationship
     Arr = []
     for t in relationship_subgraph.edges:
         lst = list(t)
@@ -718,13 +805,13 @@ def get_subgraph_by_edge_type(schema_url, relationship):
     return Arr
 
 
-def find_class_specific_properties(schema_url, schema_class):
-    data_model_parser = DataModelParser(path_to_data_model = schema_url)
-    #Parse Model
+def find_class_specific_properties(schema_url, schema_class, data_model_labels):
+    data_model_parser = DataModelParser(path_to_data_model=schema_url)
+    # Parse Model
     parsed_data_model = data_model_parser.parse_model()
 
     # Instantiate DataModelGraph
-    data_model_grapher = DataModelGraph(parsed_data_model)
+    data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
     # Generate graph
     graph_data_model = data_model_grapher.generate_data_model_graph()
@@ -740,8 +827,9 @@ def find_class_specific_properties(schema_url, schema_class):
 def get_node_dependencies(
     schema_url: str,
     source_node: str,
+    data_model_labels: str,
     return_display_names: bool = True,
-    return_schema_ordered: bool = True
+    return_schema_ordered: bool = True,
 ) -> list[str]:
     """Get the immediate dependencies that are related to a given source node.
 
@@ -760,18 +848,18 @@ def get_node_dependencies(
     Returns:
         list[str]: List of nodes that are dependent on the source node.
     """
-    data_model_parser = DataModelParser(path_to_data_model = schema_url)
-    #Parse Model
+    data_model_parser = DataModelParser(path_to_data_model=schema_url)
+    # Parse Model
     parsed_data_model = data_model_parser.parse_model()
 
     # Instantiate DataModelGraph
-    data_model_grapher = DataModelGraph(parsed_data_model)
+    data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
     # Generate graph
     graph_data_model = data_model_grapher.generate_data_model_graph()
 
     dmge = DataModelGraphExplorer(graph_data_model)
-    
+
     dependencies = dmge.get_node_dependencies(
         source_node, return_display_names, return_schema_ordered
     )
@@ -779,8 +867,7 @@ def get_node_dependencies(
 
 
 def get_property_label_from_display_name_route(
-    display_name: str,
-    strict_camel_case: bool = False
+    display_name: str, strict_camel_case: bool = False
 ) -> str:
     """Converts a given display name string into a proper property label string
 
@@ -793,14 +880,17 @@ def get_property_label_from_display_name_route(
     Returns:
         str: The property label of the display name
     """
-    label = get_property_label_from_display_name(display_name=display_name, strict_camel_case=strict_camel_case)
+    label = get_property_label_from_display_name(
+        display_name=display_name, strict_camel_case=strict_camel_case
+    )
     return label
 
 
 def get_node_range(
     schema_url: str,
     node_label: str,
-    return_display_names: bool = True
+    data_model_labels: str,
+    return_display_names: bool = True,
 ) -> list[str]:
     """Get the range, i.e., all the valid values that are associated with a node label.
 
@@ -813,12 +903,12 @@ def get_node_range(
     Returns:
         list[str]: A list of nodes
     """
-    data_model_parser = DataModelParser(path_to_data_model = schema_url)
-    #Parse Model
+    data_model_parser = DataModelParser(path_to_data_model=schema_url)
+    # Parse Model
     parsed_data_model = data_model_parser.parse_model()
 
     # Instantiate DataModelGraph
-    data_model_grapher = DataModelGraph(parsed_data_model)
+    data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
     # Generate graph
     graph_data_model = data_model_grapher.generate_data_model_graph()
@@ -828,7 +918,10 @@ def get_node_range(
     node_range = dmge.get_node_range(node_label, return_display_names)
     return node_range
 
-def get_if_node_required(schema_url: str, node_display_name: str) -> bool:
+
+def get_if_node_required(
+    schema_url: str, node_display_name: str, data_model_labels: str
+) -> bool:
     """Check if the node is required
 
     Args:
@@ -839,12 +932,12 @@ def get_if_node_required(schema_url: str, node_display_name: str) -> bool:
         True: If the given node is a "required" node.
         False: If the given node is not a "required" (i.e., an "optional") node.
     """
-    data_model_parser = DataModelParser(path_to_data_model = schema_url)
-    #Parse Model
+    data_model_parser = DataModelParser(path_to_data_model=schema_url)
+    # Parse Model
     parsed_data_model = data_model_parser.parse_model()
 
     # Instantiate DataModelGraph
-    data_model_grapher = DataModelGraph(parsed_data_model)
+    data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
     # Generate graph
     graph_data_model = data_model_grapher.generate_data_model_graph()
@@ -855,7 +948,10 @@ def get_if_node_required(schema_url: str, node_display_name: str) -> bool:
 
     return is_required
 
-def get_node_validation_rules(schema_url: str, node_display_name: str) -> list:
+
+def get_node_validation_rules(
+    schema_url: str, node_display_name: str, data_model_labels: str
+) -> list:
     """
     Args:
         schema_url (str): Data Model URL
@@ -864,53 +960,57 @@ def get_node_validation_rules(schema_url: str, node_display_name: str) -> list:
         List of valiation rules for a given node.
     """
     # Instantiate DataModelParser
-    data_model_parser = DataModelParser(path_to_data_model = schema_url)
-    
-    #Parse Model
+    data_model_parser = DataModelParser(path_to_data_model=schema_url)
+
+    # Parse Model
     parsed_data_model = data_model_parser.parse_model()
 
     # Instantiate DataModelGraph
-    data_model_grapher = DataModelGraph(parsed_data_model)
+    data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
     # Generate graph
     graph_data_model = data_model_grapher.generate_data_model_graph()
 
-    #Instantiate DataModelGraphExplorer
+    # Instantiate DataModelGraphExplorer
     dmge = DataModelGraphExplorer(graph_data_model)
 
     node_validation_rules = dmge.get_node_validation_rules(node_display_name)
 
     return node_validation_rules
 
-def get_nodes_display_names(schema_url: str, node_list: list[str]) -> list:
+
+def get_nodes_display_names(
+    schema_url: str, node_list: list[str], data_model_labels: str
+) -> list:
     """From a list of node labels retrieve their display names, return as list.
-    
+
     Args:
         schema_url (str): Data Model URL
         node_list (List[str]): List of node labels.
-        
+
     Returns:
         node_display_names (List[str]): List of node display names.
 
     """
     # Instantiate DataModelParser
-    data_model_parser = DataModelParser(path_to_data_model = schema_url)
-    
-    #Parse Model
+    data_model_parser = DataModelParser(path_to_data_model=schema_url)
+
+    # Parse Model
     parsed_data_model = data_model_parser.parse_model()
 
     # Instantiate DataModelGraph
-    data_model_grapher = DataModelGraph(parsed_data_model)
+    data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
     # Generate graph
     graph_data_model = data_model_grapher.generate_data_model_graph()
 
-    #Instantiate DataModelGraphExplorer
+    # Instantiate DataModelGraphExplorer
     dmge = DataModelGraphExplorer(graph_data_model)
 
     node_display_names = dmge.get_nodes_display_names(node_list)
     return node_display_names
 
+
 def get_schematic_version() -> str:
     """
     Return the current version of schematic
@@ -921,4 +1021,4 @@ def get_schematic_version() -> str:
         raise NotImplementedError(
             "Using this endpoint to check the version of schematic is only supported when the API is running in a docker container."
         )
-    return version
+    return version
\ No newline at end of file
diff --git a/tests/conftest.py b/tests/conftest.py
index 55d100310..6f72cf596 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -33,6 +33,7 @@
 TESTS_DIR = os.path.dirname(os.path.abspath(__file__))
 DATA_DIR = os.path.join(TESTS_DIR, "data")
 
+
 @pytest.fixture(scope="session")
 def dataset_id():
     yield "syn25614635"
@@ -57,59 +58,67 @@ def get_data_frame(path, *paths, **kwargs):
         return load_df(fullpath, **kwargs)
 
     @staticmethod
-    def get_data_model_graph_explorer(path=None, *paths):
-        #commenting this now bc we dont want to have multiple instances
+    def get_data_model_graph_explorer(
+        path=None, data_model_labels: str = "class_label", *paths
+    ):
+        # commenting this now bc we dont want to have multiple instances
         if path is None:
             return
 
         fullpath = Helpers.get_data_path(path, *paths)
 
         # Instantiate DataModelParser
-        data_model_parser = DataModelParser(path_to_data_model = fullpath)
-        
-        #Parse Model
+        data_model_parser = DataModelParser(
+            path_to_data_model=fullpath,
+        )
+
+        # Parse Model
         parsed_data_model = data_model_parser.parse_model()
 
         # Instantiate DataModelGraph
-        data_model_grapher = DataModelGraph(parsed_data_model)
+        data_model_grapher = DataModelGraph(
+            parsed_data_model, data_model_labels=data_model_labels
+        )
 
         # Generate graph
         graph_data_model = data_model_grapher.generate_data_model_graph()
 
-        #Instantiate DataModelGraphExplorer
+        # Instantiate DataModelGraphExplorer
         DMGE = DataModelGraphExplorer(graph_data_model)
 
         return DMGE
 
     @staticmethod
     def get_python_version():
-        version=sys.version
-        base_version=".".join(version.split('.')[0:2])
+        version = sys.version
+        base_version = ".".join(version.split(".")[0:2])
 
         return base_version
 
     @staticmethod
     def get_python_project(self):
-
         version = self.get_python_version()
 
         python_projects = {
-            "3.7":  "syn47217926",
-            "3.8":  "syn47217967",
-            "3.9":  "syn47218127",
+            "3.7": "syn47217926",
+            "3.8": "syn47217967",
+            "3.9": "syn47218127",
             "3.10": "syn47218347",
         }
 
         return python_projects[version]
 
+
 @pytest.fixture(scope="session")
 def helpers():
     yield Helpers
 
+
 @pytest.fixture(scope="session")
 def config():
     yield CONFIG
 
+
 @pytest.fixture(scope="session")
 def synapse_store(request):
     access_token = os.getenv("SYNAPSE_ACCESS_TOKEN")
diff --git a/tests/data/example.model.csv b/tests/data/example.model.csv
index 6858e509c..f49aa8d3a 100644
--- a/tests/data/example.model.csv
+++ b/tests/data/example.model.csv
@@ -1,7 +1,7 @@
 Attribute,Description,Valid Values,DependsOn,Properties,Required,Parent,DependsOn Component,Source,Validation Rules
 Component,,,,,TRUE,,,,
 Patient,,,"Patient ID, Sex, Year of Birth, Diagnosis, Component",,FALSE,DataType,,,
-Patient ID,,,,,TRUE,DataProperty,,,
+Patient ID,,,,,TRUE,DataProperty,,,#Patient unique warning^^#Biospecimen unique error
 Sex,,"Female, Male, Other",,,TRUE,DataProperty,,,
 Year of Birth,,,,,FALSE,DataProperty,,,
 Diagnosis,,"Healthy, Cancer",,,TRUE,DataProperty,,,
@@ -42,4 +42,4 @@ Check Date,,,,,TRUE,DataProperty,,,date
 Check NA,,,,,TRUE,DataProperty,,,int::IsNA
 MockRDB,,,"Component, MockRDB_id, SourceManifest",,FALSE,DataType,,,
 MockRDB_id,,,,,TRUE,DataProperty,,,int
-SourceManifest,,,,,TRUE,DataProperty,,,
+SourceManifest,,,,,TRUE,DataProperty,,,
\ No newline at end of file
diff --git a/tests/data/example.model.jsonld b/tests/data/example.model.jsonld
index a58d36323..9724e341d 100644
--- a/tests/data/example.model.jsonld
+++ b/tests/data/example.model.jsonld
@@ -73,7 +73,10 @@
             },
             "sms:displayName": "Patient ID",
             "sms:required": "sms:true",
-            "sms:validationRules": []
+            "sms:validationRules": {
+                "Biospecimen": "unique error",
+                "Patient": "unique warning"
+            }
         },
         {
             "@id": "bts:Sex",
diff --git a/tests/data/example.single_rule.model.jsonld b/tests/data/example.single_rule.model.jsonld
index 738bba05e..24da12094 100644
--- a/tests/data/example.single_rule.model.jsonld
+++ b/tests/data/example.single_rule.model.jsonld
@@ -7,1971 +7,6 @@
         "xsd": "http://www.w3.org/2001/XMLSchema#"
     },
     "@graph": [
-        {
-            "@id": "schema:Text",
-            "@type": [
-                "schema:DataType",
-                "rdfs:Class"
-            ],
-            "rdfs:comment": "Data type: Text.",
-            "rdfs:label": "Text"
-        },
-        {
-            "@id": "schema:Number",
-            "@type": [
-                "schema:DataType",
-                "rdfs:Class"
-            ],
-            "rdfs:comment": "Data type: Number.",
-            "rdfs:label": "Number"
-        },
-        {
-            "@id": "schema:Integer",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "Data type: Integer.",
-            "rdfs:label": "Integer",
-            "rdfs:subClassOf": {
-                "@id": "schema:Number"
-            }
-        },
-        {
-            "@id": "schema:Thing",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "Thing",
-            "rdfs:label": "Thing",
-            "schema:isPartOf": {
-                "@id": "http://schema.org"
-            }
-        },
-        {
-            "@id": "bts:BiologicalEntity",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "BiologicalEntity",
-            "rdfs:subClassOf": {
-                "@id": "schema:Thing"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:OntologyClass",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "a concept or class in an ontology, vocabulary or thesaurus",
-            "rdfs:label": "OntologyClass",
-            "rdfs:subClassOf": {
-                "@id": "schema:Thing"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:RelationshipType",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "An OWL property used as an edge label",
-            "rdfs:label": "RelationshipType",
-            "rdfs:subClassOf": {
-                "@id": "bts:OntologyClass"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:GeneOntologyClass",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "an ontology class that describes a functional aspect of a gene, gene prodoct or complex",
-            "rdfs:label": "GeneOntologyClass",
-            "rdfs:subClassOf": {
-                "@id": "bts:OntologyClass"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:OrganismTaxon",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "OrganismTaxon",
-            "rdfs:subClassOf": {
-                "@id": "bts:OntologyClass"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:OrganismalEntity",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A named entity that is either a part of an organism, a whole organism, population or clade of organisms, excluding molecular entities",
-            "rdfs:label": "OrganismalEntity",
-            "rdfs:subClassOf": {
-                "@id": "bts:BiologicalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:IndividualOrganism",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "IndividualOrganism",
-            "rdfs:subClassOf": {
-                "@id": "bts:OrganismalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:Case",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "An individual organism that has a patient role in some clinical context.",
-            "rdfs:label": "Case",
-            "rdfs:subClassOf": {
-                "@id": "bts:IndividualOrganism"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:PopulationOfIndividualOrganisms",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "PopulationOfIndividualOrganisms",
-            "rdfs:subClassOf": {
-                "@id": "bts:OrganismalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:Biosample",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "Biosample",
-            "rdfs:subClassOf": {
-                "@id": "bts:OrganismalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:DiseaseOrPhenotypicFeature",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "Either one of a disease or an individual phenotypic feature. Some knowledge resources such as Monarch treat these as distinct, others such as MESH conflate.",
-            "rdfs:label": "DiseaseOrPhenotypicFeature",
-            "rdfs:subClassOf": {
-                "@id": "bts:BiologicalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:Disease",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "Disease",
-            "rdfs:subClassOf": {
-                "@id": "bts:DiseaseOrPhenotypicFeature"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:PhenotypicFeature",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "PhenotypicFeature",
-            "rdfs:subClassOf": {
-                "@id": "bts:DiseaseOrPhenotypicFeature"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:Environment",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A feature of the environment of an organism that influences one or more phenotypic features of that organism, potentially mediated by genes",
-            "rdfs:label": "Environment",
-            "rdfs:subClassOf": {
-                "@id": "bts:BiologicalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:InformationContentEntity",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "a piece of information that typically describes some piece of biology or is used as support.",
-            "rdfs:label": "InformationContentEntity",
-            "rdfs:subClassOf": {
-                "@id": "schema:Thing"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:ConfidenceLevel",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "Level of confidence in a statement",
-            "rdfs:label": "ConfidenceLevel",
-            "rdfs:subClassOf": {
-                "@id": "bts:InformationContentEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:EvidenceType",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "Class of evidence that supports an association",
-            "rdfs:label": "EvidenceType",
-            "rdfs:subClassOf": {
-                "@id": "bts:InformationContentEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:Publication",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "Any published piece of information. Can refer to a whole publication, or to a part of it (e.g. a figure, figure legend, or section highlighted by NLP). The scope is intended to be general and include information published on the web as well as journals.",
-            "rdfs:label": "Publication",
-            "rdfs:subClassOf": {
-                "@id": "bts:InformationContentEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:MolecularEntity",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A gene, gene product, small molecule or macromolecule (including protein complex)",
-            "rdfs:label": "MolecularEntity",
-            "rdfs:subClassOf": {
-                "@id": "bts:BiologicalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:ChemicalSubstance",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "May be a chemical entity or a formulation with a chemical entity as active ingredient, or a complex material with multiple chemical entities as part",
-            "rdfs:label": "ChemicalSubstance",
-            "rdfs:subClassOf": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:Drug",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A substance intended for use in the diagnosis, cure, mitigation, treatment, or prevention of disease",
-            "rdfs:label": "Drug",
-            "rdfs:subClassOf": {
-                "@id": "bts:ChemicalSubstance"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:Metabolite",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "Any intermediate or product resulting from metabolism. Includes primary and secondary metabolites.",
-            "rdfs:label": "Metabolite",
-            "rdfs:subClassOf": {
-                "@id": "bts:ChemicalSubstance"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:AnatomicalEntity",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A subcellular location, cell type or gross anatomical part",
-            "rdfs:label": "AnatomicalEntity",
-            "rdfs:subClassOf": {
-                "@id": "bts:OrganismalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:LifeStage",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A stage of development or growth of an organism, including post-natal adult stages",
-            "rdfs:label": "LifeStage",
-            "rdfs:subClassOf": {
-                "@id": "bts:OrganismalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:PlanetaryEntity",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "Any entity or process that exists at the level of the whole planet",
-            "rdfs:label": "PlanetaryEntity",
-            "rdfs:subClassOf": {
-                "@id": "schema:Thing"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:EnvironmentalProcess",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "EnvironmentalProcess",
-            "rdfs:subClassOf": {
-                "@id": "bts:PlanetaryEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:EnvironmentalFeature",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "EnvironmentalFeature",
-            "rdfs:subClassOf": {
-                "@id": "bts:PlanetaryEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:ClinicalEntity",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "Any entity or process that exists in the clinical domain and outside the biological realm. Diseases are placed under biological entities",
-            "rdfs:label": "ClinicalEntity",
-            "rdfs:subClassOf": {
-                "@id": "schema:Thing"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:ClinicalTrial",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "ClinicalTrial",
-            "rdfs:subClassOf": {
-                "@id": "bts:ClinicalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:ClinicalIntervention",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "ClinicalIntervention",
-            "rdfs:subClassOf": {
-                "@id": "bts:ClinicalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:Device",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A thing made or adapted for a particular purpose, especially a piece of mechanical or electronic equipment",
-            "rdfs:label": "Device",
-            "rdfs:subClassOf": {
-                "@id": "schema:Thing"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:GenomicEntity",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "an entity that can either be directly located on a genome (gene, transcript, exon, regulatory region) or is encoded in a genome (protein)",
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-            "rdfs:subClassOf": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:Genome",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A genome is the sum of genetic material within a cell or virion.",
-            "rdfs:label": "Genome",
-            "rdfs:subClassOf": {
-                "@id": "bts:GenomicEntity"
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-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        },
-        {
-            "@id": "bts:Transcript",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "An RNA synthesized on a DNA or RNA template by an RNA polymerase",
-            "rdfs:label": "Transcript",
-            "rdfs:subClassOf": {
-                "@id": "bts:GenomicEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        },
-        {
-            "@id": "bts:Exon",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A region of the transcript sequence within a gene which is not removed from the primary RNA transcript by RNA splicing",
-            "rdfs:label": "Exon",
-            "rdfs:subClassOf": {
-                "@id": "bts:GenomicEntity"
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-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        {
-            "@id": "bts:CodingSequence",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "CodingSequence",
-            "rdfs:subClassOf": {
-                "@id": "bts:GenomicEntity"
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-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        {
-            "@id": "bts:MacromolecularMachine",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A union of gene, gene product, and macromolecular complex. These are the basic units of function in a cell. They either carry out individual biological activities, or they encode molecules which do this.",
-            "rdfs:label": "MacromolecularMachine",
-            "rdfs:subClassOf": {
-                "@id": "bts:GenomicEntity"
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-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        },
-        {
-            "@id": "bts:GeneOrGeneProduct",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "a union of genes or gene products. Frequently an identifier for one will be used as proxy for another",
-            "rdfs:label": "GeneOrGeneProduct",
-            "rdfs:subClassOf": {
-                "@id": "bts:MacromolecularMachine"
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-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "Gene",
-            "rdfs:subClassOf": {
-                "@id": "bts:GeneOrGeneProduct"
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-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        {
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-            "@type": "rdfs:Class",
-            "rdfs:comment": "The functional molecular product of a single gene. Gene products are either proteins or functional RNA molecules",
-            "rdfs:label": "GeneProduct",
-            "rdfs:subClassOf": {
-                "@id": "bts:GeneOrGeneProduct"
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-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        {
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-            "@type": "rdfs:Class",
-            "rdfs:comment": "A gene product that is composed of a chain of amino acid sequences and is produced by ribosome-mediated translation of mRNA",
-            "rdfs:label": "Protein",
-            "rdfs:subClassOf": {
-                "@id": "bts:GeneProduct"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:GeneProductIsoform",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "This is an abstract class that can be mixed in with different kinds of gene products to indicate that the gene product is intended to represent a specific isoform rather than a canonical or reference or generic product. The designation of canonical or reference may be arbitrary, or it may represent the superclass of all isoforms.",
-            "rdfs:label": "GeneProductIsoform",
-            "rdfs:subClassOf": {
-                "@id": "bts:GeneProduct"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:ProteinIsoform",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "Represents a protein that is a specific isoform of the canonical or reference protein. See https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4114032/",
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-            "rdfs:subClassOf": {
-                "@id": "bts:Protein"
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-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        {
-            "@id": "bts:RnaProduct",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "RnaProduct",
-            "rdfs:subClassOf": {
-                "@id": "bts:GeneProduct"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:RnaProductIsoform",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "Represents a protein that is a specific isoform of the canonical or reference RNA",
-            "rdfs:label": "RnaProductIsoform",
-            "rdfs:subClassOf": {
-                "@id": "bts:RnaProduct"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        },
-        {
-            "@id": "bts:NoncodingRnaProduct",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "NoncodingRnaProduct",
-            "rdfs:subClassOf": {
-                "@id": "bts:RnaProduct"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        },
-        {
-            "@id": "bts:Microrna",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "Microrna",
-            "rdfs:subClassOf": {
-                "@id": "bts:NoncodingRnaProduct"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        },
-        {
-            "@id": "bts:MacromolecularComplex",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "MacromolecularComplex",
-            "rdfs:subClassOf": {
-                "@id": "bts:MacromolecularMachine"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:GeneFamily",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "any grouping of multiple genes or gene products related by common descent",
-            "rdfs:label": "GeneFamily",
-            "rdfs:subClassOf": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:Genotype",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "An information content entity that describes a genome by specifying the total variation in genomic sequence and/or gene expression, relative to some extablished background",
-            "rdfs:label": "Genotype",
-            "rdfs:subClassOf": {
-                "@id": "bts:GenomicEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:Haplotype",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A set of zero or more Alleles on a single instance of a Sequence[VMC]",
-            "rdfs:label": "Haplotype",
-            "rdfs:subClassOf": {
-                "@id": "bts:GenomicEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:SequenceVariant",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "An allele that varies in its sequence from what is considered the reference allele at that locus.",
-            "rdfs:label": "SequenceVariant",
-            "rdfs:subClassOf": {
-                "@id": "bts:GenomicEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:DrugExposure",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A drug exposure is an intake of a particular chemical substance",
-            "rdfs:label": "DrugExposure",
-            "rdfs:subClassOf": {
-                "@id": "bts:Environment"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        {
-            "@id": "bts:Treatment",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A treatment is targeted at a disease or phenotype and may involve multiple drug 'exposures'",
-            "rdfs:label": "Treatment",
-            "rdfs:subClassOf": {
-                "@id": "bts:Environment"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        },
-        {
-            "@id": "bts:GeographicLocation",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "a location that can be described in lat/long coordinates",
-            "rdfs:label": "GeographicLocation",
-            "rdfs:subClassOf": {
-                "@id": "bts:PlanetaryEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:GeographicLocationAtTime",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "a location that can be described in lat/long coordinates, for a particular time",
-            "rdfs:label": "GeographicLocationAtTime",
-            "rdfs:subClassOf": {
-                "@id": "bts:GeographicLocation"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:Occurrent",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A processual entity",
-            "rdfs:label": "Occurrent",
-            "rdfs:subClassOf": {
-                "@id": "schema:Thing"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:BiologicalProcessOrActivity",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "Either an individual molecular activity, or a collection of causally connected molecular activities",
-            "rdfs:label": "BiologicalProcessOrActivity",
-            "rdfs:subClassOf": {
-                "@id": "bts:BiologicalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        {
-            "@id": "bts:MolecularActivity",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "An execution of a molecular function carried out by a gene product or macromolecular complex.",
-            "rdfs:label": "MolecularActivity",
-            "rdfs:subClassOf": {
-                "@id": "bts:BiologicalProcessOrActivity"
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-            "schema:isPartOf": {
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-        {
-            "@id": "bts:ActivityAndBehavior",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "Activity or behavior of any independent integral living, organization or mechanical actor in the world",
-            "rdfs:label": "ActivityAndBehavior",
-            "rdfs:subClassOf": {
-                "@id": "bts:Occurrent"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        },
-        {
-            "@id": "bts:Procedure",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A series of actions conducted in a certain order or manner",
-            "rdfs:label": "Procedure",
-            "rdfs:subClassOf": {
-                "@id": "bts:Occurrent"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        },
-        {
-            "@id": "bts:Phenomenon",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "a fact or situation that is observed to exist or happen, especially one whose cause or explanation is in question",
-            "rdfs:label": "Phenomenon",
-            "rdfs:subClassOf": {
-                "@id": "bts:Occurrent"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:BiologicalProcess",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "One or more causally connected executions of molecular functions",
-            "rdfs:label": "BiologicalProcess",
-            "rdfs:subClassOf": {
-                "@id": "bts:BiologicalProcessOrActivity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        },
-        {
-            "@id": "bts:Pathway",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "Pathway",
-            "rdfs:subClassOf": {
-                "@id": "bts:BiologicalProcess"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            }
-        },
-        {
-            "@id": "bts:PhysiologicalProcess",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "PhysiologicalProcess",
-            "rdfs:subClassOf": {
-                "@id": "bts:BiologicalProcess"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        },
-        {
-            "@id": "bts:CellularComponent",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "A location in or around a cell",
-            "rdfs:label": "CellularComponent",
-            "rdfs:subClassOf": {
-                "@id": "bts:AnatomicalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        },
-        {
-            "@id": "bts:Cell",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "Cell",
-            "rdfs:subClassOf": {
-                "@id": "bts:AnatomicalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        },
-        {
-            "@id": "bts:CellLine",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "CellLine",
-            "rdfs:subClassOf": {
-                "@id": "bts:Biosample"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        {
-            "@id": "bts:GrossAnatomicalStructure",
-            "@type": "rdfs:Class",
-            "rdfs:comment": null,
-            "rdfs:label": "GrossAnatomicalStructure",
-            "rdfs:subClassOf": {
-                "@id": "bts:AnatomicalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-        {
-            "@id": "bts:ensembl",
-            "@type": "rdf:Property",
-            "rdfs:comment": "Ensembl ID for gene, protein or transcript",
-            "rdfs:label": "ensembl",
-            "schema:domainIncludes": [
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-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "schema:Text"
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-        },
-        {
-            "@id": "bts:hgnc",
-            "@type": "rdf:Property",
-            "rdfs:comment": "HGNC ID for gene",
-            "rdfs:label": "hgnc",
-            "schema:domainIncludes": {
-                "@id": "bts:Gene"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "schema:Integer"
-            }
-        },
-        {
-            "@id": "bts:entrez",
-            "@type": "rdf:Property",
-            "rdfs:comment": "Entrez ID for gene",
-            "rdfs:label": "entrez",
-            "schema:domainIncludes": {
-                "@id": "bts:Gene"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "schema:Integer"
-            }
-        },
-        {
-            "@id": "bts:refseq",
-            "@type": "rdf:Property",
-            "rdfs:comment": "Refseq ID for gene, protein or transcript",
-            "rdfs:label": "refseq",
-            "schema:domainIncludes": [
-                {
-                    "@id": "bts:Transcript"
-                }
-            ],
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
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-            "schema:rangeIncludes": {
-                "@id": "schema:Text"
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-        },
-        {
-            "@id": "bts:omim",
-            "@type": "rdf:Property",
-            "rdfs:comment": "Refseq ID for gene, protein or transcript",
-            "rdfs:label": "omim",
-            "schema:domainIncludes": [
-                {
-                    "@id": "bts:Disease"
-                }
-            ],
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "schema:Integer"
-            }
-        },
-        {
-            "@id": "bts:umls",
-            "@type": "rdf:Property",
-            "rdfs:comment": "Refseq ID for gene, protein or transcript",
-            "rdfs:label": "umls",
-            "schema:domainIncludes": {
-                "@id": "bts:Disease"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "schema:Text"
-            }
-        },
-        {
-            "@id": "bts:homologousTo",
-            "@type": "rdf:Property",
-            "rdfs:comment": "Shared ancestry between protein or gene",
-            "rdfs:label": "homologousTo",
-            "schema:domainIncludes": {
-                "@id": "bts:GeneOrGeneProduct"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:GeneOrGeneProduct"
-            }
-        },
-        {
-            "@id": "bts:molecularlyInteractsWith",
-            "@type": "rdf:Property",
-            "rdfs:comment": null,
-            "rdfs:label": "molecularlyInteractsWith",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:geneticallyInteractsWith",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two genes whose phenotypic effects are dependent on each other in some way - such that their combined phenotypic effects are the result of some interaction between the activity of their gene products. Examples include epistasis and synthetic lethality.",
-            "rdfs:label": "geneticallyInteractsWith",
-            "schema:domainIncludes": {
-                "@id": "bts:Gene"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:Gene"
-            }
-        },
-        {
-            "@id": "bts:affectsAbundanceOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one changes the amount of the other within a system of interest",
-            "rdfs:label": "affectsAbundanceOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesAbundanceOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one increases the amount of the other within a system of interest",
-            "rdfs:label": "increasesAbundanceOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesAbundanceOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one decreases the amount of the other within a system of interest",
-            "rdfs:label": "decreasesAbundanceOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsActivityOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one changes the activity of the other within a system of interest",
-            "rdfs:label": "affectsActivityOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesActivityOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one increases the activity of the other within a system of interest",
-            "rdfs:label": "increasesActivityOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesActivityOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one decreases the activity of the other within a system of interest",
-            "rdfs:label": "decreasesActivityOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsExpressionOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one changes the level of expression of the other within a system of interest",
-            "rdfs:label": "affectsExpressionOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:GenomicEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesExpressionOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one increases the level of expression of the other within a system of interest",
-            "rdfs:label": "increasesExpressionOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:GenomicEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesExpressionOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one decreases the level of expression of the other within a system of interest",
-            "rdfs:label": "decreasesExpressionOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:GenomicEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsFoldingOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one changes the rate or quality of folding of the other ",
-            "rdfs:label": "affectsFoldingOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesFoldingOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one increases the rate or quality of folding of the other ",
-            "rdfs:label": "increasesFoldingOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesFoldingOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one decreases the rate or quality of folding of the other ",
-            "rdfs:label": "decreasesFoldingOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsLocalizationOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one changes the localization of the other within a system of interest",
-            "rdfs:label": "affectsLocalizationOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesLocalizationOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one increases the proper localization of the other within a system of interest",
-            "rdfs:label": "increasesLocalizationOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesLocalizationOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one decreases the proper localization of the other within a system of interest",
-            "rdfs:label": "decreasesLocalizationOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsMetabolicProcessingOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one impacts the metabolic processing of the other within a system of interest",
-            "rdfs:label": "affectsMetabolicProcessingOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesMetabolicProcessingOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one increases the rate of metabolic processing of the other within a system of interest",
-            "rdfs:label": "increasesMetabolicProcessingOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesMetabolicProcessingOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one decreases the rate of metabolic processing of the other within a system of interest",
-            "rdfs:label": "decreasesMetabolicProcessingOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsMolecularModificationOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one leads changes in the molecular modification(s) of the other (e.g. via post-translational modifications of proteins such as the addition of phosphoryl group, or via redox reaction that adds or subtracts electrons)",
-            "rdfs:label": "affectsMolecularModificationOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesMolecularModificationOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one leads to increased molecular modification(s) of the other (e.g. via post-translational modifications of proteins such as the addition of phosphoryl group, or via redox reaction that adds or subtracts electrons)",
-            "rdfs:label": "increasesMolecularModificationOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesMolecularModificationOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one leads to decreased molecular modification(s) of the other (e.g. via post-translational modifications of proteins such as the addition of phosphoryl group, or via redox reaction that adds or subtracts electrons)",
-            "rdfs:label": "decreasesMolecularModificationOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsSynthesisOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one impacts the rate of chemical synthesis of the other",
-            "rdfs:label": "affectsSynthesisOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesSynthesisOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one increases the rate of chemical synthesis of the other",
-            "rdfs:label": "increasesSynthesisOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesSynthesisOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one decreases the rate of chemical synthesis of the other",
-            "rdfs:label": "decreasesSynthesisOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsDegradationOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one impacts the rate of degradation of the other within a system of interest",
-            "rdfs:label": "affectsDegradationOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesDegradationOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one increases the rate of degradation of the other within a system of interest",
-            "rdfs:label": "increasesDegradationOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesDegradationOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one decreases the rate of degradation of the other within a system of interest",
-            "rdfs:label": "decreasesDegradationOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsMutationRateOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a molecular entity and a genomic entity where the action or effect of the molecular entity impacts the rate of mutation of the genomic entity within a system of interest",
-            "rdfs:label": "affectsMutationRateOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:GenomicEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesMutationRateOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a molecular entity and a genomic entity where the action or effect of the molecular entity increases the rate of mutation of the genomic entity within a system of interest",
-            "rdfs:label": "increasesMutationRateOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:GenomicEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesMutationRateOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a molecular entity and a genomic entity where the action or effect of the molecular entity decreases the rate of mutation of the genomic entity within a system of interest",
-            "rdfs:label": "decreasesMutationRateOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:GenomicEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsResponseTo",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one impacts the susceptibility of a biological entity or system (e.g. an organism, cell, cellular component, macromolecular machine, biological or pathological process) to the other",
-            "rdfs:label": "affectsResponseTo",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesResponseTo",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one increases the susceptibility of a biological entity or system (e.g. an organism, cell, cellular component, macromolecular machine, biological or pathological process) to the other",
-            "rdfs:label": "increasesResponseTo",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesResponseTo",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one decreases the susceptibility of a biological entity or system (e.g. an organism, cell, cellular component, macromolecular machine, biological or pathological process) to the other",
-            "rdfs:label": "decreasesResponseTo",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsSplicingOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a molecular entity and an mRNA where the action or effect of the molecular entity impacts the splicing of the mRNA",
-            "rdfs:label": "affectsSplicingOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:Transcript"
-            }
-        },
-        {
-            "@id": "bts:increasesSplicingOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a molecular entity and an mRNA where the action or effect of the molecular entity increases the proper splicing of the mRNA",
-            "rdfs:label": "increasesSplicingOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:Transcript"
-            }
-        },
-        {
-            "@id": "bts:decreasesSplicingOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a molecular entity and an mRNA where the action or effect of the molecular entity decreases the proper splicing of the mRNA",
-            "rdfs:label": "decreasesSplicingOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:Transcript"
-            }
-        },
-        {
-            "@id": "bts:affectsStabilityOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one impacts the stability of the other within a system of interest",
-            "rdfs:label": "affectsStabilityOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesStabilityOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one increases the stability of the other within a system of interest",
-            "rdfs:label": "increasesStabilityOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesStabilityOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one decreases the stability of the other within a system of interest",
-            "rdfs:label": "decreasesStabilityOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsTransportOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one impacts the rate of transport of the other across some boundary in a system of interest",
-            "rdfs:label": "affectsTransportOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesTransportOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one increases the rate of transport of the other across some boundary in a system of interest",
-            "rdfs:label": "increasesTransportOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesTransportOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one decreases the rate of transport of the other across some boundary in a system of interest",
-            "rdfs:label": "decreasesTransportOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsSecretionOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one impacts the rate of secretion of the other out of a cell, gland, or organ",
-            "rdfs:label": "affectsSecretionOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesSecretionOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one increases the rate of secretion of the other out of a cell, gland, or organ",
-            "rdfs:label": "increasesSecretionOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesSecretionOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one decreases the rate of secretion of the other out of a cell, gland, or organ",
-            "rdfs:label": "decreasesSecretionOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:affectsUptakeOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one impacts the rate of uptake of the other into of a cell, gland, or organ",
-            "rdfs:label": "affectsUptakeOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:increasesUptakeOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one increases the rate of uptake of the other into of a cell, gland, or organ",
-            "rdfs:label": "increasesUptakeOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:decreasesUptakeOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two molecular entities where the action or effect of one decreases the rate of uptake of the other into of a cell, gland, or organ",
-            "rdfs:label": "decreasesUptakeOf",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:regulates,ProcessToProcess",
-            "@type": "rdf:Property",
-            "rdfs:comment": null,
-            "rdfs:label": "regulates,ProcessToProcess",
-            "schema:domainIncludes": {
-                "@id": "bts:Occurrent"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:Occurrent"
-            }
-        },
-        {
-            "@id": "bts:regulates,EntityToEntity",
-            "@type": "rdf:Property",
-            "rdfs:comment": null,
-            "rdfs:label": "regulates,EntityToEntity",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:hasGeneProduct",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a gene and a transcribed and/or translated product generated from it",
-            "rdfs:label": "hasGeneProduct",
-            "schema:domainIncludes": {
-                "@id": "bts:Gene"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:GeneProduct"
-            }
-        },
-        {
-            "@id": "bts:inPathwayWith",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two genes or gene products that are part of in the same biological pathway",
-            "rdfs:label": "inPathwayWith",
-            "schema:domainIncludes": {
-                "@id": "bts:GeneOrGeneProduct"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:GeneOrGeneProduct"
-            }
-        },
-        {
-            "@id": "bts:inComplexWith",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two genes or gene products that are part of (or code for products that are part of) in the same macromolecular complex",
-            "rdfs:label": "inComplexWith",
-            "schema:domainIncludes": {
-                "@id": "bts:GeneOrGeneProduct"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:GeneOrGeneProduct"
-            }
-        },
-        {
-            "@id": "bts:inCellPopulationWith",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two genes or gene products that are expressed in the same cell type or population ",
-            "rdfs:label": "inCellPopulationWith",
-            "schema:domainIncludes": {
-                "@id": "bts:GeneOrGeneProduct"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:GeneOrGeneProduct"
-            }
-        },
-        {
-            "@id": "bts:geneAssociatedWithCondition",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a gene and a disease or phenotypic feature that the gene or its alleles/products may influence, contribute to, or correlate with",
-            "rdfs:label": "geneAssociatedWithCondition",
-            "schema:domainIncludes": {
-                "@id": "bts:Gene"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:DiseaseOrPhenotypicFeature"
-            }
-        },
-        {
-            "@id": "bts:treats",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a therapeutic procedure or chemical substance and a disease or phenotypic feature that it is used to treat",
-            "rdfs:label": "treats",
-            "schema:domainIncludes": {
-                "@id": "bts:Treatment"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:DiseaseOrPhenotypicFeature"
-            }
-        },
-        {
-            "@id": "bts:correlatedWith",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a disease or phenotypic feature and a measurable molecular entity that is used as an indicator of the presence or state of the disease or feature.",
-            "rdfs:label": "correlatedWith",
-            "schema:domainIncludes": {
-                "@id": "bts:DiseaseOrPhenotypicFeature"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:hasBiomarker",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a disease or phenotypic feature and a measurable molecular entity that is used as an indicator of the presence or state of the disease or feature.",
-            "rdfs:label": "hasBiomarker",
-            "schema:domainIncludes": {
-                "@id": "bts:DiseaseOrPhenotypicFeature"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:MolecularEntity"
-            }
-        },
-        {
-            "@id": "bts:biomarkerFor",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a measurable molecular entity and a disease or phenotypic feature, where the entity is used as an indicator of the presence or state of the disease or feature.",
-            "rdfs:label": "biomarkerFor",
-            "schema:domainIncludes": {
-                "@id": "bts:MolecularEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:DiseaseOrPhenotypicFeature"
-            }
-        },
-        {
-            "@id": "bts:expressedIn",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a gene or gene product and an anatomical entity in which it is expressed",
-            "rdfs:label": "expressedIn",
-            "schema:domainIncludes": {
-                "@id": "bts:GeneOrGeneProduct"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:AnatomicalEntity"
-            }
-        },
-        {
-            "@id": "bts:expresses",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between an anatomical entity and gene or gene product that is expressed there",
-            "rdfs:label": "expresses",
-            "schema:domainIncludes": {
-                "@id": "bts:AnatomicalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:GeneOrGeneProduct"
-            }
-        },
-        {
-            "@id": "bts:hasPhenotype",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between a biological entity and a phenotype, where a phenotype is construed broadly as any kind of quality of an organism part, a collection of these qualities, or a change in quality or qualities (e.g. abnormally increased temperature). ",
-            "rdfs:label": "hasPhenotype",
-            "schema:domainIncludes": {
-                "@id": "bts:BiologicalEntity"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:DiseaseOrPhenotypicFeature"
-            }
-        },
-        {
-            "@id": "bts:precedes",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two processes, where one completes before the other begins",
-            "rdfs:label": "precedes",
-            "schema:domainIncludes": {
-                "@id": "bts:Occurrent"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:Occurrent"
-            }
-        },
-        {
-            "@id": "bts:subclassOf",
-            "@type": "rdf:Property",
-            "rdfs:comment": "holds between two classes where the domain class is a specialization of the range class",
-            "rdfs:label": "subclassOf",
-            "schema:domainIncludes": {
-                "@id": "bts:OntologyClass"
-            },
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": {
-                "@id": "bts:OntologyClass"
-            }
-        },
         {
             "@id": "bts:Patient",
             "@type": "rdfs:Class",
@@ -2016,219 +51,46 @@
                     "@id": "bts:DataProperty"
                 }
             ],
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "sms:displayName": "Patient ID",
-            "sms:required": "sms:true",
-            "sms:validationRules": []
-        },
-        {
-            "@id": "bts:Sex",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "TBD",
-            "rdfs:label": "Sex",
-            "rdfs:subClassOf": [
-                {
-                    "@id": "bts:DataProperty"
-                }
-            ],
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": [
-                {
-                    "@id": "bts:Female"
-                },
-                {
-                    "@id": "bts:Male"
-                },
-                {
-                    "@id": "bts:Other"
-                }
-            ],
-            "sms:displayName": "Sex",
-            "sms:required": "sms:true",
-            "sms:validationRules": []
-        },
-        {
-            "@id": "bts:YearofBirth",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "TBD",
-            "rdfs:label": "YearofBirth",
-            "rdfs:subClassOf": [
-                {
-                    "@id": "bts:DataProperty"
-                }
-            ],
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "sms:displayName": "Year of Birth",
-            "sms:required": "sms:false",
-            "sms:validationRules": []
-        },
-        {
-            "@id": "bts:Diagnosis",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "TBD",
-            "rdfs:label": "Diagnosis",
-            "rdfs:subClassOf": [
-                {
-                    "@id": "bts:DataProperty"
-                }
-            ],
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": [
-                {
-                    "@id": "bts:Healthy"
-                },
-                {
-                    "@id": "bts:Cancer"
-                }
-            ],
-            "sms:displayName": "Diagnosis",
-            "sms:required": "sms:true",
-            "sms:validationRules": []
-        },
-        {
-            "@id": "bts:Cancer",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "TBD",
-            "rdfs:label": "Cancer",
-            "rdfs:subClassOf": [
-                {
-                    "@id": "bts:ValidValue"
-                }
-            ],
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "sms:displayName": "Cancer",
-            "sms:required": "sms:false",
-            "sms:requiresDependency": [
-                {
-                    "@id": "bts:CancerType"
-                },
-                {
-                    "@id": "bts:FamilyHistory"
-                }
-            ],
-            "sms:validationRules": []
-        },
-        {
-            "@id": "bts:CancerType",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "TBD",
-            "rdfs:label": "CancerType",
-            "rdfs:subClassOf": [
-                {
-                    "@id": "bts:DataProperty"
-                }
-            ],
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": [
-                {
-                    "@id": "bts:Breast"
-                },
-                {
-                    "@id": "bts:Colorectal"
-                },
-                {
-                    "@id": "bts:Lung"
-                },
-                {
-                    "@id": "bts:Prostate"
-                },
-                {
-                    "@id": "bts:Skin"
-                }
-            ],
-            "sms:displayName": "Cancer Type",
-            "sms:required": "sms:true",
-            "sms:validationRules": []
-        },
-        {
-            "@id": "bts:FamilyHistory",
-            "@type": "rdfs:Class",
-            "rdfs:comment": "TBD",
-            "rdfs:label": "FamilyHistory",
-            "rdfs:subClassOf": [
-                {
-                    "@id": "bts:DataProperty"
-                }
-            ],
-            "schema:isPartOf": {
-                "@id": "http://schema.biothings.io"
-            },
-            "schema:rangeIncludes": [
-                {
-                    "@id": "bts:Breast"
-                },
-                {
-                    "@id": "bts:Colorectal"
-                },
-                {
-                    "@id": "bts:Lung"
-                },
-                {
-                    "@id": "bts:Prostate"
-                },
-                {
-                    "@id": "bts:Skin"
-                }
-            ],
-            "sms:displayName": "Family History",
+            "schema:isPartOf": {
+                "@id": "http://schema.biothings.io"
+            },
+            "sms:displayName": "Patient ID",
             "sms:required": "sms:true",
-            "sms:validationRules": [
-                "list strict"
-            ]
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:Biospecimen",
+            "@id": "bts:Sex",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "Biospecimen",
+            "rdfs:label": "Sex",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataType"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Biospecimen",
-            "sms:required": "sms:false",
-            "sms:requiresComponent": [
-                {
-                    "@id": "bts:Patient"
-                }
-            ],
-            "sms:requiresDependency": [
-                {
-                    "@id": "bts:SampleID"
-                },
+            "schema:rangeIncludes": [
                 {
-                    "@id": "bts:PatientID"
+                    "@id": "bts:Female"
                 },
                 {
-                    "@id": "bts:TissueStatus"
+                    "@id": "bts:Male"
                 },
                 {
-                    "@id": "bts:Component"
+                    "@id": "bts:Other"
                 }
             ],
+            "sms:displayName": "Sex",
+            "sms:required": "sms:true",
             "sms:validationRules": []
         },
         {
-            "@id": "bts:SampleID",
+            "@id": "bts:YearofBirth",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "SampleID",
+            "rdfs:label": "YearofBirth",
             "rdfs:subClassOf": [
                 {
                     "@id": "bts:DataProperty"
@@ -2237,15 +99,15 @@
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Sample ID",
-            "sms:required": "sms:true",
+            "sms:displayName": "Year of Birth",
+            "sms:required": "sms:false",
             "sms:validationRules": []
         },
         {
-            "@id": "bts:TissueStatus",
+            "@id": "bts:Diagnosis",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "TissueStatus",
+            "rdfs:label": "Diagnosis",
             "rdfs:subClassOf": [
                 {
                     "@id": "bts:DataProperty"
@@ -2259,171 +121,202 @@
                     "@id": "bts:Healthy"
                 },
                 {
-                    "@id": "bts:Malignant"
+                    "@id": "bts:Cancer"
                 }
             ],
-            "sms:displayName": "Tissue Status",
+            "sms:displayName": "Diagnosis",
             "sms:required": "sms:true",
             "sms:validationRules": []
         },
         {
-            "@id": "bts:BulkRNA-seqAssay",
+            "@id": "bts:Component",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "BulkRNA-seqAssay",
+            "rdfs:label": "Component",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataType"
+                    "@id": "bts:Thing"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Bulk RNA-seq Assay",
+            "sms:displayName": "Component",
             "sms:required": "sms:false",
-            "sms:requiresComponent": [
-                {
-                    "@id": "bts:Biospecimen"
-                }
-            ],
-            "sms:requiresDependency": [
-                {
-                    "@id": "bts:Filename"
-                },
-                {
-                    "@id": "bts:SampleID"
-                },
-                {
-                    "@id": "bts:FileFormat"
-                },
+            "sms:validationRules": []
+        },
+        {
+            "@id": "bts:DataType",
+            "@type": "rdfs:Class",
+            "rdfs:comment": "TBD",
+            "rdfs:label": "DataType",
+            "rdfs:subClassOf": [
                 {
-                    "@id": "bts:Component"
+                    "@id": "bts:Thing"
                 }
             ],
+            "schema:isPartOf": {
+                "@id": "http://schema.biothings.io"
+            },
+            "sms:displayName": "DataType",
+            "sms:required": "sms:false",
             "sms:validationRules": []
         },
         {
-            "@id": "bts:Filename",
+            "@id": "bts:DataProperty",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "Filename",
+            "rdfs:label": "DataProperty",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:Thing"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Filename",
-            "sms:required": "sms:true",
+            "sms:displayName": "DataProperty",
+            "sms:required": "sms:false",
             "sms:validationRules": []
         },
         {
-            "@id": "bts:FileFormat",
+            "@id": "bts:Female",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "FileFormat",
+            "rdfs:label": "Female",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:Sex"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "schema:rangeIncludes": [
-                {
-                    "@id": "bts:FASTQ"
-                },
-                {
-                    "@id": "bts:BAM"
-                },
-                {
-                    "@id": "bts:CRAM"
-                },
+            "sms:displayName": "Female",
+            "sms:required": "sms:false",
+            "sms:validationRules": []
+        },
+        {
+            "@id": "bts:Male",
+            "@type": "rdfs:Class",
+            "rdfs:comment": "TBD",
+            "rdfs:label": "Male",
+            "rdfs:subClassOf": [
                 {
-                    "@id": "bts:CSV/TSV"
+                    "@id": "bts:Sex"
                 }
             ],
-            "sms:displayName": "File Format",
-            "sms:required": "sms:true",
+            "schema:isPartOf": {
+                "@id": "http://schema.biothings.io"
+            },
+            "sms:displayName": "Male",
+            "sms:required": "sms:false",
             "sms:validationRules": []
         },
         {
-            "@id": "bts:BAM",
+            "@id": "bts:Other",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "BAM",
+            "rdfs:label": "Other",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:ValidValue"
+                    "@id": "bts:Sex"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "BAM",
+            "sms:displayName": "Other",
             "sms:required": "sms:false",
-            "sms:requiresDependency": [
+            "sms:validationRules": []
+        },
+        {
+            "@id": "bts:Healthy",
+            "@type": "rdfs:Class",
+            "rdfs:comment": "TBD",
+            "rdfs:label": "Healthy",
+            "rdfs:subClassOf": [
                 {
-                    "@id": "bts:GenomeBuild"
+                    "@id": "bts:Diagnosis"
+                },
+                {
+                    "@id": "bts:TissueStatus"
                 }
             ],
+            "schema:isPartOf": {
+                "@id": "http://schema.biothings.io"
+            },
+            "sms:displayName": "Healthy",
+            "sms:required": "sms:false",
             "sms:validationRules": []
         },
         {
-            "@id": "bts:CRAM",
+            "@id": "bts:Cancer",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CRAM",
+            "rdfs:label": "Cancer",
             "rdfs:subClassOf": [
                 {
                     "@id": "bts:ValidValue"
+                },
+                {
+                    "@id": "bts:Diagnosis"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "CRAM",
+            "sms:displayName": "Cancer",
             "sms:required": "sms:false",
             "sms:requiresDependency": [
                 {
-                    "@id": "bts:GenomeBuild"
+                    "@id": "bts:CancerType"
                 },
                 {
-                    "@id": "bts:GenomeFASTA"
+                    "@id": "bts:FamilyHistory"
                 }
             ],
             "sms:validationRules": []
         },
         {
-            "@id": "bts:CSV/TSV",
+            "@id": "bts:CancerType",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CSV/TSV",
+            "rdfs:label": "CancerType",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:ValidValue"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "CSV/TSV",
-            "sms:required": "sms:false",
-            "sms:requiresDependency": [
+            "schema:rangeIncludes": [
                 {
-                    "@id": "bts:GenomeBuild"
+                    "@id": "bts:Breast"
+                },
+                {
+                    "@id": "bts:Colorectal"
+                },
+                {
+                    "@id": "bts:Lung"
+                },
+                {
+                    "@id": "bts:Prostate"
+                },
+                {
+                    "@id": "bts:Skin"
                 }
             ],
+            "sms:displayName": "Cancer Type",
+            "sms:required": "sms:true",
             "sms:validationRules": []
         },
         {
-            "@id": "bts:GenomeBuild",
+            "@id": "bts:FamilyHistory",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "GenomeBuild",
+            "rdfs:label": "FamilyHistory",
             "rdfs:subClassOf": [
                 {
                     "@id": "bts:DataProperty"
@@ -2434,156 +327,185 @@
             },
             "schema:rangeIncludes": [
                 {
-                    "@id": "bts:GRCh37"
+                    "@id": "bts:Breast"
                 },
                 {
-                    "@id": "bts:GRCh38"
+                    "@id": "bts:Colorectal"
                 },
                 {
-                    "@id": "bts:GRCm38"
+                    "@id": "bts:Lung"
                 },
                 {
-                    "@id": "bts:GRCm39"
+                    "@id": "bts:Prostate"
+                },
+                {
+                    "@id": "bts:Skin"
                 }
             ],
-            "sms:displayName": "Genome Build",
+            "sms:displayName": "Family History",
             "sms:required": "sms:true",
+            "sms:validationRules": [
+                "list strict"
+            ]
+        },
+        {
+            "@id": "bts:ValidValue",
+            "@type": "rdfs:Class",
+            "rdfs:comment": "TBD",
+            "rdfs:label": "ValidValue",
+            "rdfs:subClassOf": [
+                {
+                    "@id": "bts:Thing"
+                }
+            ],
+            "schema:isPartOf": {
+                "@id": "http://schema.biothings.io"
+            },
+            "sms:displayName": "ValidValue",
+            "sms:required": "sms:false",
+            "sms:validationRules": []
+        },
+        {
+            "@id": "bts:Breast",
+            "@type": "rdfs:Class",
+            "rdfs:comment": "TBD",
+            "rdfs:label": "Breast",
+            "rdfs:subClassOf": [
+                {
+                    "@id": "bts:CancerType"
+                },
+                {
+                    "@id": "bts:FamilyHistory"
+                }
+            ],
+            "schema:isPartOf": {
+                "@id": "http://schema.biothings.io"
+            },
+            "sms:displayName": "Breast",
+            "sms:required": "sms:false",
+            "sms:validationRules": []
+        },
+        {
+            "@id": "bts:Colorectal",
+            "@type": "rdfs:Class",
+            "rdfs:comment": "TBD",
+            "rdfs:label": "Colorectal",
+            "rdfs:subClassOf": [
+                {
+                    "@id": "bts:CancerType"
+                },
+                {
+                    "@id": "bts:FamilyHistory"
+                }
+            ],
+            "schema:isPartOf": {
+                "@id": "http://schema.biothings.io"
+            },
+            "sms:displayName": "Colorectal",
+            "sms:required": "sms:false",
             "sms:validationRules": []
         },
         {
-            "@id": "bts:GenomeFASTA",
+            "@id": "bts:Lung",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "GenomeFASTA",
+            "rdfs:label": "Lung",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:CancerType"
+                },
+                {
+                    "@id": "bts:FamilyHistory"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Genome FASTA",
-            "sms:required": "sms:true",
+            "sms:displayName": "Lung",
+            "sms:required": "sms:false",
             "sms:validationRules": []
         },
         {
-            "@id": "bts:MockComponent",
+            "@id": "bts:Prostate",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "MockComponent",
+            "rdfs:label": "Prostate",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataType"
+                    "@id": "bts:CancerType"
+                },
+                {
+                    "@id": "bts:FamilyHistory"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "MockComponent",
+            "sms:displayName": "Prostate",
             "sms:required": "sms:false",
-            "sms:requiresDependency": [
-                {
-                    "@id": "bts:Component"
-                },
-                {
-                    "@id": "bts:CheckList"
-                },
-                {
-                    "@id": "bts:CheckRegexList"
-                },
-                {
-                    "@id": "bts:CheckRegexSingle"
-                },
-                {
-                    "@id": "bts:CheckRegexFormat"
-                },
-                {
-                    "@id": "bts:CheckNum"
-                },
-                {
-                    "@id": "bts:CheckFloat"
-                },
-                {
-                    "@id": "bts:CheckInt"
-                },
-                {
-                    "@id": "bts:CheckString"
-                },
-                {
-                    "@id": "bts:CheckURL"
-                },
-                {
-                    "@id": "bts:CheckMatchatLeast"
-                },
-                {
-                    "@id": "bts:CheckMatchatLeastvalues"
-                },
-                {
-                    "@id": "bts:CheckMatchExactly"
-                },
-                {
-                    "@id": "bts:CheckMatchExactlyvalues"
-                },
-                {
-                    "@id": "bts:CheckRecommended"
-                },
-                {
-                    "@id": "bts:CheckAges"
-                },
-                {
-                    "@id": "bts:CheckUnique"
-                },
-                {
-                    "@id": "bts:CheckRange"
-                },
+            "sms:validationRules": []
+        },
+        {
+            "@id": "bts:Skin",
+            "@type": "rdfs:Class",
+            "rdfs:comment": "TBD",
+            "rdfs:label": "Skin",
+            "rdfs:subClassOf": [
                 {
-                    "@id": "bts:CheckDate"
+                    "@id": "bts:CancerType"
                 },
                 {
-                    "@id": "bts:CheckNA"
+                    "@id": "bts:FamilyHistory"
                 }
             ],
+            "schema:isPartOf": {
+                "@id": "http://schema.biothings.io"
+            },
+            "sms:displayName": "Skin",
+            "sms:required": "sms:false",
             "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckList",
+            "@id": "bts:Biospecimen",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckList",
+            "rdfs:label": "Biospecimen",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:DataType"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "schema:rangeIncludes": [
+            "sms:displayName": "Biospecimen",
+            "sms:required": "sms:false",
+            "sms:requiresComponent": [
                 {
-                    "@id": "bts:Ab"
+                    "@id": "bts:Patient"
+                }
+            ],
+            "sms:requiresDependency": [
+                {
+                    "@id": "bts:SampleID"
                 },
                 {
-                    "@id": "bts:Cd"
+                    "@id": "bts:PatientID"
                 },
                 {
-                    "@id": "bts:Ef"
+                    "@id": "bts:TissueStatus"
                 },
                 {
-                    "@id": "bts:Gh"
+                    "@id": "bts:Component"
                 }
             ],
-            "sms:displayName": "Check List",
-            "sms:required": "sms:false",
-            "sms:validationRules": [
-                "list strict error"
-            ]
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckRegexList",
+            "@id": "bts:SampleID",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckRegexList",
+            "rdfs:label": "SampleID",
             "rdfs:subClassOf": [
                 {
                     "@id": "bts:DataProperty"
@@ -2592,18 +514,15 @@
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Regex List",
-            "sms:required": "sms:false",
-            "sms:validationRules": [
-                "list strict error",
-                "regex match [a-f] error"
-            ]
+            "sms:displayName": "Sample ID",
+            "sms:required": "sms:true",
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckRegexSingle",
+            "@id": "bts:TissueStatus",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckRegexSingle",
+            "rdfs:label": "TissueStatus",
             "rdfs:subClassOf": [
                 {
                     "@id": "bts:DataProperty"
@@ -2612,55 +531,76 @@
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Regex Single",
-            "sms:required": "sms:false",
-            "sms:validationRules": [
-                "regex search [a-f] error"
-            ]
+            "schema:rangeIncludes": [
+                {
+                    "@id": "bts:Healthy"
+                },
+                {
+                    "@id": "bts:Malignant"
+                }
+            ],
+            "sms:displayName": "Tissue Status",
+            "sms:required": "sms:true",
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckRegexFormat",
+            "@id": "bts:Malignant",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckRegexFormat",
+            "rdfs:label": "Malignant",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:TissueStatus"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Regex Format",
+            "sms:displayName": "Malignant",
             "sms:required": "sms:false",
-            "sms:validationRules": [
-                "regex match [a-f] error"
-            ]
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckNum",
+            "@id": "bts:BulkRNA-seqAssay",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckNum",
+            "rdfs:label": "BulkRNA-seqAssay",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:DataType"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Num",
+            "sms:displayName": "Bulk RNA-seq Assay",
             "sms:required": "sms:false",
-            "sms:validationRules": [
-                "num error"
-            ]
+            "sms:requiresComponent": [
+                {
+                    "@id": "bts:Biospecimen"
+                }
+            ],
+            "sms:requiresDependency": [
+                {
+                    "@id": "bts:Filename"
+                },
+                {
+                    "@id": "bts:SampleID"
+                },
+                {
+                    "@id": "bts:FileFormat"
+                },
+                {
+                    "@id": "bts:Component"
+                }
+            ],
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckFloat",
+            "@id": "bts:Filename",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckFloat",
+            "rdfs:label": "Filename",
             "rdfs:subClassOf": [
                 {
                     "@id": "bts:DataProperty"
@@ -2669,17 +609,15 @@
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Float",
-            "sms:required": "sms:false",
-            "sms:validationRules": [
-                "float error"
-            ]
+            "sms:displayName": "Filename",
+            "sms:required": "sms:true",
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckInt",
+            "@id": "bts:FileFormat",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckInt",
+            "rdfs:label": "FileFormat",
             "rdfs:subClassOf": [
                 {
                     "@id": "bts:DataProperty"
@@ -2688,93 +626,124 @@
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Int",
-            "sms:required": "sms:false",
-            "sms:validationRules": [
-                "int error"
-            ]
+            "schema:rangeIncludes": [
+                {
+                    "@id": "bts:FASTQ"
+                },
+                {
+                    "@id": "bts:BAM"
+                },
+                {
+                    "@id": "bts:CRAM"
+                },
+                {
+                    "@id": "bts:CSV/TSV"
+                }
+            ],
+            "sms:displayName": "File Format",
+            "sms:required": "sms:true",
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckString",
+            "@id": "bts:FASTQ",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckString",
+            "rdfs:label": "FASTQ",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:FileFormat"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check String",
+            "sms:displayName": "FASTQ",
             "sms:required": "sms:false",
-            "sms:validationRules": [
-                "str error"
-            ]
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckURL",
+            "@id": "bts:BAM",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckURL",
+            "rdfs:label": "BAM",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:ValidValue"
+                },
+                {
+                    "@id": "bts:FileFormat"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check URL",
+            "sms:displayName": "BAM",
             "sms:required": "sms:false",
-            "sms:validationRules": [
-                "url error"
-            ]
+            "sms:requiresDependency": [
+                {
+                    "@id": "bts:GenomeBuild"
+                }
+            ],
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckMatchatLeast",
+            "@id": "bts:CRAM",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckMatchatLeast",
+            "rdfs:label": "CRAM",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:ValidValue"
+                },
+                {
+                    "@id": "bts:FileFormat"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Match at Least",
+            "sms:displayName": "CRAM",
             "sms:required": "sms:false",
-            "sms:validationRules": [
-                "matchAtLeastOne Patient.PatientID set warning"
-            ]
+            "sms:requiresDependency": [
+                {
+                    "@id": "bts:GenomeBuild"
+                },
+                {
+                    "@id": "bts:GenomeFASTA"
+                }
+            ],
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckMatchExactly",
+            "@id": "bts:CSV/TSV",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckMatchExactly",
+            "rdfs:label": "CSV/TSV",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:ValidValue"
+                },
+                {
+                    "@id": "bts:FileFormat"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Match Exactly",
+            "sms:displayName": "CSV/TSV",
             "sms:required": "sms:false",
-            "sms:validationRules": [
-                "matchExactlyOne MockComponent.checkMatchExactly set warning"
-            ]
+            "sms:requiresDependency": [
+                {
+                    "@id": "bts:GenomeBuild"
+                }
+            ],
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckMatchatLeastvalues",
+            "@id": "bts:GenomeBuild",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckMatchatLeastvalues",
+            "rdfs:label": "GenomeBuild",
             "rdfs:subClassOf": [
                 {
                     "@id": "bts:DataProperty"
@@ -2783,17 +752,29 @@
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Match at Least values",
-            "sms:required": "sms:false",
-            "sms:validationRules": [
-                "matchAtLeastOne MockComponent.checkMatchatLeastvalues value warning"
-            ]
+            "schema:rangeIncludes": [
+                {
+                    "@id": "bts:GRCh37"
+                },
+                {
+                    "@id": "bts:GRCh38"
+                },
+                {
+                    "@id": "bts:GRCm38"
+                },
+                {
+                    "@id": "bts:GRCm39"
+                }
+            ],
+            "sms:displayName": "Genome Build",
+            "sms:required": "sms:true",
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckMatchExactlyvalues",
+            "@id": "bts:GenomeFASTA",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckMatchExactlyvalues",
+            "rdfs:label": "GenomeFASTA",
             "rdfs:subClassOf": [
                 {
                     "@id": "bts:DataProperty"
@@ -2802,112 +783,165 @@
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Match Exactly values",
-            "sms:required": "sms:false",
-            "sms:validationRules": [
-                "matchExactlyOne MockComponent.checkMatchExactlyvalues value warning"
-            ]
+            "sms:displayName": "Genome FASTA",
+            "sms:required": "sms:true",
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckRecommended",
+            "@id": "bts:GRCh37",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckRecommended",
+            "rdfs:label": "GRCh37",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:GenomeBuild"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Recommended",
+            "sms:displayName": "GRCh37",
             "sms:required": "sms:false",
-            "sms:validationRules": [
-                "recommended warning"
-            ]
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckAges",
+            "@id": "bts:GRCh38",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckAges",
+            "rdfs:label": "GRCh38",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:GenomeBuild"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Ages",
+            "sms:displayName": "GRCh38",
             "sms:required": "sms:false",
-            "sms:validationRules": [
-                "protectAges warning"
-            ]
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckUnique",
+            "@id": "bts:GRCm38",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckUnique",
+            "rdfs:label": "GRCm38",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:GenomeBuild"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Unique",
+            "sms:displayName": "GRCm38",
             "sms:required": "sms:false",
-            "sms:validationRules": [
-                "unique error"
-            ]
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckRange",
+            "@id": "bts:GRCm39",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckRange",
+            "rdfs:label": "GRCm39",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:GenomeBuild"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Range",
+            "sms:displayName": "GRCm39",
             "sms:required": "sms:false",
-            "sms:validationRules": [
-                "inRange 50 100 error"
-            ]
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckDate",
+            "@id": "bts:MockComponent",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckDate",
+            "rdfs:label": "MockComponent",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataProperty"
+                    "@id": "bts:DataType"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check Date",
+            "sms:displayName": "MockComponent",
             "sms:required": "sms:false",
-            "sms:validationRules": [
-                "date error"
-            ]
+            "sms:requiresDependency": [
+                {
+                    "@id": "bts:Component"
+                },
+                {
+                    "@id": "bts:CheckList"
+                },
+                {
+                    "@id": "bts:CheckRegexList"
+                },
+                {
+                    "@id": "bts:CheckRegexSingle"
+                },
+                {
+                    "@id": "bts:CheckRegexFormat"
+                },
+                {
+                    "@id": "bts:CheckRegexInteger"
+                },
+                {
+                    "@id": "bts:CheckNum"
+                },
+                {
+                    "@id": "bts:CheckFloat"
+                },
+                {
+                    "@id": "bts:CheckInt"
+                },
+                {
+                    "@id": "bts:CheckString"
+                },
+                {
+                    "@id": "bts:CheckURL"
+                },
+                {
+                    "@id": "bts:CheckMatchatLeast"
+                },
+                {
+                    "@id": "bts:CheckMatchatLeastvalues"
+                },
+                {
+                    "@id": "bts:CheckMatchExactly"
+                },
+                {
+                    "@id": "bts:CheckMatchExactlyvalues"
+                },
+                {
+                    "@id": "bts:CheckRecommended"
+                },
+                {
+                    "@id": "bts:CheckAges"
+                },
+                {
+                    "@id": "bts:CheckUnique"
+                },
+                {
+                    "@id": "bts:CheckRange"
+                },
+                {
+                    "@id": "bts:CheckDate"
+                },
+                {
+                    "@id": "bts:CheckNA"
+                }
+            ],
+            "sms:validationRules": []
         },
         {
-            "@id": "bts:CheckNA",
+            "@id": "bts:CheckList",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "CheckNA",
+            "rdfs:label": "CheckList",
             "rdfs:subClassOf": [
                 {
                     "@id": "bts:DataProperty"
@@ -2916,46 +950,51 @@
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Check NA",
+            "schema:rangeIncludes": [
+                {
+                    "@id": "bts:Ab"
+                },
+                {
+                    "@id": "bts:Cd"
+                },
+                {
+                    "@id": "bts:Ef"
+                },
+                {
+                    "@id": "bts:Gh"
+                }
+            ],
+            "sms:displayName": "Check List",
             "sms:required": "sms:false",
             "sms:validationRules": [
-                "int error",
-                "IsNA warning"
+                "list strict"
             ]
         },
         {
-            "@id": "bts:MockRDB",
+            "@id": "bts:CheckRegexList",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "MockRDB",
+            "rdfs:label": "CheckRegexList",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:DataType"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "MockRDB",
+            "sms:displayName": "Check Regex List",
             "sms:required": "sms:false",
-            "sms:requiresDependency": [
-                {
-                    "@id": "bts:Component"
-                },
-                {
-                    "@id": "bts:MockRDBId"
-                },
-                {
-                    "@id": "bts:SourceManifest"
-                }
-            ],
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "list strict",
+                "regex match [a-f]"
+            ]
         },
         {
-            "@id": "bts:MockRDBId",
+            "@id": "bts:CheckRegexSingle",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "MockRDBId",
+            "rdfs:label": "CheckRegexSingle",
             "rdfs:subClassOf": [
                 {
                     "@id": "bts:DataProperty"
@@ -2964,17 +1003,17 @@
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "MockRDB_id",
-            "sms:required": "sms:true",
+            "sms:displayName": "Check Regex Single",
+            "sms:required": "sms:false",
             "sms:validationRules": [
-                "int"
+                "regex search [a-f]"
             ]
         },
         {
-            "@id": "bts:SourceManifest",
+            "@id": "bts:CheckRegexFormat",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "SourceManifest",
+            "rdfs:label": "CheckRegexFormat",
             "rdfs:subClassOf": [
                 {
                     "@id": "bts:DataProperty"
@@ -2983,281 +1022,316 @@
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "SourceManifest",
-            "sms:required": "sms:true",
-            "sms:validationRules": []
+            "sms:displayName": "Check Regex Format",
+            "sms:required": "sms:false",
+            "sms:validationRules": [
+                "regex match [a-f]"
+            ]
         },
         {
-            "@id": "bts:Component",
+            "@id": "bts:CheckRegexInteger",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "Component",
+            "rdfs:label": "CheckRegexInteger",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:Patient"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Component",
+            "sms:displayName": "Check Regex Integer",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "regex search ^\\d+$"
+            ]
         },
         {
-            "@id": "bts:Female",
+            "@id": "bts:CheckNum",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "Female",
+            "rdfs:label": "CheckNum",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:Sex"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Female",
+            "sms:displayName": "Check Num",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "num"
+            ]
         },
         {
-            "@id": "bts:Male",
+            "@id": "bts:CheckFloat",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "Male",
+            "rdfs:label": "CheckFloat",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:Sex"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Male",
+            "sms:displayName": "Check Float",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "float"
+            ]
         },
         {
-            "@id": "bts:Other",
+            "@id": "bts:CheckInt",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "Other",
+            "rdfs:label": "CheckInt",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:Sex"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Other",
+            "sms:displayName": "Check Int",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "int"
+            ]
         },
         {
-            "@id": "bts:Healthy",
+            "@id": "bts:CheckString",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "Healthy",
+            "rdfs:label": "CheckString",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:Diagnosis"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Healthy",
+            "sms:displayName": "Check String",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "str"
+            ]
         },
         {
-            "@id": "bts:Breast",
+            "@id": "bts:CheckURL",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "Breast",
+            "rdfs:label": "CheckURL",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:CancerType"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Breast",
+            "sms:displayName": "Check URL",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "url"
+            ]
         },
         {
-            "@id": "bts:Colorectal",
+            "@id": "bts:CheckMatchatLeast",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "Colorectal",
+            "rdfs:label": "CheckMatchatLeast",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:CancerType"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Colorectal",
+            "sms:displayName": "Check Match at Least",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "matchAtLeastOne Patient.PatientID set"
+            ]
         },
         {
-            "@id": "bts:Lung",
+            "@id": "bts:CheckMatchatLeastvalues",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "Lung",
+            "rdfs:label": "CheckMatchatLeastvalues",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:CancerType"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Lung",
+            "sms:displayName": "Check Match at Least values",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "matchAtLeastOne MockComponent.checkMatchatLeastvalues value"
+            ]
         },
         {
-            "@id": "bts:Prostate",
+            "@id": "bts:CheckMatchExactly",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "Prostate",
+            "rdfs:label": "CheckMatchExactly",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:CancerType"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Prostate",
+            "sms:displayName": "Check Match Exactly",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "matchExactlyOne MockComponent.checkMatchExactly set"
+            ]
         },
         {
-            "@id": "bts:Skin",
+            "@id": "bts:CheckMatchExactlyvalues",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "Skin",
+            "rdfs:label": "CheckMatchExactlyvalues",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:CancerType"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Skin",
+            "sms:displayName": "Check Match Exactly values",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "matchExactlyOne MockComponent.checkMatchExactlyvalues value"
+            ]
         },
         {
-            "@id": "bts:Malignant",
+            "@id": "bts:CheckRecommended",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "Malignant",
+            "rdfs:label": "CheckRecommended",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:TissueStatus"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "Malignant",
+            "sms:displayName": "Check Recommended",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "recommended"
+            ]
         },
         {
-            "@id": "bts:FASTQ",
+            "@id": "bts:CheckAges",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "FASTQ",
+            "rdfs:label": "CheckAges",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:FileFormat"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "FASTQ",
+            "sms:displayName": "Check Ages",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "protectAges"
+            ]
         },
         {
-            "@id": "bts:GRCh37",
+            "@id": "bts:CheckUnique",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "GRCh37",
+            "rdfs:label": "CheckUnique",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:GenomeBuild"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "GRCh37",
+            "sms:displayName": "Check Unique",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "unique error"
+            ]
         },
         {
-            "@id": "bts:GRCh38",
+            "@id": "bts:CheckRange",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "GRCh38",
+            "rdfs:label": "CheckRange",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:GenomeBuild"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "GRCh38",
+            "sms:displayName": "Check Range",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "inRange 50 100 error"
+            ]
         },
         {
-            "@id": "bts:GRCm38",
+            "@id": "bts:CheckDate",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "GRCm38",
+            "rdfs:label": "CheckDate",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:GenomeBuild"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "GRCm38",
+            "sms:displayName": "Check Date",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "date"
+            ]
         },
         {
-            "@id": "bts:GRCm39",
+            "@id": "bts:CheckNA",
             "@type": "rdfs:Class",
             "rdfs:comment": "TBD",
-            "rdfs:label": "GRCm39",
+            "rdfs:label": "CheckNA",
             "rdfs:subClassOf": [
                 {
-                    "@id": "bts:GenomeBuild"
+                    "@id": "bts:DataProperty"
                 }
             ],
             "schema:isPartOf": {
                 "@id": "http://schema.biothings.io"
             },
-            "sms:displayName": "GRCm39",
+            "sms:displayName": "Check NA",
             "sms:required": "sms:false",
-            "sms:validationRules": []
+            "sms:validationRules": [
+                "int",
+                "IsNA"
+            ]
         },
         {
             "@id": "bts:Ab",
@@ -3326,6 +1400,70 @@
             "sms:displayName": "gh",
             "sms:required": "sms:false",
             "sms:validationRules": []
+        },
+        {
+            "@id": "bts:MockRDB",
+            "@type": "rdfs:Class",
+            "rdfs:comment": "TBD",
+            "rdfs:label": "MockRDB",
+            "rdfs:subClassOf": [
+                {
+                    "@id": "bts:DataType"
+                }
+            ],
+            "schema:isPartOf": {
+                "@id": "http://schema.biothings.io"
+            },
+            "sms:displayName": "MockRDB",
+            "sms:required": "sms:false",
+            "sms:requiresDependency": [
+                {
+                    "@id": "bts:Component"
+                },
+                {
+                    "@id": "bts:MockRDBId"
+                },
+                {
+                    "@id": "bts:SourceManifest"
+                }
+            ],
+            "sms:validationRules": []
+        },
+        {
+            "@id": "bts:MockRDBId",
+            "@type": "rdfs:Class",
+            "rdfs:comment": "TBD",
+            "rdfs:label": "MockRDBId",
+            "rdfs:subClassOf": [
+                {
+                    "@id": "bts:DataProperty"
+                }
+            ],
+            "schema:isPartOf": {
+                "@id": "http://schema.biothings.io"
+            },
+            "sms:displayName": "MockRDB_id",
+            "sms:required": "sms:true",
+            "sms:validationRules": [
+                "int"
+            ]
+        },
+        {
+            "@id": "bts:SourceManifest",
+            "@type": "rdfs:Class",
+            "rdfs:comment": "TBD",
+            "rdfs:label": "SourceManifest",
+            "rdfs:subClassOf": [
+                {
+                    "@id": "bts:DataProperty"
+                }
+            ],
+            "schema:isPartOf": {
+                "@id": "http://schema.biothings.io"
+            },
+            "sms:displayName": "SourceManifest",
+            "sms:required": "sms:true",
+            "sms:validationRules": []
         }
     ],
     "@id": "http://schema.biothings.io/#0.1"
diff --git a/tests/data/mock_manifests/Invalid_Test_Manifest.csv b/tests/data/mock_manifests/Invalid_Test_Manifest.csv
index ea0e7685c..1cc8995ef 100644
--- a/tests/data/mock_manifests/Invalid_Test_Manifest.csv
+++ b/tests/data/mock_manifests/Invalid_Test_Manifest.csv
@@ -1,4 +1,5 @@
 Component,Check List,Check Regex List,Check Regex Single,Check Regex Format,Check Regex Integer,Check Num,Check Float,Check Int,Check String,Check URL,Check Match at Least,Check Match at Least values,Check Match Exactly,Check Match Exactly values,Check Recommended,Check Ages,Check Unique,Check Range,Check Date,Check NA
 MockComponent,"ab,cd","ab,cd,ef",a,a,5.4,6,99.65,7,valid,https://www.google.com/,1738,1738,8085,98085,,6549,str1,70,32-984,7
 MockComponent,invalid list values,ab cd ef,q,m,0,c,99,5.63,94,http://googlef.com/,7163,51100,9965,71738,,32851,str1,30,notADate,9.5
-MockComponent,"ab,cd","ab,cd,ef",b,b,683902,6.5,62.3,2,valid,https://github.com/Sage-Bionetworks/schematic,8085,8085,1738,210065,,6550,str1,90,84-43-094,Not Applicable
\ No newline at end of file
+MockComponent,"ab,cd","ab,cd,ef",b,b,683902,6.5,62.3,2,valid,https://github.com/Sage-Bionetworks/schematic,8085,8085,1738,210065,,6550,str1,90,84-43-094,Not Applicable
+,,,,,,,,,,,,,,,,,,,
\ No newline at end of file
diff --git a/tests/data/mock_manifests/example.biospecimen_component_rule.manifest.csv b/tests/data/mock_manifests/example.biospecimen_component_rule.manifest.csv
new file mode 100644
index 000000000..8ac07cd1d
--- /dev/null
+++ b/tests/data/mock_manifests/example.biospecimen_component_rule.manifest.csv
@@ -0,0 +1,4 @@
+Sample ID,Patient ID,Tissue Status,Component
+123,123,Healthy,Biospecimen
+456,123,Healthy,Biospecimen
+789,syn465,Healthy,Biospecimen
\ No newline at end of file
diff --git a/tests/data/mock_manifests/example.patient_component_rule.manifest.csv b/tests/data/mock_manifests/example.patient_component_rule.manifest.csv
new file mode 100644
index 000000000..d0d26035b
--- /dev/null
+++ b/tests/data/mock_manifests/example.patient_component_rule.manifest.csv
@@ -0,0 +1,4 @@
+Patient ID,Sex,Year of Birth,Diagnosis,Component,Cancer Type,Family History
+123,Female,,Cancer,Patient,Breast,"Breast, Colorectal"
+123,Male,,Healthy,Patient,,"Breast, Colorectal"
+789,Other,,Healthy,Patient,,"Breast, Colorectal"
\ No newline at end of file
diff --git a/tests/data/test_configs/valid_config2.yml b/tests/data/test_configs/valid_config2.yml
new file mode 100644
index 000000000..78306ee18
--- /dev/null
+++ b/tests/data/test_configs/valid_config2.yml
@@ -0,0 +1,15 @@
+# This is a valid config, but missing the asset store section
+
+manifest:
+  manifest_folder: "folder_name"
+  title: "title"
+  data_type:
+    - "data_type"
+
+model:
+  location: "model.jsonld"
+
+google_sheets:
+  service_acct_creds_synapse_id: "syn1"
+  service_acct_creds: "creds.json"
+  strict_validation: false
diff --git a/tests/test_api.py b/tests/test_api.py
index 29a55615e..e2dc2ad5f 100644
--- a/tests/test_api.py
+++ b/tests/test_api.py
@@ -1,4 +1,3 @@
-
 import configparser
 import json
 import logging
@@ -23,65 +22,84 @@
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
+
 ## TO DO: Clean up url and use a global variable SERVER_URL
 @pytest.fixture(scope="class")
 def app():
     app = create_app()
     yield app
 
+
 @pytest.fixture(scope="class")
 def client(app):
-    app.config['SCHEMATIC_CONFIG'] = None
+    app.config["SCHEMATIC_CONFIG"] = None
 
     with app.test_client() as client:
         yield client
 
+
 @pytest.fixture(scope="class")
 def test_manifest_csv(helpers):
     test_manifest_path = helpers.get_data_path("mock_manifests/Valid_Test_Manifest.csv")
     yield test_manifest_path
 
+
 @pytest.fixture(scope="class")
 def test_manifest_submit(helpers):
-    test_manifest_path = helpers.get_data_path("mock_manifests/example_biospecimen_test.csv")
-    yield test_manifest_path   
+    test_manifest_path = helpers.get_data_path(
+        "mock_manifests/example_biospecimen_test.csv"
+    )
+    yield test_manifest_path
+
 
 @pytest.fixture(scope="class")
 def test_invalid_manifest(helpers):
-    test_invalid_manifest = helpers.get_data_frame("mock_manifests/Invalid_Test_Manifest.csv", preserve_raw_input=False)
+    test_invalid_manifest = helpers.get_data_frame(
+        "mock_manifests/Invalid_Test_Manifest.csv", preserve_raw_input=False
+    )
     yield test_invalid_manifest
 
+
 @pytest.fixture(scope="class")
 def test_upsert_manifest_csv(helpers):
-    test_upsert_manifest_path = helpers.get_data_path("mock_manifests/rdb_table_manifest.csv")
+    test_upsert_manifest_path = helpers.get_data_path(
+        "mock_manifests/rdb_table_manifest.csv"
+    )
     yield test_upsert_manifest_path
 
+
 @pytest.fixture(scope="class")
 def test_manifest_json(helpers):
-    test_manifest_path = helpers.get_data_path("mock_manifests/Example.Patient.manifest.json")
+    test_manifest_path = helpers.get_data_path(
+        "mock_manifests/Example.Patient.manifest.json"
+    )
     yield test_manifest_path
 
+
 @pytest.fixture(scope="class")
 def data_model_jsonld():
-    #data_model_jsonld ="https://raw.githubusercontent.com/Sage-Bionetworks/schematic/develop/tests/data/example.model.jsonld"
+    # data_model_jsonld ="https://raw.githubusercontent.com/Sage-Bionetworks/schematic/develop/tests/data/example.model.jsonld"
     data_model_jsonld = "https://raw.githubusercontent.com/mialy-defelice/data_models/main/example.model.jsonld"
     yield data_model_jsonld
 
+
 @pytest.fixture(scope="class")
 def benchmark_data_model_jsonld():
-    #benchmark_data_model_jsonld = "https://raw.githubusercontent.com/Sage-Bionetworks/schematic/develop/tests/data/example.single_rule.model.jsonld"
+    # benchmark_data_model_jsonld = "https://raw.githubusercontent.com/Sage-Bionetworks/schematic/develop/tests/data/example.single_rule.model.jsonld"
+    # Placeholder till the model is updated on develop
     benchmark_data_model_jsonld = "https://raw.githubusercontent.com/mialy-defelice/data_models/main/example.single_rule.model.jsonld"
     yield benchmark_data_model_jsonld
 
+
 def get_MockComponent_attribute():
     """
     Yield all of the mock conponent attributes one at a time
     TODO: pull in jsonld from fixture
     """
-    #schema_url = "https://raw.githubusercontent.com/Sage-Bionetworks/schematic/develop/tests/data/example.single_rule.model.jsonld"
+    # schema_url = "https://raw.githubusercontent.com/Sage-Bionetworks/schematic/develop/tests/data/example.single_rule.model.jsonld"
     schema_url = "https://raw.githubusercontent.com/mialy-defelice/data_models/main/example.single_rule.model.jsonld"
-    data_model_parser = DataModelParser(path_to_data_model = schema_url)
-    #Parse Model
+    data_model_parser = DataModelParser(path_to_data_model=schema_url)
+    # Parse Model
     parsed_data_model = data_model_parser.parse_model()
 
     # Instantiate DataModelGraph
@@ -91,43 +109,45 @@ def get_MockComponent_attribute():
     graph_data_model = data_model_grapher.generate_data_model_graph()
 
     dmge = DataModelGraphExplorer(graph_data_model)
-    #sg = SchemaGenerator("https://raw.githubusercontent.com/Sage-Bionetworks/schematic/develop/tests/data/example.single_rule.model.jsonld")
-    attributes=dmge.get_node_dependencies('MockComponent')
-    attributes.remove('Component')
+    # sg = SchemaGenerator("https://raw.githubusercontent.com/Sage-Bionetworks/schematic/develop/tests/data/example.single_rule.model.jsonld")
+    attributes = dmge.get_node_dependencies("MockComponent")
+    attributes.remove("Component")
 
     for MockComponent_attribute in attributes:
-        yield MockComponent_attribute   
+        yield MockComponent_attribute
+
 
 @pytest.fixture(scope="class")
-def syn_token(config:Configuration):
+def syn_token(config: Configuration):
     synapse_config_path = config.synapse_configuration_path
     config_parser = configparser.ConfigParser()
     config_parser.read(synapse_config_path)
     # try using synapse access token
     if "SYNAPSE_ACCESS_TOKEN" in os.environ:
-        token=os.environ["SYNAPSE_ACCESS_TOKEN"]
+        token = os.environ["SYNAPSE_ACCESS_TOKEN"]
     else:
         token = config_parser["authentication"]["authtoken"]
     yield token
 
+
 @pytest.fixture
 def request_headers(syn_token):
-    headers = {
-        "Authorization": "Bearer " + syn_token
-    }
+    headers = {"Authorization": "Bearer " + syn_token}
     yield headers
 
+
 @pytest.mark.schematic_api
 class TestSynapseStorage:
     @pytest.mark.synapse_credentials_needed
     @pytest.mark.parametrize("return_type", ["json", "csv"])
     def test_get_storage_assets_tables(self, client, return_type, request_headers):
-        params = {
-            "asset_view": "syn23643253",
-            "return_type": return_type
-        }
+        params = {"asset_view": "syn23643253", "return_type": return_type}
 
-        response = client.get('http://localhost:3001/v1/storage/assets/tables', query_string=params, headers=request_headers)
+        response = client.get(
+            "http://localhost:3001/v1/storage/assets/tables",
+            query_string=params,
+            headers=request_headers,
+        )
 
         assert response.status_code == 200
 
@@ -139,16 +159,16 @@ def test_get_storage_assets_tables(self, client, return_type, request_headers):
         # if return type == csv, returning a csv file
         else:
             assert response_dt.endswith("file_view_table.csv")
-        # clean up 
+        # clean up
         if os.path.exists(response_dt):
             os.remove(response_dt)
-        else: 
+        else:
             pass
-    
+
     @pytest.mark.synapse_credentials_needed
     @pytest.mark.parametrize("full_path", [True, False])
     @pytest.mark.parametrize("file_names", [None, "Sample_A.txt"])
-    def test_get_dataset_files(self,full_path, file_names, request_headers, client):
+    def test_get_dataset_files(self, full_path, file_names, request_headers, client):
         params = {
             "asset_view": "syn23643253",
             "dataset_id": "syn23643250",
@@ -157,68 +177,100 @@ def test_get_dataset_files(self,full_path, file_names, request_headers, client):
 
         if file_names:
             params["file_names"] = file_names
-        
-        response = client.get('http://localhost:3001/v1/storage/dataset/files', query_string=params, headers=request_headers)
+
+        response = client.get(
+            "http://localhost:3001/v1/storage/dataset/files",
+            query_string=params,
+            headers=request_headers,
+        )
 
         assert response.status_code == 200
         response_dt = json.loads(response.data)
 
         # would show full file path .txt in result
         if full_path:
-            if file_names: 
-                assert ["syn23643255","schematic - main/DataTypeX/Sample_A.txt"] and ["syn24226530","schematic - main/TestDatasets/TestDataset-Annotations/Sample_A.txt"] and ["syn25057024","schematic - main/TestDatasets/TestDataset-Annotations-v2/Sample_A.txt"] in response_dt
-            else: 
-                assert   ["syn23643255","schematic - main/DataTypeX/Sample_A.txt"] in response_dt
-        else: 
-            if file_names: 
-                assert ["syn23643255","Sample_A.txt"] and ["syn24226530","Sample_A.txt"] and ["syn25057024","Sample_A.txt"] in response_dt
-                assert ['syn23643256', 'Sample_C.txt'] and ['syn24226531', 'Sample_B.txt'] not in response_dt
-            else: 
-                assert ['syn23643256', 'Sample_C.txt'] and ['syn24226530', 'Sample_A.txt'] and ['syn24226531', 'Sample_B.txt'] in response_dt
-        
+            if file_names:
+                assert (
+                    ["syn23643255", "schematic - main/DataTypeX/Sample_A.txt"]
+                    and [
+                        "syn24226530",
+                        "schematic - main/TestDatasets/TestDataset-Annotations/Sample_A.txt",
+                    ]
+                    and [
+                        "syn25057024",
+                        "schematic - main/TestDatasets/TestDataset-Annotations-v2/Sample_A.txt",
+                    ]
+                    in response_dt
+                )
+            else:
+                assert [
+                    "syn23643255",
+                    "schematic - main/DataTypeX/Sample_A.txt",
+                ] in response_dt
+        else:
+            if file_names:
+                assert (
+                    ["syn23643255", "Sample_A.txt"]
+                    and ["syn24226530", "Sample_A.txt"]
+                    and ["syn25057024", "Sample_A.txt"] in response_dt
+                )
+                assert ["syn23643256", "Sample_C.txt"] and [
+                    "syn24226531",
+                    "Sample_B.txt",
+                ] not in response_dt
+            else:
+                assert (
+                    ["syn23643256", "Sample_C.txt"]
+                    and ["syn24226530", "Sample_A.txt"]
+                    and ["syn24226531", "Sample_B.txt"] in response_dt
+                )
+
     @pytest.mark.synapse_credentials_needed
     def test_get_storage_project_dataset(self, request_headers, client):
-        params = {
-        "asset_view": "syn23643253",
-        "project_id": "syn26251192"
-        }
+        params = {"asset_view": "syn23643253", "project_id": "syn26251192"}
 
-        response = client.get("http://localhost:3001/v1/storage/project/datasets", query_string = params, headers = request_headers)
+        response = client.get(
+            "http://localhost:3001/v1/storage/project/datasets",
+            query_string=params,
+            headers=request_headers,
+        )
         assert response.status_code == 200
         response_dt = json.loads(response.data)
-        assert ["syn26251193","Issue522"] in response_dt
+        assert ["syn26251193", "Issue522"] in response_dt
 
     @pytest.mark.synapse_credentials_needed
     def test_get_storage_project_manifests(self, request_headers, client):
+        params = {"asset_view": "syn23643253", "project_id": "syn30988314"}
 
-        params = {
-        "asset_view": "syn23643253",
-        "project_id": "syn30988314"
-        }
-
-        response = client.get("http://localhost:3001/v1/storage/project/manifests", query_string=params, headers=request_headers)
+        response = client.get(
+            "http://localhost:3001/v1/storage/project/manifests",
+            query_string=params,
+            headers=request_headers,
+        )
 
         assert response.status_code == 200
 
     @pytest.mark.synapse_credentials_needed
     def test_get_storage_projects(self, request_headers, client):
+        params = {"asset_view": "syn23643253"}
 
-        params = {
-        "asset_view": "syn23643253"
-        }
-
-        response = client.get("http://localhost:3001/v1/storage/projects", query_string = params, headers = request_headers)
+        response = client.get(
+            "http://localhost:3001/v1/storage/projects",
+            query_string=params,
+            headers=request_headers,
+        )
 
         assert response.status_code == 200
 
     @pytest.mark.synapse_credentials_needed
     @pytest.mark.parametrize("entity_id", ["syn34640850", "syn23643253", "syn24992754"])
     def test_get_entity_type(self, request_headers, client, entity_id):
-        params = {
-            "asset_view": "syn23643253",
-            "entity_id": entity_id
-        }
-        response = client.get("http://localhost:3001/v1/storage/entity/type", query_string = params, headers = request_headers)
+        params = {"asset_view": "syn23643253", "entity_id": entity_id}
+        response = client.get(
+            "http://localhost:3001/v1/storage/entity/type",
+            query_string=params,
+            headers=request_headers,
+        )
 
         assert response.status_code == 200
         response_dt = json.loads(response.data)
@@ -232,11 +284,12 @@ def test_get_entity_type(self, request_headers, client, entity_id):
     @pytest.mark.synapse_credentials_needed
     @pytest.mark.parametrize("entity_id", ["syn30988314", "syn27221721"])
     def test_if_in_assetview(self, request_headers, client, entity_id):
-        params = {
-            "asset_view": "syn23643253",
-            "entity_id": entity_id
-        }
-        response = client.get("http://localhost:3001/v1/storage/if_in_asset_view", query_string = params, headers = request_headers)        
+        params = {"asset_view": "syn23643253", "entity_id": entity_id}
+        response = client.get(
+            "http://localhost:3001/v1/storage/if_in_asset_view",
+            query_string=params,
+            headers=request_headers,
+        )
         assert response.status_code == 200
         response_dt = json.loads(response.data)
 
@@ -245,38 +298,47 @@ def test_if_in_assetview(self, request_headers, client, entity_id):
         elif entity_id == "syn27221721":
             assert response_dt == False
 
+
 @pytest.mark.schematic_api
 class TestMetadataModelOperation:
-    @pytest.mark.parametrize("as_graph", [True, False]) 
+    @pytest.mark.parametrize("as_graph", [True, False])
     def test_component_requirement(self, client, data_model_jsonld, as_graph):
         params = {
             "schema_url": data_model_jsonld,
-            "source_component": "BulkRNA-seqAssay", 
-            "as_graph": as_graph
+            "source_component": "BulkRNA-seqAssay",
+            "as_graph": as_graph,
         }
 
-        response = client.get("http://localhost:3001/v1/model/component-requirements", query_string = params)
+        response = client.get(
+            "http://localhost:3001/v1/model/component-requirements", query_string=params
+        )
 
         assert response.status_code == 200
 
         response_dt = json.loads(response.data)
 
         if as_graph:
-            assert response_dt == [['Biospecimen','Patient'],['BulkRNA-seqAssay','Biospecimen']]
-        else: 
-            assert response_dt == ['Patient','Biospecimen','BulkRNA-seqAssay']
+            assert response_dt == [
+                ["Biospecimen", "Patient"],
+                ["BulkRNA-seqAssay", "Biospecimen"],
+            ]
+        else:
+            assert response_dt == ["Patient", "Biospecimen", "BulkRNA-seqAssay"]
 
 
 @pytest.mark.schematic_api
 class TestUtilsOperation:
-    @pytest.mark.parametrize("strict_camel_case", [True, False]) 
+    @pytest.mark.parametrize("strict_camel_case", [True, False])
     def test_get_property_label_from_display_name(self, client, strict_camel_case):
         params = {
             "display_name": "mocular entity",
-            "strict_camel_case": strict_camel_case
+            "strict_camel_case": strict_camel_case,
         }
 
-        response = client.get("http://localhost:3001/v1/utils/get_property_label_from_display_name", query_string = params)
+        response = client.get(
+            "http://localhost:3001/v1/utils/get_property_label_from_display_name",
+            query_string=params,
+        )
         assert response.status_code == 200
 
         response_dt = json.loads(response.data)
@@ -290,10 +352,11 @@ def test_get_property_label_from_display_name(self, client, strict_camel_case):
 @pytest.mark.schematic_api
 class TestDataModelGraphExplorerOperation:
     def test_get_schema(self, client, data_model_jsonld):
-        params = {
-            "schema_url": data_model_jsonld
-        }
-        response = client.get("http://localhost:3001/v1/schemas/get/schema", query_string = params)
+        params = {"schema_url": data_model_jsonld,
+                  "data_model_labels": 'class_label'}
+        response = client.get(
+            "http://localhost:3001/v1/schemas/get/schema", query_string=params
+        )
 
         response_dt = response.data
         assert response.status_code == 200
@@ -304,61 +367,72 @@ def test_get_schema(self, client, data_model_jsonld):
             os.remove(response_dt)
 
     def test_if_node_required(test, client, data_model_jsonld):
-        params = {
-            "schema_url": data_model_jsonld,
-            "node_display_name": "FamilyHistory"
-        }
+        params = {"schema_url": data_model_jsonld, "node_display_name": "FamilyHistory", "data_model_labels": "class_label"}
 
-        response = client.get("http://localhost:3001/v1/schemas/is_node_required", query_string = params)
+        response = client.get(
+            "http://localhost:3001/v1/schemas/is_node_required", query_string=params
+        )
         response_dta = json.loads(response.data)
         assert response.status_code == 200
         assert response_dta == True
+
     def test_get_node_validation_rules(test, client, data_model_jsonld):
         params = {
             "schema_url": data_model_jsonld,
-            "node_display_name": "CheckRegexList"
+            "node_display_name": "CheckRegexList",
         }
-        response = client.get("http://localhost:3001/v1/schemas/get_node_validation_rules", query_string = params)
+        response = client.get(
+            "http://localhost:3001/v1/schemas/get_node_validation_rules",
+            query_string=params,
+        )
         response_dta = json.loads(response.data)
         assert response.status_code == 200
         assert "list strict" in response_dta
-        assert "regex match [a-f]" in response_dta        
+        assert "regex match [a-f]" in response_dta
 
     def test_get_nodes_display_names(test, client, data_model_jsonld):
         params = {
             "schema_url": data_model_jsonld,
-            "node_list": ["FamilyHistory", "Biospecimen"]
+            "node_list": ["FamilyHistory", "Biospecimen"],
         }
-        response = client.get("http://localhost:3001/v1/schemas/get_nodes_display_names", query_string = params)
+        response = client.get(
+            "http://localhost:3001/v1/schemas/get_nodes_display_names",
+            query_string=params,
+        )
         response_dta = json.loads(response.data)
         assert response.status_code == 200
         assert "Family History" and "Biospecimen" in response_dta
 
-    @pytest.mark.parametrize("relationship", ["parentOf", "requiresDependency", "rangeValue", "domainValue"])
+    @pytest.mark.parametrize(
+        "relationship", ["parentOf", "requiresDependency", "rangeValue", "domainValue"]
+    )
     def test_get_subgraph_by_edge(self, client, data_model_jsonld, relationship):
-        params = {
-            "schema_url": data_model_jsonld,
-            "relationship": relationship
-        }
+        params = {"schema_url": data_model_jsonld, "relationship": relationship}
 
-        response = client.get("http://localhost:3001/v1/schemas/get/graph_by_edge_type", query_string=params)
+        response = client.get(
+            "http://localhost:3001/v1/schemas/get/graph_by_edge_type",
+            query_string=params,
+        )
         assert response.status_code == 200
 
-
     @pytest.mark.parametrize("return_display_names", [True, False])
     @pytest.mark.parametrize("node_label", ["FamilyHistory", "TissueStatus"])
-    def test_get_node_range(self, client, data_model_jsonld, return_display_names, node_label):
+    def test_get_node_range(
+        self, client, data_model_jsonld, return_display_names, node_label
+    ):
         params = {
             "schema_url": data_model_jsonld,
             "return_display_names": return_display_names,
-            "node_label": node_label
+            "node_label": node_label,
         }
 
-        response = client.get('http://localhost:3001/v1/schemas/get_node_range', query_string=params)
+        response = client.get(
+            "http://localhost:3001/v1/schemas/get_node_range", query_string=params
+        )
         response_dt = json.loads(response.data)
         assert response.status_code == 200
 
-        if "node_label" == "FamilyHistory": 
+        if "node_label" == "FamilyHistory":
             assert "Breast" in response_dt
             assert "Lung" in response_dt
 
@@ -369,8 +443,14 @@ def test_get_node_range(self, client, data_model_jsonld, return_display_names, n
     @pytest.mark.parametrize("return_display_names", [None, True, False])
     @pytest.mark.parametrize("return_schema_ordered", [None, True, False])
     @pytest.mark.parametrize("source_node", ["Patient", "Biospecimen"])
-    def test_node_dependencies(self, client, data_model_jsonld, source_node, return_display_names, return_schema_ordered):
-
+    def test_node_dependencies(
+        self,
+        client,
+        data_model_jsonld,
+        source_node,
+        return_display_names,
+        return_schema_ordered,
+    ):
         return_display_names = True
         return_schema_ordered = False
 
@@ -378,10 +458,13 @@ def test_node_dependencies(self, client, data_model_jsonld, source_node, return_
             "schema_url": data_model_jsonld,
             "source_node": source_node,
             "return_display_names": return_display_names,
-            "return_schema_ordered": return_schema_ordered
+            "return_schema_ordered": return_schema_ordered,
         }
 
-        response = client.get('http://localhost:3001/v1/schemas/get_node_dependencies', query_string=params)
+        response = client.get(
+            "http://localhost:3001/v1/schemas/get_node_dependencies",
+            query_string=params,
+        )
         response_dt = json.loads(response.data)
         assert response.status_code == 200
 
@@ -392,71 +475,93 @@ def test_node_dependencies(self, client, data_model_jsonld, source_node, return_
 
                 # by default, return_schema_ordered is set to True
                 if return_schema_ordered == True or return_schema_ordered == None:
-                    assert response_dt == ["Patient ID","Sex","Year of Birth","Diagnosis","Component"]
-                else: 
+                    assert response_dt == [
+                        "Patient ID",
+                        "Sex",
+                        "Year of Birth",
+                        "Diagnosis",
+                        "Component",
+                    ]
+                else:
                     assert "Year of Birth" in response_dt
                     assert "Diagnosis" in response_dt
-                    assert "Patient ID" in response_dt            
+                    assert "Patient ID" in response_dt
             else:
                 assert "YearofBirth" in response_dt
 
         elif source_node == "Biospecimen":
             if return_display_names == True or return_display_names == None:
                 assert "Tissue Status" in response_dt
-            else: 
+            else:
                 assert "TissueStatus" in response_dt
 
+
 @pytest.mark.schematic_api
 class TestManifestOperation:
-
     def ifExcelExists(self, response, file_name):
         # return one excel file
-        d = response.headers['content-disposition']
+        d = response.headers["content-disposition"]
         fname = re.findall("filename=(.+)", d)[0]
         assert fname == file_name
-    
+
     def ifGoogleSheetExists(self, response_dt):
-        for i in response_dt: 
+        for i in response_dt:
             assert i.startswith("https://docs.google.com/")
+
     def ifPandasDataframe(self, response_dt):
         for i in response_dt:
             df = pd.read_json(i)
             assert isinstance(df, pd.DataFrame)
 
-
     @pytest.mark.empty_token
-    #@pytest.mark.parametrize("output_format", [None, "excel", "google_sheet", "dataframe (only if getting existing manifests)"])
+    # @pytest.mark.parametrize("output_format", [None, "excel", "google_sheet", "dataframe (only if getting existing manifests)"])
     @pytest.mark.parametrize("output_format", ["excel"])
-    @pytest.mark.parametrize("data_type", ["Biospecimen", "Patient", "all manifests", ["Biospecimen", "Patient"]])
-    def test_generate_existing_manifest(self, client, data_model_jsonld, data_type, output_format, caplog, request_headers):
+    @pytest.mark.parametrize(
+        "data_type",
+        ["Biospecimen", "Patient", "all manifests", ["Biospecimen", "Patient"]],
+    )
+    def test_generate_existing_manifest(
+        self,
+        client,
+        data_model_jsonld,
+        data_type,
+        output_format,
+        caplog,
+        request_headers,
+    ):
         # set dataset
         if data_type == "Patient":
-            dataset_id = ["syn51730545"] #Mock Patient Manifest folder on synapse
+            dataset_id = ["syn51730545"]  # Mock Patient Manifest folder on synapse
         elif data_type == "Biospecimen":
-            dataset_id = ["syn51730547"] #Mock biospecimen manifest folder
+            dataset_id = ["syn51730547"]  # Mock biospecimen manifest folder
         elif data_type == ["Biospecimen", "Patient"]:
             dataset_id = ["syn51730547", "syn51730545"]
-        else: 
-            dataset_id = None #if "all manifests", dataset id is None
+        else:
+            dataset_id = None  # if "all manifests", dataset id is None
 
         params = {
             "schema_url": data_model_jsonld,
             "asset_view": "syn23643253",
             "title": "Example",
             "data_type": data_type,
-            "use_annotations": False, 
-            }
-        
+            "use_annotations": False,
+            "data_model_labels": "class_label",
+        }
+
         # Previous form of the test had `access_token` set to `None`
         request_headers["Authorization"] = None
 
-        if dataset_id: 
-            params['dataset_id'] = dataset_id
-        
-        if output_format: 
-            params['output_format'] = output_format
+        if dataset_id:
+            params["dataset_id"] = dataset_id
+
+        if output_format:
+            params["output_format"] = output_format
 
-        response = client.get('http://localhost:3001/v1/manifest/generate', query_string=params, headers=request_headers)
+        response = client.get(
+            "http://localhost:3001/v1/manifest/generate",
+            query_string=params,
+            headers=request_headers,
+        )
 
         assert response.status_code == 200
 
@@ -466,28 +571,48 @@ def test_generate_existing_manifest(self, client, data_model_jsonld, data_type,
                 if isinstance(data_type, list) and len(data_type) > 1:
                     # return warning message
                     for record in caplog.records:
-                        if record.message == "Currently we do not support returning multiple files as Excel format at once.":
+                        if (
+                            record.message
+                            == "Currently we do not support returning multiple files as Excel format at once."
+                        ):
                             assert record.levelname == "WARNING"
                     self.ifExcelExists(response, "Example.Biospecimen.manifest.xlsx")
                 # for single data type
-                else: 
+                else:
                     self.ifExcelExists(response, "Example.xlsx")
             else:
                 response_dt = json.loads(response.data)
                 if "dataframe" in output_format:
                     self.ifPandasDataframe(response_dt)
                     assert len(response_dt) == len(dataset_id)
-                else: 
+                else:
                     self.ifGoogleSheetExists(response_dt)
         else:
             response_dt = json.loads(response.data)
             self.ifGoogleSheetExists(response_dt)
 
-
     @pytest.mark.empty_token
-    @pytest.mark.parametrize("output_format", ["excel", "google_sheet", "dataframe (only if getting existing manifests)", None])
-    @pytest.mark.parametrize("data_type", ["all manifests", ["Biospecimen", "Patient"], "Patient"])
-    def test_generate_new_manifest(self, caplog, client, data_model_jsonld, data_type, output_format, request_headers):
+    @pytest.mark.parametrize(
+        "output_format",
+        [
+            "excel",
+            "google_sheet",
+            "dataframe (only if getting existing manifests)",
+            None,
+        ],
+    )
+    @pytest.mark.parametrize(
+        "data_type", ["all manifests", ["Biospecimen", "Patient"], "Patient"]
+    )
+    def test_generate_new_manifest(
+        self,
+        caplog,
+        client,
+        data_model_jsonld,
+        data_type,
+        output_format,
+        request_headers,
+    ):
         params = {
             "schema_url": data_model_jsonld,
             "asset_view": "syn23643253",
@@ -500,29 +625,37 @@ def test_generate_new_manifest(self, caplog, client, data_model_jsonld, data_typ
         # Previous form of the test had `access_token` set to `None`
         request_headers["Authorization"] = None
 
-        if output_format: 
+        if output_format:
             params["output_format"] = output_format
-    
 
-        response = client.get('http://localhost:3001/v1/manifest/generate', query_string=params, headers=request_headers)
+        response = client.get(
+            "http://localhost:3001/v1/manifest/generate",
+            query_string=params,
+            headers=request_headers,
+        )
         assert response.status_code == 200
 
-
         if output_format and output_format == "excel":
             if data_type == "all manifests":
                 # return error message
                 for record in caplog.records:
-                    if record.message == "Currently we do not support returning multiple files as Excel format at once.":
+                    if (
+                        record.message
+                        == "Currently we do not support returning multiple files as Excel format at once."
+                    ):
                         assert record.levelname == "WARNING"
             elif isinstance(data_type, list) and len(data_type) > 1:
                 # return warning message
                 for record in caplog.records:
-                    if record.message == "Currently we do not support returning multiple files as Excel format at once.":
+                    if (
+                        record.message
+                        == "Currently we do not support returning multiple files as Excel format at once."
+                    ):
                         assert record.levelname == "WARNING"
                 self.ifExcelExists(response, "Example.Biospecimen.manifest.xlsx")
             else:
                 self.ifExcelExists(response, "Example.xlsx")
-        
+
         # return one or multiple google sheet links in all other cases
         # note: output_format == dataframe only matters when dataset_id is not None
         else:
@@ -531,34 +664,75 @@ def test_generate_new_manifest(self, caplog, client, data_model_jsonld, data_typ
 
             if data_type == "all manifests":
                 assert len(response_dt) == 3
-            elif isinstance(data_type, list) and len(data_type) >1:
+            elif isinstance(data_type, list) and len(data_type) > 1:
                 assert len(response_dt) == 2
-            else: 
+            else:
                 assert len(response_dt) == 1
-    
+
     # test case: generate a manifest when use_annotations is set to True/False for a file-based component
     # based on the parameter, the columns in the manifests would be different
-    # the dataset folder does not contain an existing manifest 
-    @pytest.mark.parametrize("use_annotations,expected",[(True, ['Filename', 'Sample ID', 'File Format', 'Component', 'Genome Build', 'Genome FASTA', 'impact', 'Year of Birth', 'date', 'confidence', 'IsImportantBool', 'IsImportantText', 'author', 'eTag', 'entityId']), 
-    (False, ['Filename', 'Sample ID', 'File Format', 'Component', 'Genome Build', 'Genome FASTA', 'entityId'])])
-    def test_generate_manifest_file_based_annotations(self, client, use_annotations, expected, data_model_jsonld):
+    # the dataset folder does not contain an existing manifest
+    @pytest.mark.parametrize(
+        "use_annotations,expected",
+        [
+            (
+                True,
+                [
+                    "Filename",
+                    "Sample ID",
+                    "File Format",
+                    "Component",
+                    "Genome Build",
+                    "Genome FASTA",
+                    "impact",
+                    "Year of Birth",
+                    "date",
+                    "confidence",
+                    "IsImportantBool",
+                    "IsImportantText",
+                    "author",
+                    "eTag",
+                    "entityId",
+                ],
+            ),
+            (
+                False,
+                [
+                    "Filename",
+                    "Sample ID",
+                    "File Format",
+                    "Component",
+                    "Genome Build",
+                    "Genome FASTA",
+                    "entityId",
+                ],
+            ),
+        ],
+    )
+    def test_generate_manifest_file_based_annotations(
+        self, client, use_annotations, expected, data_model_jsonld
+    ):
         params = {
             "schema_url": data_model_jsonld,
             "data_type": "BulkRNA-seqAssay",
             "dataset_id": "syn25614635",
             "asset_view": "syn51707141",
-            "output_format": "google_sheet", 
-            "use_annotations": use_annotations
+            "output_format": "google_sheet",
+            "use_annotations": use_annotations,
         }
 
-        response = client.get('http://localhost:3001/v1/manifest/generate', query_string=params)
+        response = client.get(
+            "http://localhost:3001/v1/manifest/generate", query_string=params
+        )
         assert response.status_code == 200
 
         response_google_sheet = json.loads(response.data)
-        
-        # open the google sheet 
-        google_sheet_df = pd.read_csv(response_google_sheet[0] + '/export?gid=0&format=csv')
-        
+
+        # open the google sheet
+        google_sheet_df = pd.read_csv(
+            response_google_sheet[0] + "/export?gid=0&format=csv"
+        )
+
         # make sure that columns used in annotations get added
         # and also make sure that entityId column appears in the end
 
@@ -567,81 +741,126 @@ def test_generate_manifest_file_based_annotations(self, client, use_annotations,
         assert sorted(google_sheet_df.columns.to_list()) == sorted(expected)
 
         # make sure Filename, entityId, and component get filled with correct value
-        assert google_sheet_df["Filename"].to_list() == ["TestDataset-Annotations-v3/Sample_A.txt", "TestDataset-Annotations-v3/Sample_B.txt", "TestDataset-Annotations-v3/Sample_C.txt"]
-        assert google_sheet_df["entityId"].to_list() == ["syn25614636", "syn25614637", "syn25614638"]
-        assert google_sheet_df["Component"].to_list() == ["BulkRNA-seqAssay", "BulkRNA-seqAssay", "BulkRNA-seqAssay"]
+        assert google_sheet_df["Filename"].to_list() == [
+            "TestDataset-Annotations-v3/Sample_A.txt",
+            "TestDataset-Annotations-v3/Sample_B.txt",
+            "TestDataset-Annotations-v3/Sample_C.txt",
+        ]
+        assert google_sheet_df["entityId"].to_list() == [
+            "syn25614636",
+            "syn25614637",
+            "syn25614638",
+        ]
+        assert google_sheet_df["Component"].to_list() == [
+            "BulkRNA-seqAssay",
+            "BulkRNA-seqAssay",
+            "BulkRNA-seqAssay",
+        ]
 
     # test case: generate a manifest with annotations when use_annotations is set to True for a component that is not file-based
-    # the dataset folder does not contain an existing manifest 
-    def test_generate_manifest_not_file_based_with_annotations(self, client, data_model_jsonld):
+    # the dataset folder does not contain an existing manifest
+    def test_generate_manifest_not_file_based_with_annotations(
+        self, client, data_model_jsonld
+    ):
         params = {
             "schema_url": data_model_jsonld,
             "data_type": "Patient",
             "dataset_id": "syn25614635",
             "asset_view": "syn51707141",
-            "output_format": "google_sheet", 
-            "use_annotations": False        
+            "output_format": "google_sheet",
+            "use_annotations": False,
         }
-        response = client.get('http://localhost:3001/v1/manifest/generate', query_string=params)
+        response = client.get(
+            "http://localhost:3001/v1/manifest/generate", query_string=params
+        )
         assert response.status_code == 200
 
         response_google_sheet = json.loads(response.data)
 
-        # open the google sheet 
-        google_sheet_df = pd.read_csv(response_google_sheet[0] + '/export?gid=0&format=csv')
+        # open the google sheet
+        google_sheet_df = pd.read_csv(
+            response_google_sheet[0] + "/export?gid=0&format=csv"
+        )
 
         # make sure that the result is basically the same as generating a new manifest
-        assert sorted(google_sheet_df.columns) == sorted(['Patient ID', 'Sex', 'Year of Birth', 'Diagnosis', 'Component', 'Cancer Type', 'Family History'])
-        
+        assert sorted(google_sheet_df.columns) == sorted(
+            [
+                "Patient ID",
+                "Sex",
+                "Year of Birth",
+                "Diagnosis",
+                "Component",
+                "Cancer Type",
+                "Family History",
+            ]
+        )
+
     def test_populate_manifest(self, client, data_model_jsonld, test_manifest_csv):
         # test manifest
         test_manifest_data = open(test_manifest_csv, "rb")
-        
+
         params = {
             "data_type": "MockComponent",
             "schema_url": data_model_jsonld,
             "title": "Example",
-            "csv_file": test_manifest_data
+            "csv_file": test_manifest_data,
         }
 
-        response = client.get('http://localhost:3001/v1/manifest/generate', query_string=params)
+        response = client.get(
+            "http://localhost:3001/v1/manifest/generate", query_string=params
+        )
 
         assert response.status_code == 200
         response_dt = json.loads(response.data)
-    
-        # should return a list with one google sheet link 
+
+        # should return a list with one google sheet link
         assert isinstance(response_dt[0], str)
         assert response_dt[0].startswith("https://docs.google.com/")
 
     @pytest.mark.parametrize("restrict_rules", [False, True, None])
-    @pytest.mark.parametrize("json_str", [None, '[{"Patient ID": 123, "Sex": "Female", "Year of Birth": "", "Diagnosis": "Healthy", "Component": "Patient", "Cancer Type": "Breast", "Family History": "Breast, Lung"}]'])
-    def test_validate_manifest(self, data_model_jsonld, client, json_str, restrict_rules, test_manifest_csv, request_headers):
-
-        params = {
-            "schema_url": data_model_jsonld,
-            "restrict_rules": restrict_rules
-        }
+    @pytest.mark.parametrize(
+        "json_str",
+        [
+            None,
+            '[{"Patient ID": 123, "Sex": "Female", "Year of Birth": "", "Diagnosis": "Healthy", "Component": "Patient", "Cancer Type": "Breast", "Family History": "Breast, Lung"}]',
+        ],
+    )
+    def test_validate_manifest(
+        self,
+        data_model_jsonld,
+        client,
+        json_str,
+        restrict_rules,
+        test_manifest_csv,
+        request_headers,
+    ):
+        params = {"schema_url": data_model_jsonld, "restrict_rules": restrict_rules}
 
         if json_str:
             params["json_str"] = json_str
             params["data_type"] = "Patient"
-            response = client.post('http://localhost:3001/v1/model/validate', query_string=params)
+            response = client.post(
+                "http://localhost:3001/v1/model/validate", query_string=params
+            )
             response_dt = json.loads(response.data)
             assert response.status_code == 200
 
-        else: 
+        else:
             params["data_type"] = "MockComponent"
 
-            request_headers.update({
-            'Content-Type': "multipart/form-data",
-            'Accept': "application/json"
-            })
+            request_headers.update(
+                {"Content-Type": "multipart/form-data", "Accept": "application/json"}
+            )
 
             # test uploading a csv file
-            response_csv = client.post('http://localhost:3001/v1/model/validate', query_string=params, data={"file_name": (open(test_manifest_csv, 'rb'), "test.csv")}, headers=request_headers)
+            response_csv = client.post(
+                "http://localhost:3001/v1/model/validate",
+                query_string=params,
+                data={"file_name": (open(test_manifest_csv, "rb"), "test.csv")},
+                headers=request_headers,
+            )
             response_dt = json.loads(response_csv.data)
             assert response_csv.status_code == 200
-            
 
             # test uploading a json file
             # change data type to patient since the testing json manifest is using Patient component
@@ -656,46 +875,67 @@ def test_validate_manifest(self, data_model_jsonld, client, json_str, restrict_r
 
     @pytest.mark.synapse_credentials_needed
     def test_get_datatype_manifest(self, client, request_headers):
-        params = {
-            "asset_view": "syn23643253",
-            "manifest_id": "syn27600110"
-        }
+        params = {"asset_view": "syn23643253", "manifest_id": "syn27600110"}
 
-        response = client.get('http://localhost:3001/v1/get/datatype/manifest', query_string=params, headers=request_headers)  
+        response = client.get(
+            "http://localhost:3001/v1/get/datatype/manifest",
+            query_string=params,
+            headers=request_headers,
+        )
 
         assert response.status_code == 200
         response_dt = json.loads(response.data)
-        assert response_dt =={
-                "Cancer Type": "string",
-                "Component": "string",
-                "Diagnosis": "string",
-                "Family History": "string",
-                "Patient ID": "Int64",
-                "Sex": "string",
-                "Year of Birth": "Int64",
-                "entityId": "string"}
+        assert response_dt == {
+            "Cancer Type": "string",
+            "Component": "string",
+            "Diagnosis": "string",
+            "Family History": "string",
+            "Patient ID": "Int64",
+            "Sex": "string",
+            "Year of Birth": "Int64",
+            "entityId": "string",
+        }
 
     @pytest.mark.synapse_credentials_needed
     # small manifest: syn51078535; big manifest: syn51156998
-    @pytest.mark.parametrize("manifest_id, expected_component, expected_file_name", [("syn51078535", "BulkRNA-seqAssay", "synapse_storage_manifest.csv"), ("syn51156998", "Biospecimen", "synapse_storage_manifest_biospecimen.csv")])
-    @pytest.mark.parametrize("new_manifest_name",[None,"Example.csv"]) 
-    @pytest.mark.parametrize("as_json",[None,True,False]) 
-    def test_manifest_download(self, config: Configuration, client, request_headers, manifest_id, new_manifest_name, as_json, expected_component, expected_file_name):
+    @pytest.mark.parametrize(
+        "manifest_id, expected_component, expected_file_name",
+        [
+            ("syn51078535", "BulkRNA-seqAssay", "synapse_storage_manifest.csv"),
+            ("syn51156998", "Biospecimen", "synapse_storage_manifest_biospecimen.csv"),
+        ],
+    )
+    @pytest.mark.parametrize("new_manifest_name", [None, "Example.csv"])
+    @pytest.mark.parametrize("as_json", [None, True, False])
+    def test_manifest_download(
+        self,
+        config: Configuration,
+        client,
+        request_headers,
+        manifest_id,
+        new_manifest_name,
+        as_json,
+        expected_component,
+        expected_file_name,
+    ):
         params = {
             "manifest_id": manifest_id,
-            "new_manifest_name": new_manifest_name, 
-            "as_json": as_json
-
+            "new_manifest_name": new_manifest_name,
+            "as_json": as_json,
         }
 
-        response = client.get('http://localhost:3001/v1/manifest/download', query_string = params, headers = request_headers)
+        response = client.get(
+            "http://localhost:3001/v1/manifest/download",
+            query_string=params,
+            headers=request_headers,
+        )
         assert response.status_code == 200
 
         # if as_json is set to True or as_json is not defined, then a json gets returned
         if as_json or as_json is None:
             response_dta = json.loads(response.data)
 
-            # check if the correct manifest gets downloaded 
+            # check if the correct manifest gets downloaded
             assert response_dta[0]["Component"] == expected_component
 
             current_work_dir = os.getcwd()
@@ -704,10 +944,12 @@ def test_manifest_download(self, config: Configuration, client, request_headers,
 
             # if a manfiest gets renamed, get new manifest file path
             if new_manifest_name:
-                manifest_file_path = os.path.join(folder_dir, new_manifest_name + '.' + 'csv')
+                manifest_file_path = os.path.join(
+                    folder_dir, new_manifest_name + "." + "csv"
+                )
             # if a manifest does not get renamed, get existing manifest file path
-            else: 
-                manifest_file_path = os.path.join(folder_dir,expected_file_name)
+            else:
+                manifest_file_path = os.path.join(folder_dir, expected_file_name)
 
         else:
             # manifest file path gets returned
@@ -716,47 +958,55 @@ def test_manifest_download(self, config: Configuration, client, request_headers,
             file_base_name = os.path.basename(manifest_file_path)
             file_name = os.path.splitext(file_base_name)[0]
 
-            if new_manifest_name: 
+            if new_manifest_name:
                 assert file_name == new_manifest_name
 
         # make sure file gets correctly downloaded
         assert os.path.exists(manifest_file_path)
 
-        #delete files
-        try: 
+        # delete files
+        try:
             os.remove(manifest_file_path)
-        except: 
+        except:
             pass
 
     @pytest.mark.synapse_credentials_needed
     # test downloading a manifest with access restriction and see if the correct error message got raised
     def test_download_access_restricted_manifest(self, client, request_headers):
-        params = {
-            "manifest_id": "syn29862078"
-        }  
+        params = {"manifest_id": "syn29862078"}
 
-        response = client.get('http://localhost:3001/v1/manifest/download', query_string = params, headers = request_headers)
+        response = client.get(
+            "http://localhost:3001/v1/manifest/download",
+            query_string=params,
+            headers=request_headers,
+        )
         assert response.status_code == 500
         with pytest.raises(TypeError) as exc_info:
-            raise TypeError('the type error got raised')
+            raise TypeError("the type error got raised")
         assert exc_info.value.args[0] == "the type error got raised"
-    
+
     @pytest.mark.synapse_credentials_needed
     @pytest.mark.parametrize("as_json", [None, True, False])
     @pytest.mark.parametrize("new_manifest_name", [None, "Test"])
-    def test_dataset_manifest_download(self, client, as_json, request_headers, new_manifest_name):
+    def test_dataset_manifest_download(
+        self, client, as_json, request_headers, new_manifest_name
+    ):
         params = {
             "asset_view": "syn28559058",
             "dataset_id": "syn28268700",
             "as_json": as_json,
-            "new_manifest_name": new_manifest_name
+            "new_manifest_name": new_manifest_name,
         }
 
-        response = client.get('http://localhost:3001/v1/dataset/manifest/download', query_string = params, headers = request_headers)
+        response = client.get(
+            "http://localhost:3001/v1/dataset/manifest/download",
+            query_string=params,
+            headers=request_headers,
+        )
         assert response.status_code == 200
         response_dt = response.data
 
-        if as_json: 
+        if as_json:
             response_json = json.loads(response_dt)
             assert response_json[0]["Component"] == "BulkRNA-seqAssay"
             assert response_json[0]["File Format"] == "CSV/TSV"
@@ -764,50 +1014,72 @@ def test_dataset_manifest_download(self, client, as_json, request_headers, new_m
             assert response_json[0]["entityId"] == "syn28278954"
         else:
             # return a file path
-            response_path = response_dt.decode('utf-8')
+            response_path = response_dt.decode("utf-8")
 
             assert isinstance(response_path, str)
             assert response_path.endswith(".csv")
 
     @pytest.mark.synapse_credentials_needed
     @pytest.mark.submission
-    def test_submit_manifest_table_and_file_replace(self, client, request_headers, data_model_jsonld, test_manifest_submit):
-        """Testing submit manifest in a csv format as a table and a file. Only replace the table
-        """
+    def test_submit_manifest_table_and_file_replace(
+        self, client, request_headers, data_model_jsonld, test_manifest_submit
+    ):
+        """Testing submit manifest in a csv format as a table and a file. Only replace the table"""
         params = {
             "schema_url": data_model_jsonld,
             "data_type": "Biospecimen",
-            "restrict_rules": False, 
-            "hide_blanks": False, 
+            "restrict_rules": False,
+            "hide_blanks": False,
             "manifest_record_type": "table_and_file",
             "asset_view": "syn51514344",
             "dataset_id": "syn51514345",
-            "table_manipulation": 'replace',
-            "use_schema_label": True
+            "table_manipulation": "replace",
+            "data_model_labels": "class_label",
+            "table_column_names": "class_label",
         }
 
-        response_csv = client.post('http://localhost:3001/v1/model/submit', query_string=params, data={"file_name": (open(test_manifest_submit, 'rb'), "test.csv")}, headers=request_headers)
+        response_csv = client.post(
+            "http://localhost:3001/v1/model/submit",
+            query_string=params,
+            data={"file_name": (open(test_manifest_submit, "rb"), "test.csv")},
+            headers=request_headers,
+        )
         assert response_csv.status_code == 200
 
     @pytest.mark.synapse_credentials_needed
     @pytest.mark.submission
-    @pytest.mark.parametrize("data_type, manifest_path_fixture",[("Biospecimen","test_manifest_submit"), ("MockComponent", "test_manifest_csv")])
-    def test_submit_manifest_file_only_replace(self, helpers, client, request_headers, data_model_jsonld, data_type, manifest_path_fixture, request):
-        """Testing submit manifest in a csv format as a file
-        """
+    @pytest.mark.parametrize(
+        "data_type, manifest_path_fixture",
+        [
+            ("Biospecimen", "test_manifest_submit"),
+            ("MockComponent", "test_manifest_csv"),
+        ],
+    )
+    def test_submit_manifest_file_only_replace(
+        self,
+        helpers,
+        client,
+        request_headers,
+        data_model_jsonld,
+        data_type,
+        manifest_path_fixture,
+        request,
+    ):
+        """Testing submit manifest in a csv format as a file"""
         params = {
             "schema_url": data_model_jsonld,
             "data_type": data_type,
-            "restrict_rules": False, 
+            "restrict_rules": False,
             "manifest_record_type": "file_only",
-            "table_manipulation": 'replace',
-            "use_schema_label": True
+            "table_manipulation": "replace",
+            "data_model_labels": "class_label",
+            "table_column_names": "class_label",
         }
 
         if data_type == "Biospecimen":
             specific_params = {
-            "asset_view": "syn51514344",
-            "dataset_id": "syn51514345",
+                "asset_view": "syn51514344",
+                "dataset_id": "syn51514345",
             }
 
         elif data_type == "MockComponent":
@@ -815,119 +1087,174 @@ def test_submit_manifest_file_only_replace(self, helpers, client, request_header
 
             if python_version == "3.10":
                 dataset_id = "syn52656106"
-            elif python_version =="3.9":
+            elif python_version == "3.9":
                 dataset_id = "syn52656104"
 
-            specific_params = {
-            "asset_view": "syn23643253",
-            "dataset_id": dataset_id
-            }
+            specific_params = {"asset_view": "syn23643253", "dataset_id": dataset_id}
 
         params.update(specific_params)
 
         manifest_path = request.getfixturevalue(manifest_path_fixture)
-        response_csv = client.post('http://localhost:3001/v1/model/submit', query_string=params, data={"file_name": (open(manifest_path, 'rb'), "test.csv")}, headers=request_headers)
-        assert response_csv.status_code == 200 
+        response_csv = client.post(
+            "http://localhost:3001/v1/model/submit",
+            query_string=params,
+            data={"file_name": (open(manifest_path, "rb"), "test.csv")},
+            headers=request_headers,
+        )
+        assert response_csv.status_code == 200
 
-    @pytest.mark.synapse_credentials_needed    
+    @pytest.mark.synapse_credentials_needed
     @pytest.mark.submission
-    def test_submit_manifest_json_str_replace(self, client, request_headers, data_model_jsonld):
-        """Submit json str as a file
-        """
+    def test_submit_manifest_json_str_replace(
+        self, client, request_headers, data_model_jsonld
+    ):
+        """Submit json str as a file"""
         json_str = '[{"Sample ID": 123, "Patient ID": 1,"Tissue Status": "Healthy","Component": "Biospecimen"}]'
         params = {
             "schema_url": data_model_jsonld,
             "data_type": "Biospecimen",
             "json_str": json_str,
-            "restrict_rules": False, 
+            "restrict_rules": False,
             "manifest_record_type": "file_only",
             "asset_view": "syn51514344",
             "dataset_id": "syn51514345",
-            "table_manipulation": 'replace',
-            "use_schema_label": True
+            "table_manipulation": "replace",
+            "data_model_labels": "class_label",
+            "table_column_names": "class_label",
         }
         params["json_str"] = json_str
-        response = client.post('http://localhost:3001/v1/model/submit', query_string = params, data={"file_name":''}, headers = request_headers)
+        response = client.post(
+            "http://localhost:3001/v1/model/submit",
+            query_string=params,
+            data={"file_name": ""},
+            headers=request_headers,
+        )
         assert response.status_code == 200
 
     @pytest.mark.synapse_credentials_needed
     @pytest.mark.submission
-    def test_submit_manifest_w_file_and_entities(self, client, request_headers, data_model_jsonld, test_manifest_submit):
+    def test_submit_manifest_w_file_and_entities(
+        self, client, request_headers, data_model_jsonld, test_manifest_submit
+    ):
         params = {
             "schema_url": data_model_jsonld,
             "data_type": "Biospecimen",
-            "restrict_rules": False, 
+            "restrict_rules": False,
             "manifest_record_type": "file_and_entities",
             "asset_view": "syn51514501",
             "dataset_id": "syn51514523",
-            "table_manipulation": 'replace',
-            "use_schema_label": True
+            "table_manipulation": "replace",
+            "data_model_labels": "class_label",
+            "table_column_names": "class_label",
+            "annotation_keys": "class_label",
         }
 
         # test uploading a csv file
-        response_csv = client.post('http://localhost:3001/v1/model/submit', query_string=params, data={"file_name": (open(test_manifest_submit, 'rb'), "test.csv")}, headers=request_headers)
+        response_csv = client.post(
+            "http://localhost:3001/v1/model/submit",
+            query_string=params,
+            data={"file_name": (open(test_manifest_submit, "rb"), "test.csv")},
+            headers=request_headers,
+        )
         assert response_csv.status_code == 200
 
     @pytest.mark.synapse_credentials_needed
     @pytest.mark.submission
-    def test_submit_manifest_table_and_file_upsert(self, client, request_headers, data_model_jsonld, test_upsert_manifest_csv, ):
+    def test_submit_manifest_table_and_file_upsert(
+        self,
+        client,
+        request_headers,
+        data_model_jsonld,
+        test_upsert_manifest_csv,
+    ):
         params = {
             "schema_url": data_model_jsonld,
             "data_type": "MockRDB",
-            "restrict_rules": False, 
+            "restrict_rules": False,
             "manifest_record_type": "table_and_file",
             "asset_view": "syn51514557",
             "dataset_id": "syn51514551",
-            "table_manipulation": 'upsert',
-            "use_schema_label": False # have to set use_schema_label to false to ensure upsert feature works
+            "table_manipulation": "upsert",
+            "data_model_labels": "class_label",
+            "table_column_names": "display_name",  # have to set table_column_names to display_name to ensure upsert feature works
         }
 
         # test uploading a csv file
-        response_csv = client.post('http://localhost:3001/v1/model/submit', query_string=params, data={"file_name": (open(test_upsert_manifest_csv, 'rb'), "test.csv")}, headers=request_headers)            
-        assert response_csv.status_code == 200     
+        response_csv = client.post(
+            "http://localhost:3001/v1/model/submit",
+            query_string=params,
+            data={"file_name": (open(test_upsert_manifest_csv, "rb"), "test.csv")},
+            headers=request_headers,
+        )
+        assert response_csv.status_code == 200
+
 
 @pytest.mark.schematic_api
 class TestSchemaVisualization:
     def test_visualize_attributes(self, client, data_model_jsonld):
-        params = {
-            "schema_url": data_model_jsonld
-        }
+        params = {"schema_url": data_model_jsonld}
 
-        response = client.get("http://localhost:3001/v1/visualize/attributes", query_string = params)
+        response = client.get(
+            "http://localhost:3001/v1/visualize/attributes", query_string=params
+        )
 
         assert response.status_code == 200
 
     @pytest.mark.parametrize("figure_type", ["component", "dependency"])
-    def test_visualize_tangled_tree_layers(self, client, figure_type, data_model_jsonld):
+    def test_visualize_tangled_tree_layers(
+        self, client, figure_type, data_model_jsonld
+    ):
         # TODO: Determine a 2nd data model to use for this test, test both models sequentially, add checks for content of response
-        params = {
-            "schema_url": data_model_jsonld,
-            "figure_type": figure_type
-        }
+        params = {"schema_url": data_model_jsonld, "figure_type": figure_type}
 
-        response = client.get("http://localhost:3001/v1/visualize/tangled_tree/layers", query_string = params)
+        response = client.get(
+            "http://localhost:3001/v1/visualize/tangled_tree/layers",
+            query_string=params,
+        )
 
         assert response.status_code == 200
 
-    @pytest.mark.parametrize("component, response_text", [("Patient", "Component,Component,TBD,True,,,,Patient"), ("BulkRNA-seqAssay", "Component,Component,TBD,True,,,,BulkRNA-seqAssay")])
-    def test_visualize_component(self, client, data_model_jsonld,component, response_text):
+    @pytest.mark.parametrize(
+        "component, response_text",
+        [
+            ("Patient", "Component,Component,TBD,True,,,,Patient"),
+            ("BulkRNA-seqAssay", "Component,Component,TBD,True,,,,BulkRNA-seqAssay"),
+        ],
+    )
+    def test_visualize_component(
+        self, client, data_model_jsonld, component, response_text
+    ):
         params = {
             "schema_url": data_model_jsonld,
             "component": component,
-            "include_index": False
+            "include_index": False,
+            "data_model_labels": "class_label",
         }
 
-        response = client.get("http://localhost:3001/v1/visualize/component", query_string = params)
+        response = client.get(
+            "http://localhost:3001/v1/visualize/component", query_string=params
+        )
 
         assert response.status_code == 200
-        assert "Attribute,Label,Description,Required,Cond_Req,Valid Values,Conditional Requirements,Component" in response.text
+        assert (
+            "Attribute,Label,Description,Required,Cond_Req,Valid Values,Conditional Requirements,Component"
+            in response.text
+        )
         assert response_text in response.text
 
+
 @pytest.mark.schematic_api
 @pytest.mark.rule_benchmark
-class TestValidationBenchmark():
-    @pytest.mark.parametrize('MockComponent_attribute', get_MockComponent_attribute())
-    def test_validation_performance(self, helpers, benchmark_data_model_jsonld, client, test_invalid_manifest, MockComponent_attribute ):
+class TestValidationBenchmark:
+    @pytest.mark.parametrize("MockComponent_attribute", get_MockComponent_attribute())
+    def test_validation_performance(
+        self,
+        helpers,
+        benchmark_data_model_jsonld,
+        client,
+        test_invalid_manifest,
+        MockComponent_attribute,
+    ):
         """
         Test to benchamrk performance of validation rules on large manifests
         Test loads the invalid_test_manifest.csv and isolates one attribute at a time
@@ -940,58 +1267,58 @@ def test_validation_performance(self, helpers, benchmark_data_model_jsonld, clie
         # Number of rows to target for large manfiest
         target_rows = 1000
         # URL of validtion endpoint
-        endpoint_url = 'http://localhost:3001/v1/model/validate'
+        endpoint_url = "http://localhost:3001/v1/model/validate"
 
         # Set paramters for endpoint
-        params = { 
+        params = {
             "schema_url": benchmark_data_model_jsonld,
             "data_type": "MockComponent",
-
-        }
-        headers = {
-        'Content-Type': "multipart/form-data",
-        'Accept': "application/json"
         }
+        headers = {"Content-Type": "multipart/form-data", "Accept": "application/json"}
 
         # Enforce error rate when possible
-        if MockComponent_attribute == 'Check Ages':
-            test_invalid_manifest.loc[0,MockComponent_attribute]  = '6550'
-        elif MockComponent_attribute == 'Check Date':
-            test_invalid_manifest.loc[0,MockComponent_attribute]   = 'October 21 2022'
-            test_invalid_manifest.loc[2,MockComponent_attribute]   = 'October 21 2022'
-        elif MockComponent_attribute == 'Check Unique':
-            test_invalid_manifest.loc[0,MockComponent_attribute]   = 'str2'
-
+        if MockComponent_attribute == "Check Ages":
+            test_invalid_manifest.loc[0, MockComponent_attribute] = "6550"
+        elif MockComponent_attribute == "Check Date":
+            test_invalid_manifest.loc[0, MockComponent_attribute] = "October 21 2022"
+            test_invalid_manifest.loc[2, MockComponent_attribute] = "October 21 2022"
+        elif MockComponent_attribute == "Check Unique":
+            test_invalid_manifest.loc[0, MockComponent_attribute] = "str2"
 
         # Isolate single attribute of interest, keep `Component` column
-        single_attribute_manfiest = test_invalid_manifest[['Component', MockComponent_attribute]]
+        single_attribute_manfiest = test_invalid_manifest[
+            ["Component", MockComponent_attribute]
+        ]
 
         # Extend to ~1000 rows in size to for performance test
-        multi_factor = ceil(target_rows/single_attribute_manfiest.shape[0])
-        large_manfiest = pd.concat([single_attribute_manfiest]*multi_factor, ignore_index = True)
+        multi_factor = ceil(target_rows / single_attribute_manfiest.shape[0])
+        large_manfiest = pd.concat(
+            [single_attribute_manfiest] * multi_factor, ignore_index=True
+        )
 
         try:
             # Convert manfiest to csv for api endpoint
-            large_manifest_path = helpers.get_data_path('mock_manifests/large_manifest_test.csv')
+            large_manifest_path = helpers.get_data_path(
+                "mock_manifests/large_manifest_test.csv"
+            )
             large_manfiest.to_csv(large_manifest_path, index=False)
 
             # Run and time endpoint
             t_start = perf_counter()
-            response = client.post(endpoint_url, query_string=params, data={"file_name": (open(large_manifest_path, 'rb'), "large_test.csv")}, headers=headers)
+            response = client.post(
+                endpoint_url,
+                query_string=params,
+                data={"file_name": (open(large_manifest_path, "rb"), "large_test.csv")},
+                headers=headers,
+            )
             response_time = perf_counter() - t_start
         finally:
             # Remove temp manfiest
             os.remove(large_manifest_path)
-        
+
         # Log and check time and ensure successful response
-        logger.warning(f"validation endpiont response time {round(response_time,2)} seconds.")
+        logger.warning(
+            f"validation endpiont response time {round(response_time,2)} seconds."
+        )
         assert response.status_code == 200
-        assert response_time < 5.00  
-
-
-        
-        
-
-
-
-
+        assert response_time < 5.00
diff --git a/tests/test_cli.py b/tests/test_cli.py
index 5498a5900..4631e9a9c 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -9,43 +9,50 @@
 from schematic.manifest.commands import manifest
 from schematic.configuration.configuration import Configuration
 
+
 @pytest.fixture
 def runner() -> CliRunner:
     """Fixture for invoking command-line interfaces."""
 
     return CliRunner()
 
+
 @pytest.fixture
 def data_model_jsonld(helpers):
-    data_model_jsonld =helpers.get_data_path("example.model.jsonld")
+    data_model_jsonld = helpers.get_data_path("example.model.jsonld")
     yield data_model_jsonld
 
 
 class TestSchemaCli:
     def assert_expected_file(self, result, output_path):
-        extension=os.path.splitext(output_path)[-1].lower()
+        extension = os.path.splitext(output_path)[-1].lower()
 
-        if extension==".xlsx":
-            expected_substr = f"Find the manifest template using this Excel file path: {output_path}" 
-        else: 
-            expected_substr = f"Find the manifest template using this CSV file path: {output_path}" 
+        if extension == ".xlsx":
+            expected_substr = (
+                f"Find the manifest template using this Excel file path: {output_path}"
+            )
+        else:
+            expected_substr = (
+                f"Find the manifest template using this CSV file path: {output_path}"
+            )
 
         assert expected_substr in result.output
-        
+
         # clean up
-        try: 
+        try:
             os.remove(output_path)
-        except: 
+        except:
             pass
 
     def test_schema_convert_cli(self, runner, helpers):
-
         data_model_csv_path = helpers.get_data_path("example.model.csv")
 
         output_path = helpers.get_data_path("example.model.jsonld")
 
+        label_type = 'class_label'
+
         result = runner.invoke(
-            schema, ["convert", data_model_csv_path, "--output_jsonld", output_path]
+            schema, ["convert", data_model_csv_path, "--output_jsonld", output_path, "--data_model_labels", label_type]
         )
 
         assert result.exit_code == 0
@@ -59,40 +66,76 @@ def test_schema_convert_cli(self, runner, helpers):
     # get manifest by default
     # by default this should download the manifest as a CSV file
     @pytest.mark.google_credentials_needed
-    def test_get_example_manifest_default(self, runner, helpers, config: Configuration, data_model_jsonld):
+    def test_get_example_manifest_default(
+        self, runner, helpers, config: Configuration, data_model_jsonld
+    ):
         output_path = helpers.get_data_path("example.Patient.manifest.csv")
         config.load_config("config_example.yml")
 
         result = runner.invoke(
-            manifest, ["--config", config.config_path, "get",  "--data_type", "Patient", "--path_to_data_model", data_model_jsonld]
+            manifest,
+            [
+                "--config",
+                config.config_path,
+                "get",
+                "--data_type",
+                "Patient",
+                "--path_to_data_model",
+                data_model_jsonld,
+            ],
         )
 
-
         assert result.exit_code == 0
         self.assert_expected_file(result, output_path)
 
     # get manifest as a csv
     # use google drive to export
     @pytest.mark.google_credentials_needed
-    def test_get_example_manifest_csv(self, runner, helpers, config: Configuration, data_model_jsonld):
+    def test_get_example_manifest_csv(
+        self, runner, helpers, config: Configuration, data_model_jsonld
+    ):
         output_path = helpers.get_data_path("test.csv")
         config.load_config("config_example.yml")
 
         result = runner.invoke(
-            manifest, ["--config", config.config_path, "get",  "--data_type", "Patient", "--path_to_data_model", data_model_jsonld, "--output_csv", output_path]
+            manifest,
+            [
+                "--config",
+                config.config_path,
+                "get",
+                "--data_type",
+                "Patient",
+                "--path_to_data_model",
+                data_model_jsonld,
+                "--output_csv",
+                output_path,
+            ],
         )
         assert result.exit_code == 0
         self.assert_expected_file(result, output_path)
 
     # get manifest as an excel spreadsheet
     @pytest.mark.google_credentials_needed
-    def test_get_example_manifest_excel(self, runner, helpers, config: Configuration, data_model_jsonld):
+    def test_get_example_manifest_excel(
+        self, runner, helpers, config: Configuration, data_model_jsonld
+    ):
         output_path = helpers.get_data_path("test.xlsx")
         config.load_config("config_example.yml")
 
         result = runner.invoke(
-            manifest, ["--config", config.config_path,  "get",  "--data_type", "Patient", "--path_to_data_model", data_model_jsonld, "--output_xlsx", output_path]
+            manifest,
+            [
+                "--config",
+                config.config_path,
+                "get",
+                "--data_type",
+                "Patient",
+                "--path_to_data_model",
+                data_model_jsonld,
+                "--output_xlsx",
+                output_path,
+            ],
         )
 
         assert result.exit_code == 0
-        self.assert_expected_file(result, output_path)
\ No newline at end of file
+        self.assert_expected_file(result, output_path)
diff --git a/tests/test_configuration.py b/tests/test_configuration.py
index b2fd59a7a..8845a9b48 100644
--- a/tests/test_configuration.py
+++ b/tests/test_configuration.py
@@ -10,7 +10,10 @@
     ModelConfig,
     GoogleSheetsConfig,
 )
-from schematic.configuration.configuration import Configuration, ConfigNonAllowedFieldError
+from schematic.configuration.configuration import (
+    Configuration,
+    ConfigNonAllowedFieldError,
+)
 
 
 class TestDataclasses:
@@ -198,6 +201,14 @@ def test_load_config3(self) -> None:
          is not valid
         """
         config = Configuration()
+        config.load_config("tests/data/test_configs/valid_config2.yml")
+
+    def test_load_config4(self) -> None:
+        """
+        Testing for Configuration.load_config where config file
+         has no asset store section
+        """
+        config = Configuration()
         with pytest.raises(ConfigNonAllowedFieldError):
             config.load_config("tests/data/test_configs/invalid_config1.yml")
         with pytest.raises(ConfigNonAllowedFieldError):
@@ -213,3 +224,13 @@ def test_set_synapse_master_fileview_id(self) -> None:
         assert config.synapse_master_fileview_id == "syn1"
         with pytest.raises(ValidationError):
             config.synapse_master_fileview_id = "syn"
+
+    def test_set_service_account_credentials_path(self) -> None:
+        """Testing for Configuration service_account_credentials_path setter"""
+        config = Configuration()
+        assert (
+            os.path.basename(config.service_account_credentials_path)
+            == "schematic_service_account_creds.json"
+        )
+        config.service_account_credentials_path = "test.json"
+        assert os.path.basename(config.service_account_credentials_path) == "test.json"
diff --git a/tests/test_manifest.py b/tests/test_manifest.py
index 417b86b47..cc00a2140 100644
--- a/tests/test_manifest.py
+++ b/tests/test_manifest.py
@@ -8,37 +8,37 @@
 from unittest.mock import MagicMock
 from schematic.manifest.generator import ManifestGenerator
 from schematic.schemas.data_model_parser import DataModelParser
-from schematic.schemas.data_model_graph import DataModelGraph,DataModelGraphExplorer
+from schematic.schemas.data_model_graph import DataModelGraph, DataModelGraphExplorer
 from schematic.schemas.data_model_json_schema import DataModelJSONSchema
 from schematic.configuration.configuration import Configuration
 from schematic.utils.google_api_utils import execute_google_api_requests
-
-
+from schematic_api.api import create_app
 
 logging.basicConfig(level=logging.DEBUG)
 logger = logging.getLogger(__name__)
 
 
-def generate_graph_data_model(helpers, path_to_data_model):
+def generate_graph_data_model(helpers, path_to_data_model, data_model_labels):
     """
     Simple helper function to generate a networkx graph data model from a CSV or JSONLD data model
     """
-    
+
     # Instantiate Parser
     data_model_parser = DataModelParser(path_to_data_model=path_to_data_model)
 
-    #Parse Model
+    # Parse Model
     parsed_data_model = data_model_parser.parse_model()
 
     # Convert parsed model to graph
     # Instantiate DataModelGraph
-    data_model_grapher = DataModelGraph(parsed_data_model)
+    data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
     # Generate graph
     graph_data_model = data_model_grapher.generate_data_model_graph()
 
     return graph_data_model
 
+
 @pytest.fixture(
     params=[
         (True, "Patient"),
@@ -53,17 +53,16 @@ def generate_graph_data_model(helpers, path_to_data_model):
         "skip_annotations-BulkRNAseqAssay",
     ],
 )
-
 def manifest_generator(helpers, request):
-
     # Rename request param for readability
     use_annotations, data_type = request.param
 
     path_to_data_model = helpers.get_data_path("example.model.jsonld")
 
     # Get graph data model
-    graph_data_model = generate_graph_data_model(helpers, path_to_data_model=path_to_data_model)
-
+    graph_data_model = generate_graph_data_model(
+        helpers, path_to_data_model=path_to_data_model, data_model_labels='class_label',
+    )
 
     manifest_generator = ManifestGenerator(
         path_to_data_model=path_to_data_model,
@@ -79,25 +78,29 @@ def manifest_generator(helpers, request):
         os.remove(helpers.get_data_path(f"example.{data_type}.schema.json"))
     except FileNotFoundError:
         pass
+
+
 @pytest.fixture
 def simple_manifest_generator(manifest_generator):
     generator, use_annotations, data_type = manifest_generator
     yield generator
 
+
 @pytest.fixture
 def simple_test_manifest_excel(helpers):
     yield helpers.get_data_path("mock_manifests/test_bulkRNAseq_manifest.xlsx")
 
+
 @pytest.fixture
 def mock_create_blank_google_sheet():
-    'Mock creating a new google sheet'
+    "Mock creating a new google sheet"
     er = Mock()
     er.return_value = "mock_spreadsheet_id"
     yield er
 
+
 @pytest.fixture(params=[True, False], ids=["sheet_url", "data_frame"])
 def manifest(dataset_id, manifest_generator, request):
-
     # Rename request param for readability
     sheet_url = request.param
 
@@ -108,21 +111,25 @@ def manifest(dataset_id, manifest_generator, request):
 
     yield manifest, use_annotations, data_type, sheet_url
 
+@pytest.fixture(scope="class")
+def app():
+    app = create_app()
+    yield app
 
 class TestManifestGenerator:
-
     def test_init(self, helpers):
         path_to_data_model = helpers.get_data_path("example.model.jsonld")
 
         # Get graph data model
-        graph_data_model = generate_graph_data_model(helpers, path_to_data_model=path_to_data_model)
-
+        graph_data_model = generate_graph_data_model(
+            helpers, path_to_data_model=path_to_data_model, data_model_labels='class_label',
+        )
 
         generator = ManifestGenerator(
             graph=graph_data_model,
             title="mock_title",
             path_to_data_model=path_to_data_model,
-            root = "Patient",
+            root="Patient",
         )
 
         assert type(generator.title) is str
@@ -130,10 +137,18 @@ def test_init(self, helpers):
         assert generator.root is "Patient"
         assert type(generator.dmge) is DataModelGraphExplorer
 
-    @pytest.mark.parametrize("data_type, exc, exc_message",
-                              [("MissingComponent", LookupError, "could not be found in the data model schema"),
-                               (None, ValueError, "No DataType has been provided.")],
-                               ids = ["DataType not found in Schema", "No DataType provided"])
+    @pytest.mark.parametrize(
+        "data_type, exc, exc_message",
+        [
+            (
+                "MissingComponent",
+                LookupError,
+                "could not be found in the data model schema",
+            ),
+            (None, ValueError, "No DataType has been provided."),
+        ],
+        ids=["DataType not found in Schema", "No DataType provided"],
+    )
     def test_missing_root_error(self, helpers, data_type, exc, exc_message):
         """
         Test for errors when either no DataType is provided or when a DataType is provided but not found in the schema
@@ -141,24 +156,24 @@ def test_missing_root_error(self, helpers, data_type, exc, exc_message):
         path_to_data_model = helpers.get_data_path("example.model.jsonld")
 
         # Get graph data model
-        graph_data_model = generate_graph_data_model(helpers, path_to_data_model=path_to_data_model)
-
+        graph_data_model = generate_graph_data_model(
+            helpers, path_to_data_model=path_to_data_model, data_model_labels='class_label',
+        )
 
         # A LookupError should be raised and include message when the component cannot be found
         with pytest.raises(exc) as e:
             generator = ManifestGenerator(
-            path_to_data_model=helpers.get_data_path("example.model.jsonld"),
-            graph=graph_data_model,
-            root=data_type,
-            use_annotations=False,
-            )        
+                path_to_data_model=helpers.get_data_path("example.model.jsonld"),
+                graph=graph_data_model,
+                root=data_type,
+                use_annotations=False,
+            )
 
         # Check message contents
         assert exc_message in str(e)
 
     @pytest.mark.google_credentials_needed
     def test_get_manifest_first_time(self, manifest):
-
         # See parameterization of the `manifest_generator` fixture
         output, use_annotations, data_type, sheet_url = manifest
 
@@ -207,16 +222,18 @@ def test_get_manifest_first_time(self, manifest):
         if use_annotations:
             assert output["File Format"].tolist() == ["txt", "csv", "fastq"]
 
-    @pytest.mark.parametrize("output_format", [None, "dataframe", "excel", "google_sheet"])
+    @pytest.mark.parametrize(
+        "output_format", [None, "dataframe", "excel", "google_sheet"]
+    )
     @pytest.mark.parametrize("sheet_url", [None, True, False])
     @pytest.mark.parametrize("dataset_id", [None, "syn27600056"])
     @pytest.mark.google_credentials_needed
     def test_get_manifest_excel(self, helpers, sheet_url, output_format, dataset_id):
-        '''
-        Purpose: the goal of this test is to make sure that output_format parameter and sheet_url parameter could function well; 
+        """
+        Purpose: the goal of this test is to make sure that output_format parameter and sheet_url parameter could function well;
         In addition, this test also makes sure that getting a manifest with an existing dataset_id is working
         "use_annotations" and "data_type" are hard-coded to fixed values to avoid long run time
-        '''
+        """
 
         data_type = "Patient"
 
@@ -224,47 +241,54 @@ def test_get_manifest_excel(self, helpers, sheet_url, output_format, dataset_id)
         path_to_data_model = helpers.get_data_path("example.model.jsonld")
 
         # Get graph data model
-        graph_data_model = generate_graph_data_model(helpers, path_to_data_model=path_to_data_model)
-
+        graph_data_model = generate_graph_data_model(
+            helpers, path_to_data_model=path_to_data_model, data_model_labels='class_label',
+        )
 
         generator = ManifestGenerator(
-        path_to_data_model=path_to_data_model,
-        graph=graph_data_model,
-        root=data_type,
-        use_annotations=False,
+            path_to_data_model=path_to_data_model,
+            graph=graph_data_model,
+            root=data_type,
+            use_annotations=False,
         )
 
-        manifest= generator.get_manifest(dataset_id=dataset_id, sheet_url = sheet_url, output_format = output_format)
+        manifest = generator.get_manifest(
+            dataset_id=dataset_id, sheet_url=sheet_url, output_format=output_format
+        )
 
         # if dataset id exists, it could return pandas dataframe, google spreadsheet, or an excel spreadsheet
-        if dataset_id: 
+        if dataset_id:
             if output_format == "dataframe":
                 assert isinstance(manifest, pd.DataFrame)
             elif output_format == "excel":
                 assert os.path.exists(manifest) == True
-            elif sheet_url: 
+            elif sheet_url:
                 assert type(manifest) is str
                 assert manifest.startswith("https://docs.google.com/spreadsheets/")
-            else: 
+            else:
                 assert isinstance(manifest, pd.DataFrame)
-        
+
         # if dataset id does not exist, it could return an empty google sheet or an empty excel spreadsheet exported from google
         else:
-            if output_format: 
+            if output_format:
                 if output_format == "excel":
                     assert os.path.exists(manifest) == True
-                else: 
+                else:
                     assert type(manifest) is str
                     assert manifest.startswith("https://docs.google.com/spreadsheets/")
-        
+
         # Clean-up
-        if type(manifest) is str and os.path.exists(manifest): 
+        if type(manifest) is str and os.path.exists(manifest):
             os.remove(manifest)
 
-    @pytest.mark.parametrize("dataset_id", [("syn27600056"), ("syn52397659")], ids=["Annotations present", "Annotations not present"])
+    @pytest.mark.parametrize(
+        "dataset_id",
+        [("syn27600056"), ("syn52397659")],
+        ids=["Annotations present", "Annotations not present"],
+    )
     def test_get_manifest_no_annos(self, helpers, dataset_id):
         """
-        Test to cover manifest generation under the case where use_annotations is True 
+        Test to cover manifest generation under the case where use_annotations is True
         but there are no annotations in the dataset
         """
 
@@ -275,19 +299,22 @@ def test_get_manifest_no_annos(self, helpers, dataset_id):
         path_to_data_model = helpers.get_data_path("example.model.jsonld")
 
         # Get graph data model
-        graph_data_model = generate_graph_data_model(helpers, path_to_data_model=path_to_data_model)
-
+        graph_data_model = generate_graph_data_model(
+            helpers, path_to_data_model=path_to_data_model, data_model_labels='class_label',
+        )
 
         # Instantiate object with use_annotations set to True
         generator = ManifestGenerator(
-        path_to_data_model=path_to_data_model,
-        graph=graph_data_model,
-        root=data_type,
-        use_annotations=True,
+            path_to_data_model=path_to_data_model,
+            graph=graph_data_model,
+            root=data_type,
+            use_annotations=True,
         )
 
         # Get manifest as a dataframe
-        manifest = generator.get_manifest(dataset_id = dataset_id, sheet_url = False, output_format = "dataframe")
+        manifest = generator.get_manifest(
+            dataset_id=dataset_id, sheet_url=False, output_format="dataframe"
+        )
 
         # Case where annotations are present in the dataset
         # manifest should have pulled in the annotations
@@ -299,208 +326,334 @@ def test_get_manifest_no_annos(self, helpers, dataset_id):
         elif dataset_id == "syn52397659":
             assert manifest["Patient ID"].size == 1
 
-
     # test all the functions used under get_manifest
     def test_create_empty_manifest_spreadsheet(self, simple_manifest_generator):
-        '''
+        """
         Create an empty manifest spreadsheet.
         Note: _create_empty_manifest_spreadsheet calls _gdrive_copy_file.
-        '''
+        """
         generator = simple_manifest_generator
-        title="Example"
+        title = "Example"
 
         # mock _gdrive_copy_file function
-        with patch('schematic.manifest.generator.ManifestGenerator._gdrive_copy_file', return_value="mock google sheet id"):
+        with patch(
+            "schematic.manifest.generator.ManifestGenerator._gdrive_copy_file",
+            return_value="mock google sheet id",
+        ):
             spreadsheet_id = generator._create_empty_manifest_spreadsheet(title=title)
             assert spreadsheet_id == "mock google sheet id"
 
-
     @pytest.mark.parametrize("schema_path_provided", [True, False])
-    def test_get_json_schema(self, simple_manifest_generator, helpers, schema_path_provided):
-        '''
+    def test_get_json_schema(
+        self, simple_manifest_generator, helpers, schema_path_provided
+    ):
+        """
         Open json schema as a dictionary
-        '''
+        """
         generator = simple_manifest_generator
 
         if schema_path_provided:
             json_schema_path = helpers.get_data_path("example.model.jsonld")
-            json_schema = generator._get_json_schema(json_schema_filepath=json_schema_path)
+            json_schema = generator._get_json_schema(
+                json_schema_filepath=json_schema_path
+            )
 
         else:
             mock_json_schema = Mock()
             mock_json_schema.return_value = "mock json ld"
-            with patch.object(DataModelJSONSchema, "get_json_validation_schema",mock_json_schema):
+            with patch.object(
+                DataModelJSONSchema, "get_json_validation_schema", mock_json_schema
+            ):
                 json_schema = generator._get_json_schema(json_schema_filepath=None)
                 assert json_schema == "mock json ld"
-            
+
             assert type(json_schema) == str
 
-    
     def test_gather_all_fields(self, simple_manifest_generator):
-        '''
+        """
         gather all fields is a wrapper around three functions: _get_required_metadata_fields, _gather_dependency_requirements
         and _get_additional_metadata
-        '''
+        """
         generator = simple_manifest_generator
 
-        with patch('schematic.manifest.generator.ManifestGenerator._get_required_metadata_fields') as MockClass:
+        with patch(
+            "schematic.manifest.generator.ManifestGenerator._get_required_metadata_fields"
+        ) as MockClass:
             MockClass.return_value = "mock required metadata fields"
-            with patch('schematic.manifest.generator.ManifestGenerator._gather_dependency_requirements') as MockRequirement:
+            with patch(
+                "schematic.manifest.generator.ManifestGenerator._gather_dependency_requirements"
+            ) as MockRequirement:
                 MockRequirement.return_value = "mock required metadata fields"
-                with patch('schematic.manifest.generator.ManifestGenerator._get_additional_metadata') as MockAdditionalData:
+                with patch(
+                    "schematic.manifest.generator.ManifestGenerator._get_additional_metadata"
+                ) as MockAdditionalData:
                     MockAdditionalData.return_value = "mock required metadata fields"
-                    required_metadata = generator._gather_all_fields("mock fields", "mock json schema")
+                    required_metadata = generator._gather_all_fields(
+                        "mock fields", "mock json schema"
+                    )
 
                     assert required_metadata == "mock required metadata fields"
-    
+
     # test: test and make sure root node as a metadata component get added in additional_metadata dictionary
     # test cases: 1) component as Patient; 2) component as BulkRNA-seqAssay
     # assume there is no existing additional metadata
-    @pytest.mark.parametrize("data_type,required_metadata_fields,expected", [("Patient", {"Component": []}, {'Component': ['Patient']}), ("BulkRNA-seqAssay", {"Filename": [], "Component":[]}, {'Component': ['BulkRNA-seqAssay']})])
-    def test_add_root_to_component_without_additional_metadata(self, helpers, data_type, required_metadata_fields, expected):
+    @pytest.mark.parametrize(
+        "data_type,required_metadata_fields,expected",
+        [
+            ("Patient", {"Component": []}, {"Component": ["Patient"]}),
+            (
+                "BulkRNA-seqAssay",
+                {"Filename": [], "Component": []},
+                {"Component": ["BulkRNA-seqAssay"]},
+            ),
+        ],
+    )
+    def test_add_root_to_component_without_additional_metadata(
+        self, helpers, data_type, required_metadata_fields, expected
+    ):
         # Get path to data model
         path_to_data_model = helpers.get_data_path("example.model.jsonld")
 
         # Get graph data model
-        graph_data_model = generate_graph_data_model(helpers, path_to_data_model=path_to_data_model)
+        graph_data_model = generate_graph_data_model(
+            helpers, path_to_data_model=path_to_data_model, data_model_labels='class_label',
+        )
 
         manifest_generator = ManifestGenerator(
-        path_to_data_model=path_to_data_model,
-        graph=graph_data_model,
-        root=data_type,
+            path_to_data_model=path_to_data_model,
+            graph=graph_data_model,
+            root=data_type,
         )
         manifest_generator._add_root_to_component(required_metadata_fields)
         assert manifest_generator.additional_metadata == expected
-    
+
     # test and make sure root node as a metadata component get added in additional_metadata dictionary
     # also make sure that length entry of column Component is the same as length of entry of column Filename
     # test cases: different length of Filename column in additional metadata
     # assume there is additional metadata
-    @pytest.mark.parametrize("additional_metadata", [{'author': ['test', '', ], 'Filename': ['test.txt', 'test2.txt'], 'Component': []}, {'Year of Birth': ['1988'], 'Filename': ['test.txt'], 'Component': []}])
-    def test_add_root_to_component_with_additional_metadata(self, helpers, additional_metadata):
+    @pytest.mark.parametrize(
+        "additional_metadata",
+        [
+            {
+                "author": [
+                    "test",
+                    "",
+                ],
+                "Filename": ["test.txt", "test2.txt"],
+                "Component": [],
+            },
+            {"Year of Birth": ["1988"], "Filename": ["test.txt"], "Component": []},
+        ],
+    )
+    def test_add_root_to_component_with_additional_metadata(
+        self, helpers, additional_metadata
+    ):
         # Get path to data model
         path_to_data_model = helpers.get_data_path("example.model.jsonld")
 
         # Get graph data model
-        graph_data_model = generate_graph_data_model(helpers, path_to_data_model=path_to_data_model)
+        graph_data_model = generate_graph_data_model(
+            helpers, path_to_data_model=path_to_data_model, data_model_labels='class_label',
+        )
 
         manifest_generator = ManifestGenerator(
-        path_to_data_model=path_to_data_model,
-        graph=graph_data_model,
-        root="BulkRNA-seqAssay"
+            path_to_data_model=path_to_data_model,
+            graph=graph_data_model,
+            root="BulkRNA-seqAssay",
         )
 
         # add mock additional metadata
         manifest_generator.additional_metadata = additional_metadata
 
-        mock_required_metadata_fields = {"Filename": [], "Component":[]}
+        mock_required_metadata_fields = {"Filename": [], "Component": []}
         manifest_generator._add_root_to_component(mock_required_metadata_fields)
-        assert len(manifest_generator.additional_metadata["Component"]) == len(additional_metadata["Filename"])
+        assert len(manifest_generator.additional_metadata["Component"]) == len(
+            additional_metadata["Filename"]
+        )
+
     # TO DO: add tests for: test_create_empty_gs
 
-                            
-    @pytest.mark.parametrize("wb_headers", [["column one", "column two", "column three"], ["column four", "column two"]])
+    @pytest.mark.parametrize(
+        "wb_headers",
+        [["column one", "column two", "column three"], ["column four", "column two"]],
+    )
     @pytest.mark.parametrize("manifest_columns", [["column four"]])
-    def test_get_missing_columns(self, simple_manifest_generator, wb_headers, manifest_columns):
+    def test_get_missing_columns(
+        self, simple_manifest_generator, wb_headers, manifest_columns
+    ):
         generator = simple_manifest_generator
 
-        manifest_test_df = pd.DataFrame(columns = manifest_columns)
+        manifest_test_df = pd.DataFrame(columns=manifest_columns)
         manifest_test_df_headers = list(manifest_test_df.columns)
-        out_of_schema_columns = generator._get_missing_columns(manifest_test_df_headers, wb_headers)
+        out_of_schema_columns = generator._get_missing_columns(
+            manifest_test_df_headers, wb_headers
+        )
 
         if "column four" not in wb_headers:
-            assert "column four" in out_of_schema_columns 
-        else: 
+            assert "column four" in out_of_schema_columns
+        else:
             assert "column four" not in out_of_schema_columns
 
     # Need to actually put in different dfs
-    @pytest.mark.parametrize("existing_manifest", [{"Patient ID": ["1738"], "Sex": ["Male"], "Year of Birth": ["1999"], "Diagnosis": [""], 'Component': [""], 'Cancer Type': [""], 'Family History': [""]},
-                                                   {"Patient ID": ["1738"], "Sex": ["Male"], "Year of Birth": ["1999"], "Diagnosis": [""], 'Component': [""], 'Cancer Type': [""], 'Family History': [""], 'Non Schema Column': [""]},
-                                                   {"Patient ID": ["1738"], "Sex": ["Male"]},
-                                                   None])
+    @pytest.mark.parametrize(
+        "existing_manifest",
+        [
+            {
+                "Patient ID": ["1738"],
+                "Sex": ["Male"],
+                "Year of Birth": ["1999"],
+                "Diagnosis": [""],
+                "Component": [""],
+                "Cancer Type": [""],
+                "Family History": [""],
+            },
+            {
+                "Patient ID": ["1738"],
+                "Sex": ["Male"],
+                "Year of Birth": ["1999"],
+                "Diagnosis": [""],
+                "Component": [""],
+                "Cancer Type": [""],
+                "Family History": [""],
+                "Non Schema Column": [""],
+            },
+            {"Patient ID": ["1738"], "Sex": ["Male"]},
+            None,
+        ],
+    )
     @pytest.mark.google_credentials_needed
     def test_update_dataframe_with_existing_df(self, helpers, existing_manifest):
-        '''
+        """
         Tests the following discrepancies with an existing schema:
             - schema has matching columns to existing_df
             - existing_df has columns the schema does not
             - schema has columns the existing_df does not.
             - No existing manifest
-        '''
+        """
         data_type = "Patient"
         sheet_url = True
 
         path_to_data_model = helpers.get_data_path("example.model.jsonld")
 
         # Get graph data model
-        graph_data_model = generate_graph_data_model(helpers, path_to_data_model=path_to_data_model)
-
+        graph_data_model = generate_graph_data_model(
+            helpers, path_to_data_model=path_to_data_model, data_model_labels='class_label',
+        )
 
         # Instantiate the Manifest Generator.
-        generator = ManifestGenerator(path_to_data_model=path_to_data_model,
-                                      graph=graph_data_model,
-                                      root=data_type,
-                                      use_annotations=False,
-                                      )
+        generator = ManifestGenerator(
+            path_to_data_model=path_to_data_model,
+            graph=graph_data_model,
+            root=data_type,
+            use_annotations=False,
+        )
 
         # Generate a google sheet url for a blank manifest.
-        empty_manifest_url= generator.get_manifest(sheet_url = sheet_url)
+        empty_manifest_url = generator.get_manifest(sheet_url=sheet_url)
 
         # Loading existing manifest
         existing_manifest_df = pd.DataFrame(existing_manifest)
 
         # Update the empty manifest with the existing manifest
-        updated_df = generator._update_dataframe_with_existing_df(empty_manifest_url=empty_manifest_url,
-                                                                  existing_df = existing_manifest_df,
-                                                                  )[0]
+        updated_df = generator._update_dataframe_with_existing_df(
+            empty_manifest_url=empty_manifest_url,
+            existing_df=existing_manifest_df,
+        )[0]
 
         # Check that update happened as intended.
         # If the existing manifest is emtpy, the columns will not change, no data will be added
         if existing_manifest_df.empty:
             assert updated_df.empty == True
-            assert list(updated_df.columns) == ['Patient ID', 'Sex', 'Year of Birth', 'Diagnosis', 'Component',
-                                             'Cancer Type', 'Family History']
+            assert list(updated_df.columns) == [
+                "Patient ID",
+                "Sex",
+                "Year of Birth",
+                "Diagnosis",
+                "Component",
+                "Cancer Type",
+                "Family History",
+            ]
         # If the existing manifest has only 2 of the schema columns, the columns should match the schema, data is added.
         elif len(existing_manifest_df.columns) == 2:
-            assert updated_df['Patient ID'][0] == '1738'
-            assert list(updated_df.columns) == ['Patient ID', 'Sex', 'Year of Birth', 'Diagnosis', 'Component',
-                                             'Cancer Type', 'Family History']
+            assert updated_df["Patient ID"][0] == "1738"
+            assert list(updated_df.columns) == [
+                "Patient ID",
+                "Sex",
+                "Year of Birth",
+                "Diagnosis",
+                "Component",
+                "Cancer Type",
+                "Family History",
+            ]
         # If the existing manifest has matching columns to the schema, the columns should remain the same, data is added.
         elif len(existing_manifest_df.columns) == 7:
-            assert updated_df['Patient ID'][0] == '1738'
-            assert list(updated_df.columns) == ['Patient ID', 'Sex', 'Year of Birth', 'Diagnosis', 'Component',
-                                             'Cancer Type', 'Family History']
+            assert updated_df["Patient ID"][0] == "1738"
+            assert list(updated_df.columns) == [
+                "Patient ID",
+                "Sex",
+                "Year of Birth",
+                "Diagnosis",
+                "Component",
+                "Cancer Type",
+                "Family History",
+            ]
         # If the existing manifest has an extra column that is not in the schema, the new column should be added, data is added.
         elif len(existing_manifest_df.columns) == 8:
-            assert updated_df['Patient ID'][0] == '1738'
-            assert list(updated_df.columns) == ['Patient ID', 'Sex', 'Year of Birth', 'Diagnosis', 'Component',
-                                             'Cancer Type', 'Family History','Non Schema Column']
-
-    @pytest.mark.parametrize("additional_df_dict", [{"Filename": ['a', 'b'], "Sample ID": ['a', 'b'], "File Format": ['a', 'b'], "Component": ['a', 'b'], "Genome Build": ['a', 'b'], "Genome FASTA": ['a', 'b'], "test_one_column": ['a', 'b'], "test_two_column": ['c', 'd']}, None])
-    def test_populate_existing_excel_spreadsheet(self, simple_manifest_generator, simple_test_manifest_excel, additional_df_dict):
-        generator =  simple_manifest_generator
-        if additional_df_dict: 
+            assert updated_df["Patient ID"][0] == "1738"
+            assert list(updated_df.columns) == [
+                "Patient ID",
+                "Sex",
+                "Year of Birth",
+                "Diagnosis",
+                "Component",
+                "Cancer Type",
+                "Family History",
+                "Non Schema Column",
+            ]
+
+    @pytest.mark.parametrize(
+        "additional_df_dict",
+        [
+            {
+                "Filename": ["a", "b"],
+                "Sample ID": ["a", "b"],
+                "File Format": ["a", "b"],
+                "Component": ["a", "b"],
+                "Genome Build": ["a", "b"],
+                "Genome FASTA": ["a", "b"],
+                "test_one_column": ["a", "b"],
+                "test_two_column": ["c", "d"],
+            },
+            None,
+        ],
+    )
+    def test_populate_existing_excel_spreadsheet(
+        self, simple_manifest_generator, simple_test_manifest_excel, additional_df_dict
+    ):
+        generator = simple_manifest_generator
+        if additional_df_dict:
             additional_test_df = pd.DataFrame(additional_df_dict)
-        else: 
+        else:
             additional_test_df = pd.DataFrame()
-        
+
         # copy the existing excel file
         dummy_output_path = "tests/data/mock_manifests/dummy_output.xlsx"
         shutil.copy(simple_test_manifest_excel, dummy_output_path)
 
         # added new content to an existing excel spreadsheet if applicable
-        generator.populate_existing_excel_spreadsheet(dummy_output_path, additional_test_df)
+        generator.populate_existing_excel_spreadsheet(
+            dummy_output_path, additional_test_df
+        )
 
         # read the new excel spreadsheet and see if columns have been added
         new_df = pd.read_excel(dummy_output_path)
 
         # if we are not adding any additional content
         if additional_test_df.empty:
-
-            # make sure that new content also gets added 
+            # make sure that new content also gets added
             assert len(new_df.columns) == 6
-        # we should be able to see new columns get added 
-        else: 
+        # we should be able to see new columns get added
+        else:
             # new columns get added
             assert not new_df[["test_one_column", "test_two_column"]].empty
             assert len(new_df.test_one_column.value_counts()) > 0
@@ -508,4 +661,34 @@ def test_populate_existing_excel_spreadsheet(self, simple_manifest_generator, si
 
         # remove file
         os.remove(dummy_output_path)
+    
+    @pytest.mark.parametrize("return_output", ["Mock excel file path", "Mock google sheet link"])
+    def test_create_single_manifest(self, simple_manifest_generator, helpers, return_output):
+        with patch("schematic.manifest.generator.ManifestGenerator.get_manifest", return_value=return_output):
+            json_ld_path = helpers.get_data_path("example.model.jsonld")
+            data_type = "Patient"
+
+            graph_data_model = generate_graph_data_model(helpers, path_to_data_model=json_ld_path, data_model_labels='class_label')
 
+            result = simple_manifest_generator.create_single_manifest(path_to_data_model=json_ld_path, graph_data_model=graph_data_model, data_type=data_type, output_format="google_sheet", use_annotations=False)
+            assert result == return_output
+    
+    @pytest.mark.parametrize("test_data_types", [["Patient", "Biospecimen"], ["all manifests"]])
+    def test_create_manifests_raise_errors(self, simple_manifest_generator, helpers, test_data_types):
+        with pytest.raises(ValueError) as exception_info: 
+            json_ld_path = helpers.get_data_path("example.model.jsonld")
+            data_types = test_data_types
+            dataset_ids=["syn123456"]
+
+            simple_manifest_generator.create_manifests(path_to_data_model=json_ld_path, data_types=data_types, dataset_ids=dataset_ids, output_format="google_sheet", use_annotations=False, data_model_labels='class_label')
+    
+    @pytest.mark.parametrize("test_data_types, dataset_ids, expected_result", [
+        (["Patient", "Biospecimen"], ["mock dataset id1", "mock dataset id2"], ["mock google sheet link", "mock google sheet link"]),
+        (["Patient"], ["mock dataset id1"], ["mock google sheet link"]),
+        ])
+    def test_create_manifests(self, simple_manifest_generator, helpers, test_data_types, dataset_ids, expected_result):
+        with patch("schematic.manifest.generator.ManifestGenerator.create_single_manifest", return_value="mock google sheet link"):
+            json_ld_path = helpers.get_data_path("example.model.jsonld")
+            all_results = simple_manifest_generator.create_manifests(path_to_data_model=json_ld_path, data_types=test_data_types, dataset_ids=dataset_ids, output_format="google_sheet", use_annotations=False, data_model_labels='class_label')
+            assert all_results == expected_result
+    
diff --git a/tests/test_metadata.py b/tests/test_metadata.py
index 2a88e6688..9bc5e5ae5 100644
--- a/tests/test_metadata.py
+++ b/tests/test_metadata.py
@@ -8,24 +8,34 @@
 logging.basicConfig(level=logging.DEBUG)
 logger = logging.getLogger(__name__)
 
-@pytest.fixture
-def metadata_model(helpers):
 
+def metadata_model(helpers, data_model_labels):
     metadata_model = MetadataModel(
         inputMModelLocation=helpers.get_data_path("example.model.jsonld"),
+        data_model_labels=data_model_labels,
         inputMModelLocationType="local",
     )
 
-    yield metadata_model
+    return metadata_model
 
 
 class TestMetadataModel:
     @pytest.mark.parametrize("as_graph", [True, False], ids=["as_graph", "as_list"])
-    def test_get_component_requirements(self, metadata_model, as_graph):
+    @pytest.mark.parametrize(
+        "data_model_labels",
+        ["display_label", "class_label"],
+        ids=["data_model_labels-display_label", "data_model_labels-class_label"],
+    )
+    def test_get_component_requirements(self, helpers, as_graph, data_model_labels):
+        # Instantiate MetadataModel
+        meta_data_model = metadata_model(helpers, data_model_labels)
 
-        source_component = "BulkRNA-seqAssay"
+        if data_model_labels == "display_label":
+            source_component = "BulkRNAseqAssay"
+        else:
+            source_component = "BulkRNA-seqAssay"
 
-        output = metadata_model.get_component_requirements(
+        output = meta_data_model.get_component_requirements(
             source_component, as_graph=as_graph
         )
 
@@ -33,32 +43,53 @@ def test_get_component_requirements(self, metadata_model, as_graph):
 
         if as_graph:
             assert ("Biospecimen", "Patient") in output
-            assert ("BulkRNA-seqAssay", "Biospecimen") in output
+            if data_model_labels == "display_label":
+                assert ("BulkRNAseqAssay", "Biospecimen") in output
+            else:
+                assert ("BulkRNA-seqAssay", "Biospecimen") in output
         else:
             assert "Biospecimen" in output
             assert "Patient" in output
-            assert "BulkRNA-seqAssay" in output
+            if data_model_labels == "display_label":
+                assert "BulkRNAseqAssay" in output
+            else:
+                assert "BulkRNA-seqAssay" in output
 
     @pytest.mark.parametrize("return_excel", [None, True, False])
+    @pytest.mark.parametrize(
+        "data_model_labels",
+        ["display_label", "class_label"],
+        ids=["data_model_labels-display_label", "data_model_labels-class_label"],
+    )
     @pytest.mark.google_credentials_needed
-    def test_populate_manifest(self, metadata_model, helpers, return_excel):
-        #Get path of manifest 
+    def test_populate_manifest(self, helpers, return_excel, data_model_labels):
+        # Instantiate MetadataModel
+        meta_data_model = metadata_model(helpers, data_model_labels)
+
+        # Get path of manifest
         manifestPath = helpers.get_data_path("mock_manifests/Valid_Test_Manifest.csv")
-    
-        #Call populateModelManifest class
-        populated_manifest_route= metadata_model.populateModelManifest(title="mock_title", manifestPath=manifestPath, rootNode="MockComponent", return_excel=return_excel)
+
+        # Call populateModelManifest class
+        populated_manifest_route = meta_data_model.populateModelManifest(
+            title="mock_title",
+            manifestPath=manifestPath,
+            rootNode="MockComponent",
+            return_excel=return_excel,
+        )
 
         if not return_excel:
             # return a url
             assert type(populated_manifest_route) is str
-            assert populated_manifest_route.startswith("https://docs.google.com/spreadsheets/")
-        else: 
+            assert populated_manifest_route.startswith(
+                "https://docs.google.com/spreadsheets/"
+            )
+        else:
             # return a valid file path
             assert os.path.exists(populated_manifest_route) == True
 
-        # clean up 
+        # clean up
         output_path = os.path.join(os.getcwd(), "mock_title.xlsx")
         try:
             os.remove(output_path)
-        except: 
+        except:
             pass
diff --git a/tests/test_schemas.py b/tests/test_schemas.py
index cccdb0208..54b93fd84 100644
--- a/tests/test_schemas.py
+++ b/tests/test_schemas.py
@@ -18,6 +18,7 @@
     get_attribute_display_name_from_label,
     convert_bool_to_str,
     parse_validation_rules,
+    DisplayLabelType
 )
 from schematic.utils.io_utils import load_json
 
@@ -61,26 +62,33 @@ def test_fake_func():
     "Bio Things": {"class": "BioThings", "property": "bioThings"},
     "bio things": {"class": "Biothings", "property": "biothings"},
 }
-NODE_DISPLAY_NAME_DICT = {"Patient": False, "Sex": True}
+NODE_DISPLAY_NAME_DICT = {"Patient": False, "Sex": True, "MockRDB_id": True}
 
 
-def get_data_model_parser(helpers, data_model_name: str = None):
+def get_data_model_parser(
+    helpers,
+    data_model_name: str = None,
+):
     # Get path to data model
     fullpath = helpers.get_data_path(path=data_model_name)
 
     # Instantiate DataModelParser
-    data_model_parser = DataModelParser(path_to_data_model=fullpath)
+    data_model_parser = DataModelParser(
+        path_to_data_model=fullpath,
+    )
     return data_model_parser
 
 
-def generate_graph_data_model(helpers, data_model_name: str) -> nx.MultiDiGraph:
+def generate_graph_data_model(
+    helpers, data_model_name: str, data_model_labels: DisplayLabelType = "class_label",
+) -> nx.MultiDiGraph:
     """
     Simple helper function to generate a networkx graph data model from a CSV or JSONLD data model
     """
-
     # Instantiate Parser
     data_model_parser = get_data_model_parser(
-        helpers=helpers, data_model_name=data_model_name
+        helpers=helpers,
+        data_model_name=data_model_name,
     )
 
     # Parse Model
@@ -88,7 +96,7 @@ def generate_graph_data_model(helpers, data_model_name: str) -> nx.MultiDiGraph:
 
     # Convert parsed model to graph
     # Instantiate DataModelGraph
-    data_model_grapher = DataModelGraph(parsed_data_model)
+    data_model_grapher = DataModelGraph(parsed_data_model, data_model_labels)
 
     # Generate graph
     graph_data_model = data_model_grapher.generate_data_model_graph()
@@ -96,10 +104,13 @@ def generate_graph_data_model(helpers, data_model_name: str) -> nx.MultiDiGraph:
     return graph_data_model
 
 
-def generate_data_model_nodes(helpers, data_model_name: str) -> DataModelNodes:
+def generate_data_model_nodes(
+    helpers, data_model_name: str, data_model_labels: DisplayLabelType = "class_label",
+) -> DataModelNodes:
     # Instantiate Parser
     data_model_parser = get_data_model_parser(
-        helpers=helpers, data_model_name=data_model_name
+        helpers=helpers,
+        data_model_name=data_model_name,
     )
     # Parse Model
     parsed_data_model = data_model_parser.parse_model()
@@ -270,7 +281,10 @@ def test_parse_csv_model(
 @pytest.mark.parametrize("data_model", ["example.model.jsonld"], ids=["jsonld"])
 class TestDataModelJsonLdParser:
     def test_gather_jsonld_attributes_relationships(
-        self, helpers, data_model: str, jsonld_parser: DataModelJSONLDParser
+        self,
+        helpers,
+        data_model: str,
+        jsonld_parser: DataModelJSONLDParser,
     ):
         """The output of the function is a attributes relationship dictionary, check that it is formatted properly."""
         path_to_data_model = helpers.get_data_path(path=data_model)
@@ -278,7 +292,7 @@ def test_gather_jsonld_attributes_relationships(
 
         # Get output of the function:
         attr_rel_dict = jsonld_parser.gather_jsonld_attributes_relationships(
-            model_jsonld=model_jsonld["@graph"]
+            model_jsonld=model_jsonld["@graph"],
         )
 
         # Test the attr_rel_dict is formatted as expected:
@@ -292,7 +306,10 @@ def test_gather_jsonld_attributes_relationships(
         assert "Attribute" in attr_rel_dict[attribute_key]["Relationships"]
 
     def test_parse_jsonld_model(
-        self, helpers, data_model: str, jsonld_parser: DataModelJSONLDParser
+        self,
+        helpers,
+        data_model: str,
+        jsonld_parser: DataModelJSONLDParser,
     ):
         """The output of the function is a attributes relationship dictionary, check that it is formatted properly."""
         path_to_data_model = helpers.get_data_path(path=data_model)
@@ -300,7 +317,7 @@ def test_parse_jsonld_model(
 
         # Get output of the function:
         attr_rel_dictionary = jsonld_parser.parse_jsonld_model(
-            path_to_data_model=path_to_data_model
+            path_to_data_model=path_to_data_model,
         )
 
         # Test the attr_rel_dictionary is formatted as expected:
@@ -385,25 +402,49 @@ class TestDataModelGraph:
         ["example.model.csv", "example.model.jsonld"],
         ids=["csv", "jsonld"],
     )
-    def test_generate_data_model_graph(self, helpers, data_model):
+    @pytest.mark.parametrize(
+        "data_model_labels",
+        ["display_label", "class_label"],
+        ids=["data_model_labels-display_label", "data_model_labels-class_label"],
+    )
+    def test_generate_data_model_graph(self, helpers, data_model, data_model_labels):
         """Check that data model graph is constructed properly, requires calling various classes.
         TODO: In another test, check conditional dependencies.
         """
-        graph = generate_graph_data_model(helpers=helpers, data_model_name=data_model)
+        graph = generate_graph_data_model(
+            helpers=helpers,
+            data_model_name=data_model,
+            data_model_labels=data_model_labels,
+        )
 
         # Check that some edges are present as expected:
         assert ("FamilyHistory", "Breast") in graph.edges("FamilyHistory")
-        assert ("BulkRNA-seqAssay", "Biospecimen") in graph.edges("BulkRNA-seqAssay")
-        assert ["Ab", "Cd", "Ef", "Gh"] == [
+
+        if data_model_labels == "display_label":
+            expected_valid_values = ["ab", "cd", "ef", "gh"]
+            mock_id_label = "MockRDB_id"
+            assert ("BulkRNAseqAssay", "Biospecimen") in graph.edges("BulkRNAseqAssay")
+
+        else:
+            expected_valid_values = ["Ab", "Cd", "Ef", "Gh"]
+            mock_id_label = "MockRDBId"
+            assert ("BulkRNA-seqAssay", "Biospecimen") in graph.edges(
+                "BulkRNA-seqAssay"
+            )
+        assert expected_valid_values == [
             k
             for k, v in graph["CheckList"].items()
             for vk, vv in v.items()
             if vk == "rangeValue"
         ]
 
+        assert mock_id_label in graph.nodes
+
         # Check that all relationships recorded between 'CheckList' and 'Ab' are present
-        assert "rangeValue" and "parentOf" in graph["CheckList"]["Ab"]
-        assert "requiresDependency" not in graph["CheckList"]["Ab"]
+        assert (
+            "rangeValue" and "parentOf" in graph["CheckList"][expected_valid_values[0]]
+        )
+        assert "requiresDependency" not in graph["CheckList"][expected_valid_values[0]]
 
         # Check nodes:
         assert "Patient" in graph.nodes
@@ -532,7 +573,8 @@ def test_gather_nodes(self, helpers, data_model):
 
         # Instantiate DataModelNodes
         data_model_nodes = generate_data_model_nodes(
-            helpers, data_model_name=data_model
+            helpers,
+            data_model_name=data_model,
         )
 
         attr_info = ("Patient", attr_rel_dictionary["Patient"])
@@ -544,14 +586,14 @@ def test_gather_nodes(self, helpers, data_model):
         # Make sure the nodes returned conform to expectations (values and order)
         ## The parsing records display names for relationships for CSV and labels for JSONLD, so the expectations are different between the two.
         expected_nodes = [
-                "Patient",
-                "Patient ID",
-                "Sex",
-                "Year of Birth",
-                "Diagnosis",
-                "Component",
-                "DataType",
-            ]
+            "Patient",
+            "Patient ID",
+            "Sex",
+            "Year of Birth",
+            "Diagnosis",
+            "Component",
+            "DataType",
+        ]
 
         assert nodes == expected_nodes
 
@@ -741,17 +783,19 @@ def test_run_rel_functions(self, helpers, data_model, rel_func, test_dn, test_bo
 
             assert len(vrs) == len(parsed_vrs)
             if DATA_MODEL_DICT[data_model] == "CSV":
-                assert vrs != parsed_vrs
+                for ind, rule in enumerate(vrs):
+                    if "::" in rule[0]:
+                        assert parsed_vrs[ind] == rule[0].split("::")
+                    elif '^^' in rule[0]:
+                        component_rule_sets = rule[0].split("^^")
+                        components = [cr.split(' ')[0].replace('#', '') for cr in component_rule_sets]
+                        assert components == [k for k in parsed_vrs[0].keys()]
+                    else:
+                        assert parsed_vrs[ind] == rule
             elif DATA_MODEL_DICT[data_model] == "JSONLD":
                 # JSONLDs already contain parsed validaiton rules so the raw vrs will match the parsed_vrs
                 assert vrs == parsed_vrs
 
-            # For all validation rules where there are multiple rules, make sure they have been split as expected.
-            for i, pvr in enumerate(parsed_vrs):
-                delim_count = vrs[i][0].count("::")
-                if delim_count:
-                    assert len(pvr) == delim_count + 1
-
         elif rel_func == get_label_from_display_name:
             # For a limited set check label is returned as expected.
             for entry_type, expected_value in TEST_DN_DICT[test_dn].items():
@@ -789,25 +833,38 @@ def test_run_rel_functions(self, helpers, data_model, rel_func, test_dn, test_bo
     @pytest.mark.parametrize(
         "node_display_name",
         list(NODE_DISPLAY_NAME_DICT.keys()),
-        ids=[str(v) for v in NODE_DISPLAY_NAME_DICT.values()],
+        ids=["Node_required-" + str(v) for v in NODE_DISPLAY_NAME_DICT.values()],
     )
-    def test_generate_node_dict(self, helpers, data_model, node_display_name):
+    @pytest.mark.parametrize(
+        "data_model_labels",
+        ["display_label", "class_label"],
+        ids=["data_model_labels-display_label", "data_model_labels-class_label"],
+    )
+    def test_generate_node_dict(
+        self, helpers, data_model, node_display_name, data_model_labels
+    ):
         # Instantiate Parser
         data_model_parser = get_data_model_parser(
-            helpers=helpers, data_model_name=data_model
+            helpers=helpers,
+            data_model_name=data_model,
         )
 
         # Parse Model
         attr_rel_dictionary = data_model_parser.parse_model()
 
+        # Change SourceManifest to sockComponent so we can check the data_model_labels is working as expected
+
         # Instantiate DataModelNodes
         data_model_nodes = generate_data_model_nodes(
-            helpers, data_model_name=data_model
+            helpers,
+            data_model_name=data_model,
+            data_model_labels=data_model_labels,
         )
 
         node_dict = data_model_nodes.generate_node_dict(
             node_display_name=node_display_name,
             attr_rel_dict=attr_rel_dictionary,
+            data_model_labels=data_model_labels,
         )
 
         # Check that the output is as expected for the required key.
@@ -818,6 +875,13 @@ def test_generate_node_dict(self, helpers, data_model, node_display_name):
             if not node_dict["required"] == False:
                 assert DATA_MODEL_DICT[data_model] == "JSONLD"
 
+        # Check that the display name matches the label
+        if data_model_labels == "display_label":
+            try:
+                assert node_display_name == node_dict["label"]
+            except:
+                breakpoint()
+
     def test_generate_node(self, helpers, data_model):
         # Test adding a dummy node
         node_dict = {"label": "test_label"}
@@ -894,11 +958,15 @@ def test_skip_edge(self, helpers, DMR, data_model_edges):
         # We're attempting to add an edge for a node that is the only one in the graph,
         # so `generate_edge` should skip adding edges and return the same graph
         edge_list_2 = data_model_edges.generate_edge(
-            node, node_dict, {node: parsed_data_model[node]}, edge_relationships, edge_list,
+            node,
+            node_dict,
+            {node: parsed_data_model[node]},
+            edge_relationships,
+            edge_list,
         )
 
         for node_1, node_2, edge_dict in edge_list_2:
-            G.add_edge(node_1, node_2, key=edge_dict['key'], weight=edge_dict['weight'])
+            G.add_edge(node_1, node_2, key=edge_dict["key"], weight=edge_dict["weight"])
 
         # Assert that no edges were added and that the current graph edges are the same as before the call to `generate_edge`
         assert before_edges == G.edges
@@ -950,11 +1018,15 @@ def test_generate_edge(
 
         # Generate edges for whichever node we are testing
         edge_list_2 = data_model_edges.generate_edge(
-            node_to_add, all_node_dict, parsed_data_model, edge_relationships, edge_list,
+            node_to_add,
+            all_node_dict,
+            parsed_data_model,
+            edge_relationships,
+            edge_list,
         )
 
         for node_1, node_2, edge_dict in edge_list_2:
-            G.add_edge(node_1, node_2, key=edge_dict['key'], weight=edge_dict['weight'])
+            G.add_edge(node_1, node_2, key=edge_dict["key"], weight=edge_dict["weight"])
 
         # Assert that the current edges are different from the edges of the graph before
         assert G.edges > before_edges
@@ -1016,11 +1088,15 @@ def test_generate_weights(
 
         # Generate edges for whichever node we are testing
         edge_list_2 = data_model_edges.generate_edge(
-            node_to_add, all_node_dict, parsed_data_model, edge_relationships, edge_list,
+            node_to_add,
+            all_node_dict,
+            parsed_data_model,
+            edge_relationships,
+            edge_list,
         )
 
         for node_1, node_2, edge_dict in edge_list_2:
-            G.add_edge(node_1, node_2, key=edge_dict['key'], weight=edge_dict['weight'])
+            G.add_edge(node_1, node_2, key=edge_dict["key"], weight=edge_dict["weight"])
 
         # Assert that the current edges are different from the edges of the graph before
         assert G.edges > before_edges
@@ -1246,10 +1322,19 @@ def test_class_template(self, helpers):
         "template_type", ["property", "class"], ids=["property", "class"]
     )
     @pytest.mark.parametrize("node", ["", "Patient"], ids=["no node", "Patient"])
-    def test_fill_entry_template(self, helpers, data_model, template_type, node):
+    @pytest.mark.parametrize(
+        "data_model_labels",
+        ["display_label", "class_label"],
+        ids=["data_model_labels-display_label", "data_model_labels-class_label"],
+    )
+    def test_fill_entry_template(
+        self, helpers, data_model, template_type, node, data_model_labels
+    ):
         # Get Graph
         graph_data_model = generate_graph_data_model(
-            helpers, data_model_name=data_model
+            helpers,
+            data_model_name=data_model,
+            data_model_labels=data_model_labels,
         )
 
         # Instantiate DataModelJsonLD
@@ -1303,9 +1388,14 @@ def test_fill_entry_template(self, helpers, data_model, template_type, node):
                     "sms:requiresDependency",
                     "sms:validationRules",
                 ]
+
             assert (set(actual_keys) - set(expected_keys)) == (
                 set(expected_keys) - set(actual_keys)
             )
+            if data_model_labels == "display_label":
+                assert (
+                    object_template["rdfs:label"] == object_template["sms:displayName"]
+                )
 
     @pytest.mark.parametrize(
         "data_model", list(DATA_MODEL_DICT.keys()), ids=list(DATA_MODEL_DICT.values())
@@ -1437,7 +1527,8 @@ def test_generate_jsonld_object(self, helpers, data_model):
 
         # Get Graph
         graph_data_model = generate_graph_data_model(
-            helpers, data_model_name=data_model
+            helpers,
+            data_model_name=data_model,
         )
 
         # Instantiate DataModelJsonLD
diff --git a/tests/test_store.py b/tests/test_store.py
index ed8990579..ee24d9642 100644
--- a/tests/test_store.py
+++ b/tests/test_store.py
@@ -19,8 +19,10 @@
 
 from schematic.models.metadata import MetadataModel
 from schematic.store.base import BaseStorage
-from schematic.store.synapse import (DatasetFileView, 
-                                    ManifestDownload,)
+from schematic.store.synapse import (
+    DatasetFileView,
+    ManifestDownload,
+)
 
 logging.basicConfig(level=logging.DEBUG)
 logger = logging.getLogger(__name__)
@@ -30,11 +32,13 @@
 def test_download_manifest_id():
     yield "syn51203973"
 
+
 @pytest.fixture
 def mock_manifest_download(synapse_store, test_download_manifest_id):
     md = ManifestDownload(synapse_store.syn, test_download_manifest_id)
     yield md
 
+
 @pytest.fixture
 def dataset_fileview(dataset_id, synapse_store):
     dataset_fileview = DatasetFileView(dataset_id, synapse_store.syn)
@@ -53,33 +57,36 @@ def dataset_fileview_table_tidy(dataset_fileview, dataset_fileview_table):
     table = dataset_fileview.tidy_table()
     yield table
 
+
 @pytest.fixture
 def version(synapse_store, helpers):
-    
     yield helpers.get_python_version()
 
+
 @pytest.fixture
 def projectId(synapse_store, helpers):
     projectId = helpers.get_python_project(helpers)
     yield projectId
 
+
 @pytest.fixture
 def datasetId(synapse_store, projectId, helpers):
     dataset = Folder(
-        name = 'Table Test  Dataset ' + helpers.get_python_version(),
-        parent = projectId,
-        )
+        name="Table Test  Dataset " + helpers.get_python_version(),
+        parent=projectId,
+    )
 
     datasetId = synapse_store.syn.store(dataset).id
     sleep(5)
     yield datasetId
 
+
 def raise_final_error(retry_state):
     return retry_state.outcome.result()
 
+
 class TestBaseStorage:
     def test_init(self):
-
         with pytest.raises(NotImplementedError):
             BaseStorage()
 
@@ -110,47 +117,75 @@ def test_getFileAnnotations(self, synapse_store):
 
         assert expected_dict == actual_dict
 
-    @pytest.mark.parametrize('only_new_files',[True, False])
+    @pytest.mark.parametrize("only_new_files", [True, False])
     def test_get_file_entityIds(self, helpers, synapse_store, only_new_files):
-        #TODO: Automatically reset manifest at path specified below after each test 
+        # TODO: Automatically reset manifest at path specified below after each test
         # so that subsequent runs do not affect each other
         manifest_path = "mock_manifests/test_BulkRNAseq.csv"
-        dataset_files = synapse_store.getFilesInStorageDataset('syn39241199')
+        dataset_files = synapse_store.getFilesInStorageDataset("syn39241199")
 
         if only_new_files:
             # Prepare manifest is getting Ids for new files only
             manifest = helpers.get_data_frame(manifest_path)
-            entityIds = pd.DataFrame({'entityId': ['syn39242580', 'syn51900502']})
+            entityIds = pd.DataFrame({"entityId": ["syn39242580", "syn51900502"]})
 
             # If this line errors out then the changes on the manifest file need to be discarded
             manifest = manifest.join(entityIds)
-            
+
             # get entityIds for new files
-            files_and_Ids = synapse_store._get_file_entityIds(dataset_files=dataset_files, only_new_files=only_new_files, manifest=manifest)
+            files_and_Ids = synapse_store._get_file_entityIds(
+                dataset_files=dataset_files,
+                only_new_files=only_new_files,
+                manifest=manifest,
+            )
 
             # Assert that there are no new files
             for value in files_and_Ids.values():
                 assert value == []
-            
+
         else:
             # get entityIds for all files
-            files_and_Ids = synapse_store._get_file_entityIds(dataset_files=dataset_files, only_new_files=only_new_files)
+            files_and_Ids = synapse_store._get_file_entityIds(
+                dataset_files=dataset_files, only_new_files=only_new_files
+            )
 
             # assert that the correct number of files were found
-            assert len(files_and_Ids['entityId']) == 2
-
-    @pytest.mark.parametrize('manifest_path, test_annotations, datasetId, manifest_record_type',
-                             [  ("mock_manifests/annotations_test_manifest.csv", {'CheckInt': '7', 'CheckList': 'valid, list, values'}, 'syn34295552', 'file_and_entities'),
-                                ("mock_manifests/test_BulkRNAseq.csv", {'FileFormat': 'BAM', 'GenomeBuild': 'GRCh38'}, 'syn39241199', 'table_and_file')],
-                            ids = ['non file-based',
-                                    'file-based'])
-    def test_annotation_submission(self, synapse_store, helpers, manifest_path, test_annotations, datasetId, manifest_record_type, config: Configuration):
+            assert len(files_and_Ids["entityId"]) == 2
+
+    @pytest.mark.parametrize(
+        "manifest_path, test_annotations, datasetId, manifest_record_type",
+        [
+            (
+                "mock_manifests/annotations_test_manifest.csv",
+                {"CheckInt": "7", "CheckList": "valid, list, values"},
+                "syn34295552",
+                "file_and_entities",
+            ),
+            (
+                "mock_manifests/test_BulkRNAseq.csv",
+                {"FileFormat": "BAM", "GenomeBuild": "GRCh38"},
+                "syn39241199",
+                "table_and_file",
+            ),
+        ],
+        ids=["non file-based", "file-based"],
+    )
+    def test_annotation_submission(
+        self,
+        synapse_store,
+        helpers,
+        manifest_path,
+        test_annotations,
+        datasetId,
+        manifest_record_type,
+        config: Configuration,
+    ):
         # Upload dataset annotations
 
         # Instantiate DataModelParser
-        data_model_parser = DataModelParser(path_to_data_model = config.model_location)
-        
-        #Parse Model
+        data_model_parser = DataModelParser(path_to_data_model=config.model_location)
+
+        # Parse Model
         parsed_data_model = data_model_parser.parse_model()
 
         # Instantiate DataModelGraph
@@ -163,13 +198,12 @@ def test_annotation_submission(self, synapse_store, helpers, manifest_path, test
         dmge = DataModelGraphExplorer(graph_data_model)
 
         manifest_id = synapse_store.associateMetadataWithFiles(
-            dmge = dmge,
-            metadataManifestPath = helpers.get_data_path(manifest_path),
-            datasetId = datasetId,
-            manifest_record_type = manifest_record_type,
-            useSchemaLabel = True,
-            hideBlanks = True,
-            restrict_manifest = False,
+            dmge=dmge,
+            metadataManifestPath=helpers.get_data_path(manifest_path),
+            datasetId=datasetId,
+            manifest_record_type=manifest_record_type,
+            hideBlanks=True,
+            restrict_manifest=False,
         )
 
         # Retrive annotations
@@ -181,9 +215,9 @@ def test_annotation_submission(self, synapse_store, helpers, manifest_path, test
             assert key in annotations.keys()
             assert annotations[key] == test_annotations[key]
 
-        if manifest_path.endswith('annotations_test_manifest.csv'):
-            assert 'CheckRecommended' not in annotations.keys()
-        elif manifest_path.endswith('test_BulkRNAseq.csv'):
+        if manifest_path.endswith("annotations_test_manifest.csv"):
+            assert "CheckRecommended" not in annotations.keys()
+        elif manifest_path.endswith("test_BulkRNAseq.csv"):
             entity = synapse_store.syn.get(entity_id)
             assert type(entity) == File
 
@@ -228,7 +262,6 @@ def test_getDatasetAnnotations(self, dataset_id, synapse_store, force_batch):
         pd.testing.assert_frame_equal(expected_df, actual_df, check_like=True)
 
     def test_getDatasetProject(self, dataset_id, synapse_store):
-
         assert synapse_store.getDatasetProject(dataset_id) == "syn23643250"
         assert synapse_store.getDatasetProject("syn23643250") == "syn23643250"
 
@@ -237,23 +270,37 @@ def test_getDatasetProject(self, dataset_id, synapse_store):
 
         with pytest.raises(PermissionError):
             synapse_store.getDatasetProject("syn12345678")
-    
-    @pytest.mark.parametrize("full_path,expected", [(True, [('syn126', 'parent_folder/test_file'), ('syn125', 'parent_folder/test_folder/test_file_2')]),(False, [('syn126', 'test_file'), ('syn125', 'test_file_2')])])
+
+    @pytest.mark.parametrize(
+        "full_path,expected",
+        [
+            (
+                True,
+                [
+                    ("syn126", "parent_folder/test_file"),
+                    ("syn125", "parent_folder/test_folder/test_file_2"),
+                ],
+            ),
+            (False, [("syn126", "test_file"), ("syn125", "test_file_2")]),
+        ],
+    )
     def test_getFilesInStorageDataset(self, synapse_store, full_path, expected):
         mock_return = [
-        (
-            ("parent_folder", "syn123"),
-            [("test_folder", "syn124")],
-            [("test_file", "syn126")],
-        ),
-        (
-            (os.path.join("parent_folder", "test_folder"), "syn124"),
-            [],
-            [("test_file_2", "syn125")],
-        ),
+            (
+                ("parent_folder", "syn123"),
+                [("test_folder", "syn124")],
+                [("test_file", "syn126")],
+            ),
+            (
+                (os.path.join("parent_folder", "test_folder"), "syn124"),
+                [],
+                [("test_file_2", "syn125")],
+            ),
         ]
-        with patch('synapseutils.walk_functions._helpWalk', return_value=mock_return):
-            file_list = synapse_store.getFilesInStorageDataset(datasetId="syn_mock", fileNames=None, fullpath=full_path)
+        with patch("synapseutils.walk_functions._helpWalk", return_value=mock_return):
+            file_list = synapse_store.getFilesInStorageDataset(
+                datasetId="syn_mock", fileNames=None, fullpath=full_path
+            )
             assert file_list == expected
 
     @pytest.mark.parametrize("downloadFile", [True, False])
@@ -261,62 +308,144 @@ def test_getDatasetManifest(self, synapse_store, downloadFile):
         # get a test manifest
         manifest_data = synapse_store.getDatasetManifest("syn51204502", downloadFile)
 
-        #make sure the file gets downloaded
+        # make sure the file gets downloaded
         if downloadFile:
-            assert manifest_data['name'] == "synapse_storage_manifest_censored.csv"
-            assert os.path.exists(manifest_data['path'])
+            assert manifest_data["name"] == "synapse_storage_manifest_censored.csv"
+            assert os.path.exists(manifest_data["path"])
             # clean up
-            os.remove(manifest_data['path'])
-        else: 
+            os.remove(manifest_data["path"])
+        else:
             # return manifest id
             assert manifest_data == "syn51204513"
 
-    @pytest.mark.parametrize("existing_manifest_df", [pd.DataFrame(), pd.DataFrame({"Filename": ["existing_mock_file_path"], "entityId": ["existing_mock_entity_id"]})])
+    @pytest.mark.parametrize(
+        "existing_manifest_df",
+        [
+            pd.DataFrame(),
+            pd.DataFrame(
+                {
+                    "Filename": ["existing_mock_file_path"],
+                    "entityId": ["existing_mock_entity_id"],
+                }
+            ),
+        ],
+    )
     def test_fill_in_entity_id_filename(self, synapse_store, existing_manifest_df):
-        with patch("schematic.store.synapse.SynapseStorage.getFilesInStorageDataset", return_value=["syn123", "syn124", "syn125"]) as mock_get_file_storage, \
-        patch("schematic.store.synapse.SynapseStorage._get_file_entityIds", return_value={"Filename": ["mock_file_path"], "entityId": ["mock_entity_id"]}) as mock_get_file_entity_id:
-            dataset_files, new_manifest = synapse_store.fill_in_entity_id_filename(datasetId="test_syn_id", manifest=existing_manifest_df)
+        with patch(
+            "schematic.store.synapse.SynapseStorage.getFilesInStorageDataset",
+            return_value=["syn123", "syn124", "syn125"],
+        ) as mock_get_file_storage, patch(
+            "schematic.store.synapse.SynapseStorage._get_file_entityIds",
+            return_value={
+                "Filename": ["mock_file_path"],
+                "entityId": ["mock_entity_id"],
+            },
+        ) as mock_get_file_entity_id:
+            dataset_files, new_manifest = synapse_store.fill_in_entity_id_filename(
+                datasetId="test_syn_id", manifest=existing_manifest_df
+            )
             if not existing_manifest_df.empty:
-                expected_df=pd.DataFrame({"Filename": ["existing_mock_file_path", "mock_file_path"], "entityId": ["existing_mock_entity_id", "mock_entity_id"]})
+                expected_df = pd.DataFrame(
+                    {
+                        "Filename": ["existing_mock_file_path", "mock_file_path"],
+                        "entityId": ["existing_mock_entity_id", "mock_entity_id"],
+                    }
+                )
             else:
-                expected_df=pd.DataFrame({"Filename": ["mock_file_path"], "entityId": ["mock_entity_id"]})
+                expected_df = pd.DataFrame(
+                    {"Filename": ["mock_file_path"], "entityId": ["mock_entity_id"]}
+                )
             assert_frame_equal(new_manifest, expected_df)
             assert dataset_files == ["syn123", "syn124", "syn125"]
 
     # Test case: make sure that Filename and entityId column get filled and component column has the same length as filename column
     def test_add_entity_id_and_filename_with_component_col(self, synapse_store):
-        with patch("schematic.store.synapse.SynapseStorage._get_files_metadata_from_dataset", return_value={"Filename": ["test_file1", "test_file2"], "entityId": ["syn123", "syn124"]}):
-            mock_manifest = pd.DataFrame.from_dict({"Filename": [""], "Component": ["MockComponent"], "Sample ID": [""]}).reset_index(drop=True)
-            manifest_to_return = synapse_store.add_entity_id_and_filename(datasetId="mock_syn_id", manifest=mock_manifest)
-            expected_df = pd.DataFrame.from_dict({"Filename": ["test_file1", "test_file2"], "Component": ["MockComponent", "MockComponent"], "Sample ID": ["", ""], "entityId": ["syn123", "syn124"]})
+        with patch(
+            "schematic.store.synapse.SynapseStorage._get_files_metadata_from_dataset",
+            return_value={
+                "Filename": ["test_file1", "test_file2"],
+                "entityId": ["syn123", "syn124"],
+            },
+        ):
+            mock_manifest = pd.DataFrame.from_dict(
+                {"Filename": [""], "Component": ["MockComponent"], "Sample ID": [""]}
+            ).reset_index(drop=True)
+            manifest_to_return = synapse_store.add_entity_id_and_filename(
+                datasetId="mock_syn_id", manifest=mock_manifest
+            )
+            expected_df = pd.DataFrame.from_dict(
+                {
+                    "Filename": ["test_file1", "test_file2"],
+                    "Component": ["MockComponent", "MockComponent"],
+                    "Sample ID": ["", ""],
+                    "entityId": ["syn123", "syn124"],
+                }
+            )
             assert_frame_equal(manifest_to_return, expected_df)
 
-    # Test case: make sure that Filename and entityId column get filled when component column does not exist 
+    # Test case: make sure that Filename and entityId column get filled when component column does not exist
     def test_add_entity_id_and_filename_without_component_col(self, synapse_store):
-        with patch("schematic.store.synapse.SynapseStorage._get_files_metadata_from_dataset", return_value={"Filename": ["test_file1", "test_file2"], "entityId": ["syn123", "syn124"]}):
-            mock_manifest = pd.DataFrame.from_dict({"Filename": [""], "Sample ID": [""]}).reset_index(drop=True)
-            manifest_to_return = synapse_store.add_entity_id_and_filename(datasetId="mock_syn_id", manifest=mock_manifest)
-            expected_df = pd.DataFrame.from_dict({"Filename": ["test_file1", "test_file2"], "Sample ID": ["", ""], "entityId": ["syn123", "syn124"]})
+        with patch(
+            "schematic.store.synapse.SynapseStorage._get_files_metadata_from_dataset",
+            return_value={
+                "Filename": ["test_file1", "test_file2"],
+                "entityId": ["syn123", "syn124"],
+            },
+        ):
+            mock_manifest = pd.DataFrame.from_dict(
+                {"Filename": [""], "Sample ID": [""]}
+            ).reset_index(drop=True)
+            manifest_to_return = synapse_store.add_entity_id_and_filename(
+                datasetId="mock_syn_id", manifest=mock_manifest
+            )
+            expected_df = pd.DataFrame.from_dict(
+                {
+                    "Filename": ["test_file1", "test_file2"],
+                    "Sample ID": ["", ""],
+                    "entityId": ["syn123", "syn124"],
+                }
+            )
             assert_frame_equal(manifest_to_return, expected_df)
 
     def test_get_files_metadata_from_dataset(self, synapse_store):
-        patch_get_children = [('syn123', 'parent_folder/test_A.txt'), ('syn456', 'parent_folder/test_B.txt')]
-        mock_file_entityId = {"Filename": ["parent_folder/test_A.txt", "parent_folder/test_B.txt"], "entityId": ["syn123", "syn456"]}
-        with patch("schematic.store.synapse.SynapseStorage.getFilesInStorageDataset", return_value=patch_get_children):
-            with patch("schematic.store.synapse.SynapseStorage._get_file_entityIds", return_value=mock_file_entityId):
-                dataset_file_names_id_dict = synapse_store._get_files_metadata_from_dataset("mock dataset id", only_new_files=True)
-                assert dataset_file_names_id_dict ==  {"Filename": ["parent_folder/test_A.txt", "parent_folder/test_B.txt"], "entityId": ["syn123", "syn456"]}
+        patch_get_children = [
+            ("syn123", "parent_folder/test_A.txt"),
+            ("syn456", "parent_folder/test_B.txt"),
+        ]
+        mock_file_entityId = {
+            "Filename": ["parent_folder/test_A.txt", "parent_folder/test_B.txt"],
+            "entityId": ["syn123", "syn456"],
+        }
+        with patch(
+            "schematic.store.synapse.SynapseStorage.getFilesInStorageDataset",
+            return_value=patch_get_children,
+        ):
+            with patch(
+                "schematic.store.synapse.SynapseStorage._get_file_entityIds",
+                return_value=mock_file_entityId,
+            ):
+                dataset_file_names_id_dict = (
+                    synapse_store._get_files_metadata_from_dataset(
+                        "mock dataset id", only_new_files=True
+                    )
+                )
+                assert dataset_file_names_id_dict == {
+                    "Filename": [
+                        "parent_folder/test_A.txt",
+                        "parent_folder/test_B.txt",
+                    ],
+                    "entityId": ["syn123", "syn456"],
+                }
+
 
 class TestDatasetFileView:
     def test_init(self, dataset_id, dataset_fileview, synapse_store):
-
         assert dataset_fileview.datasetId == dataset_id
         assert dataset_fileview.synapse is synapse_store.syn
         assert dataset_fileview.parentId == dataset_id
         assert isinstance(dataset_fileview.view_schema, EntityViewSchema)
 
     def test_enter_exit(self, dataset_id, synapse_store):
-
         # Within the 'with' statement, the file view should be available
         with DatasetFileView(dataset_id, synapse_store.syn) as fileview:
             assert isinstance(fileview.view_schema, EntityViewSchema)
@@ -326,7 +455,6 @@ def test_enter_exit(self, dataset_id, synapse_store):
         assert fileview.view_schema is None
 
     def test_query(self, dataset_fileview_table):
-
         table = dataset_fileview_table
 
         # The content is tested in test_getDatasetAnnotations()
@@ -351,7 +479,6 @@ def test_query(self, dataset_fileview_table):
         assert math.isclose(year_value, 1980.0)
 
     def test_tidy_table(self, dataset_fileview_table_tidy):
-
         table = dataset_fileview_table_tidy
 
         # The content is tested in test_getDatasetAnnotations()
@@ -376,31 +503,55 @@ def test_tidy_table(self, dataset_fileview_table_tidy):
         assert isinstance(year_value, str)
         assert year_value == "1980"
 
+
 @pytest.mark.table_operations
 class TestTableOperations:
-
-    def test_createTable(self, helpers, synapse_store, config: Configuration, projectId, datasetId):
+    @pytest.mark.parametrize(
+        "table_column_names",
+        ["display_name", "display_label", "class_label"],
+        ids=["tcn_display_name", "tcn_display_label", "tcn_class_label"],
+    )
+    @pytest.mark.parametrize(
+        "annotation_keys",
+        ["display_label", "class_label"],
+        ids=["aks_display_label", "aks_class_label"],
+    )
+    def test_createTable(
+        self,
+        helpers,
+        synapse_store,
+        config: Configuration,
+        projectId,
+        datasetId,
+        table_column_names,
+        annotation_keys,
+    ):
         table_manipulation = None
 
         # Check if FollowUp table exists if so delete
-        existing_tables = synapse_store.get_table_info(projectId = projectId)
+        existing_tables = synapse_store.get_table_info(projectId=projectId)
+
+        table_name = "followup_synapse_storage_manifest_table"
 
-        table_name='followup_synapse_storage_manifest_table'
-        
         if table_name in existing_tables.keys():
             synapse_store.syn.delete(existing_tables[table_name])
             sleep(10)
             # assert no table
-            assert table_name not in synapse_store.get_table_info(projectId = projectId).keys()
+            assert (
+                table_name
+                not in synapse_store.get_table_info(projectId=projectId).keys()
+            )
 
         # associate metadata with files
         manifest_path = "mock_manifests/table_manifest.csv"
-        inputModelLocaiton = helpers.get_data_path(os.path.basename(config.model_location))
-        
+        inputModelLocaiton = helpers.get_data_path(
+            os.path.basename(config.model_location)
+        )
+
         # Instantiate DataModelParser
-        data_model_parser = DataModelParser(path_to_data_model = inputModelLocaiton)
-        
-        #Parse Model
+        data_model_parser = DataModelParser(path_to_data_model=inputModelLocaiton)
+
+        # Parse Model
         parsed_data_model = data_model_parser.parse_model()
 
         # Instantiate DataModelGraph
@@ -414,45 +565,71 @@ def test_createTable(self, helpers, synapse_store, config: Configuration, projec
 
         # updating file view on synapse takes a long time
         manifestId = synapse_store.associateMetadataWithFiles(
-            dmge = dmge,
-            metadataManifestPath = helpers.get_data_path(manifest_path),
-            datasetId = datasetId,
-            manifest_record_type = 'table_and_file',
-            useSchemaLabel = True,
-            hideBlanks = True,
-            restrict_manifest = False,
+            dmge=dmge,
+            metadataManifestPath=helpers.get_data_path(manifest_path),
+            datasetId=datasetId,
+            manifest_record_type="table_and_file",
+            hideBlanks=True,
+            restrict_manifest=False,
             table_manipulation=table_manipulation,
+            table_column_names=table_column_names,
+            annotation_keys=annotation_keys,
         )
-        existing_tables = synapse_store.get_table_info(projectId = projectId)
-        
+        existing_tables = synapse_store.get_table_info(projectId=projectId)
+
         # clean Up
         synapse_store.syn.delete(manifestId)
         # assert table exists
         assert table_name in existing_tables.keys()
 
-    def test_replaceTable(self, helpers, synapse_store, config: Configuration, projectId, datasetId):
-        table_manipulation = 'replace'
 
-        table_name='followup_synapse_storage_manifest_table'
+    @pytest.mark.parametrize(
+        "table_column_names",
+        ["display_label", "class_label"],
+        ids=["tcn_display_label", "tcn_class_label"],
+    )
+    @pytest.mark.parametrize(
+        "annotation_keys",
+        ["display_label", "class_label"],
+        ids=["aks_display_label", "aks_class_label"],
+    )
+    def test_replaceTable(
+        self,
+        helpers,
+        synapse_store,
+        config: Configuration,
+        projectId,
+        datasetId,
+        table_column_names,
+        annotation_keys,
+    ):
+        table_manipulation = "replace"
+
+        table_name = "followup_synapse_storage_manifest_table"
         manifest_path = "mock_manifests/table_manifest.csv"
         replacement_manifest_path = "mock_manifests/table_manifest_replacement.csv"
-        column_of_interest="DaystoFollowUp"   
-        
+        column_of_interest = "DaystoFollowUp"
+
         # Check if FollowUp table exists if so delete
-        existing_tables = synapse_store.get_table_info(projectId = projectId)        
-        
+        existing_tables = synapse_store.get_table_info(projectId=projectId)
+
         if table_name in existing_tables.keys():
             synapse_store.syn.delete(existing_tables[table_name])
             sleep(10)
             # assert no table
-            assert table_name not in synapse_store.get_table_info(projectId = projectId).keys()
+            assert (
+                table_name
+                not in synapse_store.get_table_info(projectId=projectId).keys()
+            )
 
         # associate org FollowUp metadata with files
-        inputModelLocaiton = helpers.get_data_path(os.path.basename(config.model_location))
-        #sg = SchemaGenerator(inputModelLocaiton)
+        inputModelLocaiton = helpers.get_data_path(
+            os.path.basename(config.model_location)
+        )
+        # sg = SchemaGenerator(inputModelLocaiton)
 
-        data_model_parser = DataModelParser(path_to_data_model = inputModelLocaiton)
-        #Parse Model
+        data_model_parser = DataModelParser(path_to_data_model=inputModelLocaiton)
+        # Parse Model
         parsed_data_model = data_model_parser.parse_model()
 
         # Instantiate DataModelGraph
@@ -466,72 +643,97 @@ def test_replaceTable(self, helpers, synapse_store, config: Configuration, proje
 
         # updating file view on synapse takes a long time
         manifestId = synapse_store.associateMetadataWithFiles(
-            dmge = dmge,
-            metadataManifestPath = helpers.get_data_path(manifest_path),
-            datasetId = datasetId,
-            manifest_record_type = 'table_and_file',
-            useSchemaLabel = True,
-            hideBlanks = True,
-            restrict_manifest = False,
+            dmge=dmge,
+            metadataManifestPath=helpers.get_data_path(manifest_path),
+            datasetId=datasetId,
+            manifest_record_type="table_and_file",
+            hideBlanks=True,
+            restrict_manifest=False,
             table_manipulation=table_manipulation,
+            table_column_names=table_column_names,
+            annotation_keys=annotation_keys,
         )
-        existing_tables = synapse_store.get_table_info(projectId = projectId)
+        existing_tables = synapse_store.get_table_info(projectId=projectId)
 
-        # Query table for DaystoFollowUp column        
+        # Query table for DaystoFollowUp column
         tableId = existing_tables[table_name]
-        daysToFollowUp = synapse_store.syn.tableQuery(
-            f"SELECT {column_of_interest} FROM {tableId}"
-        ).asDataFrame().squeeze()
+        daysToFollowUp = (
+            synapse_store.syn.tableQuery(f"SELECT {column_of_interest} FROM {tableId}")
+            .asDataFrame()
+            .squeeze()
+        )
 
         # assert Days to FollowUp == 73
         assert (daysToFollowUp == 73).all()
-        
+
         # Associate replacement manifest with files
         manifestId = synapse_store.associateMetadataWithFiles(
-            dmge = dmge,
-            metadataManifestPath = helpers.get_data_path(replacement_manifest_path),
-            datasetId = datasetId,
-            manifest_record_type = 'table_and_file',
-            useSchemaLabel = True,
-            hideBlanks = True,
-            restrict_manifest = False,
+            dmge=dmge,
+            metadataManifestPath=helpers.get_data_path(replacement_manifest_path),
+            datasetId=datasetId,
+            manifest_record_type="table_and_file",
+            hideBlanks=True,
+            restrict_manifest=False,
             table_manipulation=table_manipulation,
+            table_column_names=table_column_names,
+            annotation_keys=annotation_keys,
         )
-        existing_tables = synapse_store.get_table_info(projectId = projectId)
-        
-        # Query table for DaystoFollowUp column        
+        existing_tables = synapse_store.get_table_info(projectId=projectId)
+
+        # Query table for DaystoFollowUp column
         tableId = existing_tables[table_name]
-        daysToFollowUp = synapse_store.syn.tableQuery(
-            f"SELECT {column_of_interest} FROM {tableId}"
-        ).asDataFrame().squeeze()
+        daysToFollowUp = (
+            synapse_store.syn.tableQuery(f"SELECT {column_of_interest} FROM {tableId}")
+            .asDataFrame()
+            .squeeze()
+        )
 
         # assert Days to FollowUp == 89 now and not 73
         assert (daysToFollowUp == 89).all()
-        # delete table        
+        # delete table
         synapse_store.syn.delete(tableId)
 
-    def test_upsertTable(self, helpers, synapse_store, config:Configuration, projectId, datasetId):
+
+    @pytest.mark.parametrize(
+        "annotation_keys",
+        ["display_label", "class_label"],
+        ids=["aks_display_label", "aks_class_label"],
+    )
+    def test_upsertTable(
+        self,
+        helpers,
+        synapse_store,
+        config: Configuration,
+        projectId,
+        datasetId,
+        annotation_keys,
+    ):
         table_manipulation = "upsert"
 
-        table_name="MockRDB_synapse_storage_manifest_table".lower()
+        table_name = "MockRDB_synapse_storage_manifest_table".lower()
         manifest_path = "mock_manifests/rdb_table_manifest.csv"
         replacement_manifest_path = "mock_manifests/rdb_table_manifest_upsert.csv"
-        column_of_interest="MockRDB_id,SourceManifest"
-        
+        column_of_interest = "MockRDB_id,SourceManifest"
+
         # Check if FollowUp table exists if so delete
-        existing_tables = synapse_store.get_table_info(projectId = projectId)        
-        
+        existing_tables = synapse_store.get_table_info(projectId=projectId)
+
         if table_name in existing_tables.keys():
             synapse_store.syn.delete(existing_tables[table_name])
             sleep(10)
             # assert no table
-            assert table_name not in synapse_store.get_table_info(projectId = projectId).keys()
+            assert (
+                table_name
+                not in synapse_store.get_table_info(projectId=projectId).keys()
+            )
 
         # associate org FollowUp metadata with files
-        inputModelLocaiton = helpers.get_data_path(os.path.basename(config.model_location))
+        inputModelLocaiton = helpers.get_data_path(
+            os.path.basename(config.model_location)
+        )
 
-        data_model_parser = DataModelParser(path_to_data_model = inputModelLocaiton)
-        #Parse Model
+        data_model_parser = DataModelParser(path_to_data_model=inputModelLocaiton)
+        # Parse Model
         parsed_data_model = data_model_parser.parse_model()
 
         # Instantiate DataModelGraph
@@ -543,71 +745,95 @@ def test_upsertTable(self, helpers, synapse_store, config:Configuration, project
         # Instantiate DataModelGraphExplorer
         dmge = DataModelGraphExplorer(graph_data_model)
 
-            # updating file view on synapse takes a long time
+        # updating file view on synapse takes a long time
         manifestId = synapse_store.associateMetadataWithFiles(
-            dmge = dmge,
-            metadataManifestPath = helpers.get_data_path(manifest_path),
-            datasetId = datasetId,
-            manifest_record_type = 'table_and_file',
-            useSchemaLabel = False,
-            hideBlanks = True,
-            restrict_manifest = False,
+            dmge=dmge,
+            metadataManifestPath=helpers.get_data_path(manifest_path),
+            datasetId=datasetId,
+            manifest_record_type="table_and_file",
+            hideBlanks=True,
+            restrict_manifest=False,
             table_manipulation=table_manipulation,
+            table_column_names="display_name",
+            annotation_keys=annotation_keys,
         )
-        existing_tables = synapse_store.get_table_info(projectId = projectId)
+        existing_tables = synapse_store.get_table_info(projectId=projectId)
 
-        #set primary key annotation for uploaded table
+        # set primary key annotation for uploaded table
         tableId = existing_tables[table_name]
 
-        # Query table for DaystoFollowUp column        
-        table_query = synapse_store.syn.tableQuery(
-            f"SELECT {column_of_interest} FROM {tableId}"
-        ).asDataFrame().squeeze()
+        # Query table for DaystoFollowUp column
+        table_query = (
+            synapse_store.syn.tableQuery(f"SELECT {column_of_interest} FROM {tableId}")
+            .asDataFrame()
+            .squeeze()
+        )
 
         # assert max ID is '4' and that there are 4 entries
         assert table_query.MockRDB_id.max() == 4
         assert table_query.MockRDB_id.size == 4
-        assert table_query['SourceManifest'][3] == 'Manifest1'
-        
+        assert table_query["SourceManifest"][3] == "Manifest1"
+
         # Associate new manifest with files
         manifestId = synapse_store.associateMetadataWithFiles(
-            dmge = dmge,
-            metadataManifestPath = helpers.get_data_path(replacement_manifest_path),
-            datasetId = datasetId, 
-            manifest_record_type = 'table_and_file',
-            useSchemaLabel = False,
-            hideBlanks = True,
-            restrict_manifest = False,
+            dmge=dmge,
+            metadataManifestPath=helpers.get_data_path(replacement_manifest_path),
+            datasetId=datasetId,
+            manifest_record_type="table_and_file",
+            hideBlanks=True,
+            restrict_manifest=False,
             table_manipulation=table_manipulation,
+            table_column_names="display_name",
+            annotation_keys=annotation_keys,
         )
-        existing_tables = synapse_store.get_table_info(projectId = projectId)
-        
-        # Query table for DaystoFollowUp column        
+        existing_tables = synapse_store.get_table_info(projectId=projectId)
+
+        # Query table for DaystoFollowUp column
         tableId = existing_tables[table_name]
-        table_query = synapse_store.syn.tableQuery(
-            f"SELECT {column_of_interest} FROM {tableId}"
-        ).asDataFrame().squeeze()
+        table_query = (
+            synapse_store.syn.tableQuery(f"SELECT {column_of_interest} FROM {tableId}")
+            .asDataFrame()
+            .squeeze()
+        )
 
         # assert max ID is '4' and that there are 4 entries
         assert table_query.MockRDB_id.max() == 8
         assert table_query.MockRDB_id.size == 8
-        assert table_query['SourceManifest'][3] == 'Manifest2'
-        # delete table        
+        assert table_query["SourceManifest"][3] == "Manifest2"
+        # delete table
         synapse_store.syn.delete(tableId)
 
+
 class TestDownloadManifest:
-    @pytest.mark.parametrize("datasetFileView", [{"id": ["syn51203973", "syn51203943"], "name": ["synapse_storage_manifest.csv", "synapse_storage_manifest_censored.csv"]}, {"id": ["syn51203973"], "name": ["synapse_storage_manifest.csv"]}, {"id": ["syn51203943"], "name": ["synapse_storage_manifest_censored.csv"]}])
+    @pytest.mark.parametrize(
+        "datasetFileView",
+        [
+            {
+                "id": ["syn51203973", "syn51203943"],
+                "name": [
+                    "synapse_storage_manifest.csv",
+                    "synapse_storage_manifest_censored.csv",
+                ],
+            },
+            {"id": ["syn51203973"], "name": ["synapse_storage_manifest.csv"]},
+            {"id": ["syn51203943"], "name": ["synapse_storage_manifest_censored.csv"]},
+        ],
+    )
     def test_get_manifest_id(self, synapse_store, datasetFileView):
         # rows that contain the censored manifest
         datasetFileViewDataFrame = pd.DataFrame(datasetFileView)
-        row_censored = datasetFileViewDataFrame.loc[datasetFileViewDataFrame['name'] == "synapse_storage_manifest_censored.csv"]
+        row_censored = datasetFileViewDataFrame.loc[
+            datasetFileViewDataFrame["name"] == "synapse_storage_manifest_censored.csv"
+        ]
         if not row_censored.empty > 0:
-            censored_manifest_id = row_censored['id'].values[0]
+            censored_manifest_id = row_censored["id"].values[0]
         # rows that contain the uncensored manifest
-        row_uncensored = datasetFileViewDataFrame.loc[datasetFileViewDataFrame['name'] == "synapse_storage_manifest.csv"]
+        row_uncensored = datasetFileViewDataFrame.loc[
+            datasetFileViewDataFrame["name"] == "synapse_storage_manifest.csv"
+        ]
         if not row_uncensored.empty > 0:
-            uncensored_manifest_id = row_uncensored['id'].values[0]
-        
+            uncensored_manifest_id = row_uncensored["id"].values[0]
+
         # get id of the uncensored manifest
         manifest_syn_id = synapse_store._get_manifest_id(datasetFileViewDataFrame)
 
@@ -615,42 +841,44 @@ def test_get_manifest_id(self, synapse_store, datasetFileView):
         if not row_uncensored.empty > 0:
             assert manifest_syn_id == uncensored_manifest_id
         # if only censored manifests are present, return only id of censored manifest
-        elif row_uncensored.empty and not row_censored.empty: 
+        elif row_uncensored.empty and not row_censored.empty:
             assert manifest_syn_id == censored_manifest_id
 
-    @pytest.mark.parametrize("newManifestName",["", "Example"]) 
+    @pytest.mark.parametrize("newManifestName", ["", "Example"])
     def test_download_manifest(self, mock_manifest_download, newManifestName):
         # test the download function by downloading a manifest
-        manifest_data = mock_manifest_download.download_manifest(mock_manifest_download, newManifestName)
-        assert os.path.exists(manifest_data['path'])
+        manifest_data = mock_manifest_download.download_manifest(
+            mock_manifest_download, newManifestName
+        )
+        assert os.path.exists(manifest_data["path"])
 
         if not newManifestName:
             assert manifest_data["name"] == "synapse_storage_manifest.csv"
         else:
             assert manifest_data["name"] == "Example.csv"
-        
+
         # clean up
-        os.remove(manifest_data['path'])
+        os.remove(manifest_data["path"])
 
     def test_download_access_restricted_manifest(self, synapse_store):
-        # attempt to download an uncensored manifest that has access restriction. 
+        # attempt to download an uncensored manifest that has access restriction.
         # if the code works correctly, the censored manifest that does not have access restriction would get downloaded (see: syn29862066)
         md = ManifestDownload(synapse_store.syn, "syn29862066")
         manifest_data = md.download_manifest(md)
 
-        assert os.path.exists(manifest_data['path'])
-        
-        # clean up 
-        os.remove(manifest_data['path'])
+        assert os.path.exists(manifest_data["path"])
+
+        # clean up
+        os.remove(manifest_data["path"])
 
     def test_download_manifest_on_aws(self, mock_manifest_download, monkeypatch):
         # mock AWS environment by providing SECRETS_MANAGER_SECRETS environment variable and attempt to download a manifest
-        monkeypatch.setenv('SECRETS_MANAGER_SECRETS', 'mock_value')
+        monkeypatch.setenv("SECRETS_MANAGER_SECRETS", "mock_value")
         manifest_data = mock_manifest_download.download_manifest(mock_manifest_download)
 
-        assert os.path.exists(manifest_data['path'])
-        # clean up 
-        os.remove(manifest_data['path'])       
+        assert os.path.exists(manifest_data["path"])
+        # clean up
+        os.remove(manifest_data["path"])
 
     @pytest.mark.parametrize("entity_id", ["syn27600053", "syn29862078"])
     def test_entity_type_checking(self, synapse_store, entity_id, caplog):
@@ -658,4 +886,7 @@ def test_entity_type_checking(self, synapse_store, entity_id, caplog):
         md._entity_type_checking()
         if entity_id == "syn27600053":
             for record in caplog.records:
-                assert "You are using entity type: folder. Please provide a file ID" in record.message
+                assert (
+                    "You are using entity type: folder. Please provide a file ID"
+                    in record.message
+                )
diff --git a/tests/test_utils.py b/tests/test_utils.py
index d9f06c845..3b99377f2 100644
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -18,7 +18,12 @@
 
 from schematic.schemas.data_model_parser import DataModelParser
 from schematic.schemas.data_model_graph import DataModelGraph, DataModelGraphExplorer
-from schematic.schemas.data_model_jsonld import DataModelJsonLD, BaseTemplate, PropertyTemplate, ClassTemplate
+from schematic.schemas.data_model_jsonld import (
+    DataModelJsonLD,
+    BaseTemplate,
+    PropertyTemplate,
+    ClassTemplate,
+)
 from schematic.schemas.data_model_json_schema import DataModelJSONSchema
 
 from schematic.schemas.data_model_relationships import DataModelRelationships
@@ -29,18 +34,35 @@
     MissingConfigAndArgumentValueError,
 )
 from schematic import LOADER
-from schematic.exceptions import (MissingConfigAndArgumentValueError,
-                                  MissingConfigValueError)
+from schematic.exceptions import (
+    MissingConfigAndArgumentValueError,
+    MissingConfigValueError,
+)
 
-from schematic.utils import (cli_utils, df_utils, general, io_utils,
-                             validate_utils)
-from schematic.utils.general import (calculate_datetime,
-                                     check_synapse_cache_size,
-                                     clear_synapse_cache, entity_type_mapping)
-from schematic.utils.schema_utils import (export_schema,
-                                          get_property_label_from_display_name,
-                                          get_class_label_from_display_name,
-                                          strip_context)
+from schematic.utils import cli_utils, df_utils, general, io_utils, validate_utils
+from schematic.utils.general import (
+    calculate_datetime,
+    check_synapse_cache_size,
+    clear_synapse_cache,
+    entity_type_mapping,
+)
+from schematic.utils.schema_utils import (
+    export_schema,
+    get_property_label_from_display_name,
+    get_class_label_from_display_name,
+    strip_context,
+    get_label_from_display_name,
+    get_schema_label,
+    get_stripped_label,
+    check_if_display_name_is_valid_label,
+    get_individual_rules,
+    get_component_name_rules,
+    parse_component_validation_rules,
+    parse_single_set_validation_rules,
+    parse_validation_rules,
+    extract_component_validation_rules,
+    check_for_duplicate_components,
+)
 
 
 logging.basicConfig(level=logging.DEBUG)
@@ -48,6 +70,96 @@
 
 IN_GITHUB_ACTIONS = os.getenv("GITHUB_ACTIONS")
 
+MULTI_RULE_DICT = {
+    "multi_rule": {
+        "starting_rule": "unique::list::num",
+        "parsed_rule": [["unique", "list", "num"]],
+    },
+    "double_rule": {
+        "starting_rule": "unique::list",
+        "parsed_rule": [["unique", "list"]],
+    },
+    "single_rule": {"starting_rule": "unique", "parsed_rule": ["unique"]},
+}
+
+TEST_VALIDATION_RULES = {
+    "multi_component_rule": {
+        "validation_rules": [
+            "#Patient int^^#Biospecimen unique error^^#BulkRNA-seqAssay int"
+        ],
+        "parsed_rules": {
+            "Patient": "int",
+            "Biospecimen": "unique error",
+            "BulkRNA-seqAssay": "int",
+        },
+        "extracted_rules": {
+            "Patient": ["int"],
+            "Biospecimen": ["unique error"],
+            "BulkRNA-seqAssay": ["int"],
+        },
+    },
+    "double_component_rule": {
+        "validation_rules": ["#Patient int^^#Biospecimen unique error"],
+        "parsed_rules": {"Patient": "int", "Biospecimen": "unique error"},
+        "extracted_rules": {"Patient": ["int"], "Biospecimen": ["unique error"]},
+    },
+    "single_component_rule_1": {
+        "validation_rules": ["#Patient int^^"],
+        "parsed_rules": {"Patient": "int"},
+        "extracted_rules": {"Patient": ["int"]},
+    },
+    "single_component_rule_2": {
+        "validation_rules": ["^^#Patient int"],
+        "parsed_rules": {"Patient": "int"},
+        "extracted_rules": {"Patient": ["int"]},
+    },
+    "single_component_exclusion": {
+        "validation_rules": ["int::inRange 100 900^^#Patient"],
+        "parsed_rules": {
+            "all_other_components": ["int", "inRange 100 900"],
+            "Patient": "",
+        },
+        "extracted_rules": {
+            "all_other_components": ["int", "inRange 100 900"],
+            "Patient": [],
+        },
+    },
+    "dictionary_rule": {
+        "validation_rules": {"BiospecimenManifest": "unique error", "Patient": "int"},
+        "parsed_rules": {"BiospecimenManifest": "unique error", "Patient": "int"},
+        "extracted_rules": {
+            "BiospecimenManifest": ["unique error"],
+            "Patient": ["int"],
+        },
+    },
+    "str_rule": {
+        "validation_rules": "#Patient int^^#Biospecimen unique error",
+        "parsed_rules": "raises_exception",
+    },
+    "simple_rule": {
+        "validation_rules": ["int"],
+        "parsed_rules": ["int"],
+    },
+    "double_rule": {
+        "validation_rules": ["list::regex match \(\d{3}\) \d{3}-\d{4}"],
+        "parsed_rules": ["list", "regex match \(\d{3}\) \d{3}-\d{4}"],
+    },
+    "duplicated_component": {
+        "validation_rules": ["#Patient unique^^#Patient int"],
+        "parsed_rules": "raises_exception",
+        }
+
+}
+
+TEST_DN_DICT = {
+    "Bio Things": {"class": "BioThings", "property": "bioThings"},
+    "bio things": {"class": "Biothings", "property": "biothings"},
+    "BioThings": {"class": "BioThings", "property": "bioThings"},
+    "Bio-things": {"class": "Biothings", "property": "biothings"},
+    "bio_things": {"class": "BioThings", "property": "bioThings"},
+}
+
+
 class TestGeneral:
     def test_clear_synapse_cache(self, tmp_path):
         # define location of mock synapse cache
@@ -55,14 +167,18 @@ def test_clear_synapse_cache(self, tmp_path):
         mock_synapse_cache_dir.mkdir()
         mock_sub_folder = mock_synapse_cache_dir / "123"
         mock_sub_folder.mkdir()
-        mock_table_query_folder = mock_sub_folder/ "456"
+        mock_table_query_folder = mock_sub_folder / "456"
         mock_table_query_folder.mkdir()
 
         # create mock table query csv and a mock cache map
-        mock_synapse_table_query_csv = mock_table_query_folder/ "mock_synapse_table_query.csv"
+        mock_synapse_table_query_csv = (
+            mock_table_query_folder / "mock_synapse_table_query.csv"
+        )
         mock_synapse_table_query_csv.write_text("mock table query content")
-        mock_cache_map = mock_table_query_folder/ ".cacheMap"
-        mock_cache_map.write_text(f"{mock_synapse_table_query_csv}: '2022-06-13T19:24:27.000Z'")
+        mock_cache_map = mock_table_query_folder / ".cacheMap"
+        mock_cache_map.write_text(
+            f"{mock_synapse_table_query_csv}: '2022-06-13T19:24:27.000Z'"
+        )
 
         assert os.path.exists(mock_synapse_table_query_csv)
 
@@ -76,31 +192,43 @@ def test_clear_synapse_cache(self, tmp_path):
         # make sure that cache files are now gone
         assert os.path.exists(mock_synapse_table_query_csv) == False
         assert os.path.exists(mock_cache_map) == False
-    
+
     def test_calculate_datetime_before_minutes(self):
-        input_date = datetime.strptime("07/20/23 17:36:34", '%m/%d/%y %H:%M:%S')
-        minutes_before = calculate_datetime(input_date=input_date, minutes=10, before_or_after="before")
-        expected_result_date_before = datetime.strptime("07/20/23 17:26:34", '%m/%d/%y %H:%M:%S')
+        input_date = datetime.strptime("07/20/23 17:36:34", "%m/%d/%y %H:%M:%S")
+        minutes_before = calculate_datetime(
+            input_date=input_date, minutes=10, before_or_after="before"
+        )
+        expected_result_date_before = datetime.strptime(
+            "07/20/23 17:26:34", "%m/%d/%y %H:%M:%S"
+        )
         assert minutes_before == expected_result_date_before
 
     def test_calculate_datetime_after_minutes(self):
-        input_date = datetime.strptime("07/20/23 17:36:34", '%m/%d/%y %H:%M:%S')
-        minutes_after = calculate_datetime(input_date=input_date, minutes=10, before_or_after="after")
-        expected_result_date_after = datetime.strptime("07/20/23 17:46:34", '%m/%d/%y %H:%M:%S')
+        input_date = datetime.strptime("07/20/23 17:36:34", "%m/%d/%y %H:%M:%S")
+        minutes_after = calculate_datetime(
+            input_date=input_date, minutes=10, before_or_after="after"
+        )
+        expected_result_date_after = datetime.strptime(
+            "07/20/23 17:46:34", "%m/%d/%y %H:%M:%S"
+        )
         assert minutes_after == expected_result_date_after
 
     def test_calculate_datetime_raise_error(self):
         with pytest.raises(ValueError):
-            input_date = datetime.strptime("07/20/23 17:36:34", '%m/%d/%y %H:%M:%S')
-            minutes = calculate_datetime(input_date=input_date, minutes=10, before_or_after="error")
-    
+            input_date = datetime.strptime("07/20/23 17:36:34", "%m/%d/%y %H:%M:%S")
+            minutes = calculate_datetime(
+                input_date=input_date, minutes=10, before_or_after="error"
+            )
+
     # this test might fail for windows machine
     @pytest.mark.not_windows
-    def test_check_synapse_cache_size(self,tmp_path):
+    def test_check_synapse_cache_size(self, tmp_path):
         mock_synapse_cache_dir = tmp_path / ".synapseCache"
         mock_synapse_cache_dir.mkdir()
 
-        mock_synapse_table_query_csv = mock_synapse_cache_dir/ "mock_synapse_table_query.csv"
+        mock_synapse_table_query_csv = (
+            mock_synapse_cache_dir / "mock_synapse_table_query.csv"
+        )
         mock_synapse_table_query_csv.write_text("example file for calculating cache")
 
         file_size = check_synapse_cache_size(mock_synapse_cache_dir)
@@ -112,7 +240,6 @@ def test_check_synapse_cache_size(self,tmp_path):
             assert file_size == 4000
 
     def test_find_duplicates(self):
-
         mock_list = ["foo", "bar", "foo"]
         mock_dups = {"foo"}
 
@@ -120,7 +247,6 @@ def test_find_duplicates(self):
         assert test_dups == mock_dups
 
     def test_dict2list_with_dict(self):
-
         mock_dict = {"foo": "bar"}
         mock_list = [{"foo": "bar"}]
 
@@ -128,14 +254,22 @@ def test_dict2list_with_dict(self):
         assert test_list == mock_list
 
     def test_dict2list_with_list(self):
-
         # mock_dict = {'foo': 'bar'}
         mock_list = [{"foo": "bar"}]
 
         test_list = general.dict2list(mock_list)
         assert test_list == mock_list
 
-    @pytest.mark.parametrize("entity_id,expected_type", [("syn27600053","folder"), ("syn29862078", "file"), ("syn23643253", "asset view"), ("syn30988314", "folder"), ("syn51182432", "org.sagebionetworks.repo.model.table.TableEntity")])
+    @pytest.mark.parametrize(
+        "entity_id,expected_type",
+        [
+            ("syn27600053", "folder"),
+            ("syn29862078", "file"),
+            ("syn23643253", "asset view"),
+            ("syn30988314", "folder"),
+            ("syn51182432", "org.sagebionetworks.repo.model.table.TableEntity"),
+        ],
+    )
     def test_entity_type_mapping(self, synapse_store, entity_id, expected_type):
         syn = synapse_store.syn
 
@@ -157,7 +291,6 @@ def test_download_manifest_to_temp_folder(self):
 
 class TestCliUtils:
     def test_query_dict(self):
-
         mock_dict = {"k1": {"k2": {"k3": "foobar"}}}
         mock_keys_valid = ["k1", "k2", "k3"]
         mock_keys_invalid = ["k1", "k2", "k4"]
@@ -192,7 +325,6 @@ def close(self):
 
 class TestIOUtils:
     def test_json_load(self, tmpdir):
-
         json_file = tmpdir.join("example.json")
         json_file.write_text(json.dumps([{"k1": "v1"}, {"k2": "v2"}]), encoding="utf-8")
 
@@ -204,7 +336,6 @@ def test_json_load(self, tmpdir):
         assert local_result == expected
 
     def test_json_load_online(self, mocker):
-
         mock_urlopen = mocker.patch(
             "urllib.request.urlopen",
             return_value=FakeResponse(
@@ -218,7 +349,6 @@ def test_json_load_online(self, mocker):
         assert mock_urlopen.call_count == 1
 
     def test_export_json(self, tmpdir):
-
         json_str = json.dumps([{"k1": "v1"}, {"k2": "v2"}])
 
         export_file = tmpdir.join("export_json_expected.json")
@@ -230,7 +360,6 @@ def test_export_json(self, tmpdir):
         assert expected == json_str
 
     def test_load_default(self):
-
         biothings_schema = io_utils.load_default()
 
         expected_ctx_keys = ["bts", "rdf", "rdfs", "schema", "xsd"]
@@ -242,10 +371,36 @@ def test_load_default(self):
         assert expected_no_of_keys == actual_no_of_keys
 
     def test_load_schema_org(self):
-
         schema_org_schema = io_utils.load_schemaorg()
 
-        expected_ctx_keys = ['brick', 'csvw', 'dc', 'dcam', 'dcat', 'dcmitype', 'dcterms', 'doap', 'foaf', 'odrl', 'org', 'owl', 'prof', 'prov', 'qb', 'rdf', 'rdfs', 'schema', 'sh', 'skos', 'sosa', 'ssn', 'time', 'vann', 'void', 'xsd']
+        expected_ctx_keys = [
+            "brick",
+            "csvw",
+            "dc",
+            "dcam",
+            "dcat",
+            "dcmitype",
+            "dcterms",
+            "doap",
+            "foaf",
+            "odrl",
+            "org",
+            "owl",
+            "prof",
+            "prov",
+            "qb",
+            "rdf",
+            "rdfs",
+            "schema",
+            "sh",
+            "skos",
+            "sosa",
+            "ssn",
+            "time",
+            "vann",
+            "void",
+            "xsd",
+        ]
         actual_ctx_keys = list(schema_org_schema["@context"].keys())
         assert expected_ctx_keys == actual_ctx_keys
 
@@ -255,8 +410,38 @@ def test_load_schema_org(self):
 
 
 class TestDfUtils:
-    def test_update_df_col_present(self, helpers):
+    @pytest.mark.parametrize(
+        "preserve_raw_input",
+        [True, False],
+        ids=["Do not infer datatypes", "Infer datatypes"],
+    )
+    def test_load_df(self, helpers, preserve_raw_input):
+        test_col = "Check NA"
+        file_path = helpers.get_data_path("mock_manifests", "Invalid_Test_Manifest.csv")
+
+        unprocessed_df = pd.read_csv(file_path, encoding="utf8")
+        df = df_utils.load_df(
+            file_path, preserve_raw_input=preserve_raw_input, data_model=False
+        )
 
+        assert df["Component"].dtype == "object"
+
+        n_unprocessed_rows = unprocessed_df.shape[0]
+        n_processed_rows = df.shape[0]
+
+        assert n_unprocessed_rows == 4
+        assert n_processed_rows == 3
+
+        if preserve_raw_input:
+            assert isinstance(df[test_col].iloc[0], str)
+            assert isinstance(df[test_col].iloc[1], str)
+            assert isinstance(df[test_col].iloc[2], str)
+        else:
+            assert isinstance(df[test_col].iloc[0], np.int64)
+            assert isinstance(df[test_col].iloc[1], float)
+            assert isinstance(df[test_col].iloc[2], str)
+
+    def test_update_df_col_present(self, helpers):
         synapse_manifest = helpers.get_data_frame(
             "mock_manifests", "synapse_manifest.csv"
         )
@@ -268,7 +453,6 @@ def test_update_df_col_present(self, helpers):
         assert_frame_equal(col_pres_res, synapse_manifest)
 
     def test_update_df_col_absent(self, helpers):
-
         synapse_manifest = helpers.get_data_frame(
             "mock_manifests", "synapse_manifest.csv"
         )
@@ -279,14 +463,13 @@ def test_update_df_col_absent(self, helpers):
             df_utils.update_df(local_manifest, synapse_manifest, "Col_Not_In_Dfs")
 
     def test_trim_commas_df(self, helpers):
-
         local_manifest = helpers.get_data_frame("mock_manifests", "local_manifest.csv")
 
         nan_row = pd.DataFrame(
             [[np.nan] * len(local_manifest.columns)], columns=local_manifest.columns
         )
 
-        df_with_nans = local_manifest.append(nan_row, ignore_index=True)
+        df_with_nans = pd.concat([local_manifest, nan_row], ignore_index=True)
 
         df_with_nans["Unnamed: 1"] = np.nan
         trimmed_df = df_utils.trim_commas_df(df_with_nans)
@@ -324,104 +507,460 @@ def test_update_dataframe(self):
 
     def test_populate_column(self):
         input_df = pd.DataFrame(
-            {
-                "column1": ["col1Val","col1Val"],
-                "column2": [None, None]
-            }
+            {"column1": ["col1Val", "col1Val"], "column2": [None, None]}
         )
 
-        output_df = df_utils.populate_df_col_with_another_col(input_df,'column1','column2')
-        assert (output_df["column2"].values == ["col1Val","col1Val"]).all()
+        output_df = df_utils.populate_df_col_with_another_col(
+            input_df, "column1", "column2"
+        )
+        assert (output_df["column2"].values == ["col1Val", "col1Val"]).all()
+
 
 class TestSchemaUtils:
     def test_get_property_label_from_display_name(self, helpers):
-
         # tests where strict_camel_case is the same
-        assert(get_property_label_from_display_name("howToAcquire") == "howToAcquire")
-        assert(get_property_label_from_display_name("howToAcquire", strict_camel_case = True) == "howToAcquire")
-        assert(get_property_label_from_display_name("how_to_acquire") == "howToAcquire")
-        assert(get_property_label_from_display_name("how_to_acquire", strict_camel_case = True) == "howToAcquire")
-        assert(get_property_label_from_display_name("howtoAcquire") == "howtoAcquire")
-        assert(get_property_label_from_display_name("howtoAcquire", strict_camel_case = True) == "howtoAcquire")
-        assert(get_property_label_from_display_name("How To Acquire") == "howToAcquire")
-        assert(get_property_label_from_display_name("How To Acquire", strict_camel_case = True) == "howToAcquire")
-        assert(get_property_label_from_display_name("Model Of Manifestation") == "modelOfManifestation")
-        assert(get_property_label_from_display_name("Model Of Manifestation", strict_camel_case = True) == "modelOfManifestation")
-        assert(get_property_label_from_display_name("ModelOfManifestation") == "modelOfManifestation")
-        assert(get_property_label_from_display_name("ModelOfManifestation", strict_camel_case = True) == "modelOfManifestation")
-        assert(get_property_label_from_display_name("model Of Manifestation") == "modelOfManifestation")
-        assert(get_property_label_from_display_name("model Of Manifestation", strict_camel_case = True) == "modelOfManifestation")
+        assert get_property_label_from_display_name("howToAcquire") == "howToAcquire"
+        assert (
+            get_property_label_from_display_name("howToAcquire", strict_camel_case=True)
+            == "howToAcquire"
+        )
+        assert get_property_label_from_display_name("how_to_acquire") == "howToAcquire"
+        assert (
+            get_property_label_from_display_name(
+                "how_to_acquire", strict_camel_case=True
+            )
+            == "howToAcquire"
+        )
+        assert get_property_label_from_display_name("howtoAcquire") == "howtoAcquire"
+        assert (
+            get_property_label_from_display_name("howtoAcquire", strict_camel_case=True)
+            == "howtoAcquire"
+        )
+        assert get_property_label_from_display_name("How To Acquire") == "howToAcquire"
+        assert (
+            get_property_label_from_display_name(
+                "How To Acquire", strict_camel_case=True
+            )
+            == "howToAcquire"
+        )
+        assert (
+            get_property_label_from_display_name("Model Of Manifestation")
+            == "modelOfManifestation"
+        )
+        assert (
+            get_property_label_from_display_name(
+                "Model Of Manifestation", strict_camel_case=True
+            )
+            == "modelOfManifestation"
+        )
+        assert (
+            get_property_label_from_display_name("ModelOfManifestation")
+            == "modelOfManifestation"
+        )
+        assert (
+            get_property_label_from_display_name(
+                "ModelOfManifestation", strict_camel_case=True
+            )
+            == "modelOfManifestation"
+        )
+        assert (
+            get_property_label_from_display_name("model Of Manifestation")
+            == "modelOfManifestation"
+        )
+        assert (
+            get_property_label_from_display_name(
+                "model Of Manifestation", strict_camel_case=True
+            )
+            == "modelOfManifestation"
+        )
 
         # tests where strict_camel_case changes the result
-        assert(get_property_label_from_display_name("how to Acquire") == "howtoAcquire")
-        assert(get_property_label_from_display_name("how to Acquire", strict_camel_case = True) == "howToAcquire")
-        assert(get_property_label_from_display_name("How to Acquire") == "howtoAcquire")
-        assert(get_property_label_from_display_name("How to Acquire", strict_camel_case = True) == "howToAcquire")
-        assert(get_property_label_from_display_name("how to acquire") == "howtoacquire")
-        assert(get_property_label_from_display_name("how to acquire", strict_camel_case = True) == "howToAcquire")
-        assert(get_property_label_from_display_name("model of manifestation") == "modelofmanifestation")
-        assert(get_property_label_from_display_name("model of manifestation", strict_camel_case = True) == "modelOfManifestation")
-        assert(get_property_label_from_display_name("model of manifestation") == "modelofmanifestation")
-        assert(get_property_label_from_display_name("model of manifestation", strict_camel_case = True) == "modelOfManifestation")
+        assert get_property_label_from_display_name("how to Acquire") == "howtoAcquire"
+        assert (
+            get_property_label_from_display_name(
+                "how to Acquire", strict_camel_case=True
+            )
+            == "howToAcquire"
+        )
+        assert get_property_label_from_display_name("How to Acquire") == "howtoAcquire"
+        assert (
+            get_property_label_from_display_name(
+                "How to Acquire", strict_camel_case=True
+            )
+            == "howToAcquire"
+        )
+        assert get_property_label_from_display_name("how to acquire") == "howtoacquire"
+        assert (
+            get_property_label_from_display_name(
+                "how to acquire", strict_camel_case=True
+            )
+            == "howToAcquire"
+        )
+        assert (
+            get_property_label_from_display_name("model of manifestation")
+            == "modelofmanifestation"
+        )
+        assert (
+            get_property_label_from_display_name(
+                "model of manifestation", strict_camel_case=True
+            )
+            == "modelOfManifestation"
+        )
+        assert (
+            get_property_label_from_display_name("model of manifestation")
+            == "modelofmanifestation"
+        )
+        assert (
+            get_property_label_from_display_name(
+                "model of manifestation", strict_camel_case=True
+            )
+            == "modelOfManifestation"
+        )
 
     def test_get_class_label_from_display_name(self, helpers):
-
         # tests where strict_camel_case is the same
-        assert(get_class_label_from_display_name("howToAcquire") == "HowToAcquire")
-        assert(get_class_label_from_display_name("howToAcquire", strict_camel_case = True) == "HowToAcquire")
-        assert(get_class_label_from_display_name("how_to_acquire") == "HowToAcquire")
-        assert(get_class_label_from_display_name("how_to_acquire", strict_camel_case = True) == "HowToAcquire")
-        assert(get_class_label_from_display_name("howtoAcquire") == "HowtoAcquire")
-        assert(get_class_label_from_display_name("howtoAcquire", strict_camel_case = True) == "HowtoAcquire")
-        assert(get_class_label_from_display_name("How To Acquire") == "HowToAcquire")
-        assert(get_class_label_from_display_name("How To Acquire", strict_camel_case = True) == "HowToAcquire")
-        assert(get_class_label_from_display_name("Model Of Manifestation") == "ModelOfManifestation")
-        assert(get_class_label_from_display_name("Model Of Manifestation", strict_camel_case = True) == "ModelOfManifestation")
-        assert(get_class_label_from_display_name("ModelOfManifestation") == "ModelOfManifestation")
-        assert(get_class_label_from_display_name("ModelOfManifestation", strict_camel_case = True) == "ModelOfManifestation")
-        assert(get_class_label_from_display_name("model Of Manifestation") == "ModelOfManifestation")
-        assert(get_class_label_from_display_name("model Of Manifestation", strict_camel_case = True) == "ModelOfManifestation")
+        assert get_class_label_from_display_name("howToAcquire") == "HowToAcquire"
+        assert (
+            get_class_label_from_display_name("howToAcquire", strict_camel_case=True)
+            == "HowToAcquire"
+        )
+        assert get_class_label_from_display_name("how_to_acquire") == "HowToAcquire"
+        assert (
+            get_class_label_from_display_name("how_to_acquire", strict_camel_case=True)
+            == "HowToAcquire"
+        )
+        assert get_class_label_from_display_name("howtoAcquire") == "HowtoAcquire"
+        assert (
+            get_class_label_from_display_name("howtoAcquire", strict_camel_case=True)
+            == "HowtoAcquire"
+        )
+        assert get_class_label_from_display_name("How To Acquire") == "HowToAcquire"
+        assert (
+            get_class_label_from_display_name("How To Acquire", strict_camel_case=True)
+            == "HowToAcquire"
+        )
+        assert (
+            get_class_label_from_display_name("Model Of Manifestation")
+            == "ModelOfManifestation"
+        )
+        assert (
+            get_class_label_from_display_name(
+                "Model Of Manifestation", strict_camel_case=True
+            )
+            == "ModelOfManifestation"
+        )
+        assert (
+            get_class_label_from_display_name("ModelOfManifestation")
+            == "ModelOfManifestation"
+        )
+        assert (
+            get_class_label_from_display_name(
+                "ModelOfManifestation", strict_camel_case=True
+            )
+            == "ModelOfManifestation"
+        )
+        assert (
+            get_class_label_from_display_name("model Of Manifestation")
+            == "ModelOfManifestation"
+        )
+        assert (
+            get_class_label_from_display_name(
+                "model Of Manifestation", strict_camel_case=True
+            )
+            == "ModelOfManifestation"
+        )
 
         # tests where strict_camel_case changes the result
-        assert(get_class_label_from_display_name("how to Acquire") == "HowtoAcquire")
-        assert(get_class_label_from_display_name("how to Acquire", strict_camel_case = True) == "HowToAcquire")
-        assert(get_class_label_from_display_name("How to Acquire") == "HowtoAcquire")
-        assert(get_class_label_from_display_name("How to Acquire", strict_camel_case = True) == "HowToAcquire")
-        assert(get_class_label_from_display_name("how to acquire") == "Howtoacquire")
-        assert(get_class_label_from_display_name("how to acquire", strict_camel_case = True) == "HowToAcquire")
-        assert(get_class_label_from_display_name("model of manifestation") == "Modelofmanifestation")
-        assert(get_class_label_from_display_name("model of manifestation", strict_camel_case = True) == "ModelOfManifestation")
-        assert(get_class_label_from_display_name("model of manifestation") == "Modelofmanifestation")
-        assert(get_class_label_from_display_name("model of manifestation", strict_camel_case = True) == "ModelOfManifestation")
-
-    @pytest.mark.parametrize("context_value", ['@id', 'sms:required'], ids=['remove_at', 'remove_sms'])
+        assert get_class_label_from_display_name("how to Acquire") == "HowtoAcquire"
+        assert (
+            get_class_label_from_display_name("how to Acquire", strict_camel_case=True)
+            == "HowToAcquire"
+        )
+        assert get_class_label_from_display_name("How to Acquire") == "HowtoAcquire"
+        assert (
+            get_class_label_from_display_name("How to Acquire", strict_camel_case=True)
+            == "HowToAcquire"
+        )
+        assert get_class_label_from_display_name("how to acquire") == "Howtoacquire"
+        assert (
+            get_class_label_from_display_name("how to acquire", strict_camel_case=True)
+            == "HowToAcquire"
+        )
+        assert (
+            get_class_label_from_display_name("model of manifestation")
+            == "Modelofmanifestation"
+        )
+        assert (
+            get_class_label_from_display_name(
+                "model of manifestation", strict_camel_case=True
+            )
+            == "ModelOfManifestation"
+        )
+        assert (
+            get_class_label_from_display_name("model of manifestation")
+            == "Modelofmanifestation"
+        )
+        assert (
+            get_class_label_from_display_name(
+                "model of manifestation", strict_camel_case=True
+            )
+            == "ModelOfManifestation"
+        )
+
+    @pytest.mark.parametrize(
+        "context_value", ["@id", "sms:required"], ids=["remove_at", "remove_sms"]
+    )
     def test_strip_context(self, helpers, context_value):
         stripped_contex = strip_context(context_value=context_value)
-        if '@id' == context_value:
-            assert stripped_contex == ('', 'id')
-        elif 'sms:required' == context_value:
-            assert stripped_contex == ('sms', 'required')
+        if "@id" == context_value:
+            assert stripped_contex == ("", "id")
+        elif "sms:required" == context_value:
+            assert stripped_contex == ("sms", "required")
+
+    @pytest.mark.parametrize(
+        "test_multi_rule",
+        list(MULTI_RULE_DICT.keys()),
+        ids=list(MULTI_RULE_DICT.keys()),
+    )
+    def test_get_individual_rules(self, test_multi_rule):
+        validation_rules = []
+        test_rule = MULTI_RULE_DICT[test_multi_rule]["starting_rule"]
+        expected_rule = MULTI_RULE_DICT[test_multi_rule]["parsed_rule"]
+        parsed_rule = get_individual_rules(
+            rule=test_rule,
+            validation_rules=validation_rules,
+        )
+        assert expected_rule == parsed_rule
+
+    @pytest.mark.parametrize(
+        "test_individual_component_rule",
+        [
+            ["#Patient int", [["Patient"], "int"]],
+            ["int", [["all_other_components"], "int"]],
+        ],
+        ids=["Patient_component", "no_component"],
+    )
+    def test_get_component_name_rules(self, test_individual_component_rule):
+        component_names = []
+
+        component, parsed_rule = get_component_name_rules(
+            component_names=[], component_rule=test_individual_component_rule[0]
+        )
+        expected_rule = test_individual_component_rule[1][1]
+        expected_component = test_individual_component_rule[1][0]
+
+        assert expected_rule == parsed_rule
+        assert expected_component == component
+
+    @pytest.mark.parametrize(
+        "test_individual_rule_set",
+        [
+            ["#Patient int::inRange 100 900", []],
+            ["int::inRange 100 900", ["int", "inRange 100 900"]],
+            ["int", ["int"]],
+        ],
+        ids=["improper_format", "double_rule", "single_rule"],
+    )
+    def test_parse_single_set_validation_rules(self, test_individual_rule_set):
+        validation_rule_string = test_individual_rule_set[0]
+        try:
+            parsed_rule = parse_single_set_validation_rules(
+                validation_rule_string=validation_rule_string
+            )
+            expected_rule = test_individual_rule_set[1]
+            assert parsed_rule == expected_rule
+        except:
+            assert validation_rule_string == "#Patient int::inRange 100 900"
+
+    @pytest.mark.parametrize(
+        "component_names",
+        [
+            ["duplicated_component", ['Patient', 'Biospecimen', 'Patient']],
+            ["individual_component", ['Patient', 'Biospecimen']],
+            ["no_component", []]
+        ],
+        ids=["duplicated_component", "individual_component", "no_component"],
+    )
+    def test_check_for_duplicate_components(self, component_names):
+        """Test that we are properly identifying duplicates in a list.
+            Exception should only be triggered when the duplicate component list is passed.
+        """
+        try:
+            check_for_duplicate_components(component_names=component_names[1], validation_rule_string='dummy_str')
+        except:
+            assert component_names[0] == "duplicated_component"
+
+    @pytest.mark.parametrize(
+        "test_rule_name",
+        list(TEST_VALIDATION_RULES.keys()),
+        ids=list(TEST_VALIDATION_RULES.keys()),
+    )
+    def test_parse_validation_rules(self, test_rule_name):
+        """
+        The test dictionary tests the following:
+            A dictionary rule is simply returned.
+            A string rule, raises an exception.
+            A single rule, a double rule, component rules, with a single component in either orientation,
+            double rules, multiple rules, creating a rule for all components except one.
+        """
+        validation_rules = TEST_VALIDATION_RULES[test_rule_name]["validation_rules"]
+        expected_parsed_rules = TEST_VALIDATION_RULES[test_rule_name]["parsed_rules"]
+
+        try:
+            parsed_validation_rules = parse_validation_rules(
+                validation_rules=validation_rules
+            )
+            assert expected_parsed_rules == parsed_validation_rules
+        except:
+            assert test_rule_name in ["str_rule", "duplicated_component"] 
+
+    @pytest.mark.parametrize(
+        "test_rule_name",
+        list(TEST_VALIDATION_RULES.keys()),
+        ids=list(TEST_VALIDATION_RULES.keys()),
+    )
+    def test_extract_component_validation_rules(self, test_rule_name):
+        """
+        Test that a component validation rule dictionary is parsed properly
+        """
+        attribute_rules_set = TEST_VALIDATION_RULES[test_rule_name]["parsed_rules"]
+        if isinstance(attribute_rules_set, dict):
+            for component in attribute_rules_set.keys():
+                extracted_rules = extract_component_validation_rules(
+                    component, attribute_rules_set
+                )
+                assert isinstance(extracted_rules, list)
+                assert (
+                    extracted_rules
+                    == TEST_VALIDATION_RULES[test_rule_name]["extracted_rules"][
+                        component
+                    ]
+                )
+    @pytest.mark.parametrize(
+        "test_dn",
+        list(TEST_DN_DICT.keys()),
+        ids=list(TEST_DN_DICT.keys()),
+    )
+    def test_check_if_display_name_is_valid_label(self, test_dn):
+        display_name = test_dn
+        blacklisted_chars = ["(", ")", ".", " ", "-"]
+        for entry_type, expected_result in TEST_DN_DICT[test_dn].items():
+            valid_label = check_if_display_name_is_valid_label(
+                test_dn, blacklisted_chars
+            )
+            if test_dn in ["Bio-things", "bio things", "Bio Things"]:
+                assert valid_label == False
+            else:
+                assert valid_label == True
+
+    @pytest.mark.parametrize(
+        "test_dn",
+        list(TEST_DN_DICT.keys())[-2:],
+        ids=list(TEST_DN_DICT.keys())[-2:],
+    )
+    def test_get_stripped_label(self, test_dn: str):
+        display_name = test_dn
+        blacklisted_chars = ["(", ")", ".", " ", "-"]
+        for entry_type, expected_result in TEST_DN_DICT[test_dn].items():
+            label = ""
+
+            label = get_stripped_label(
+                entry_type=entry_type,
+                display_name=display_name,
+                blacklisted_chars=blacklisted_chars,
+            )
+            assert label == expected_result
+
+    @pytest.mark.parametrize(
+        "test_dn",
+        list(TEST_DN_DICT.keys()),
+        ids=list(TEST_DN_DICT.keys()),
+    )
+    def test_get_schema_label(self, test_dn: str):
+        display_name = test_dn
+        for entry_type, expected_result in TEST_DN_DICT[test_dn].items():
+            label = ""
+
+            label = get_schema_label(
+                entry_type=entry_type,
+                display_name=display_name,
+                strict_camel_case=False,
+            )
+
+            if "-" in display_name:
+                # In this case, biothings will not strip the blacklisted character,
+                # so it will not match the dictionary.
+                if entry_type == "class":
+                    assert label == display_name.capitalize()
+                else:
+                    assert label == display_name[0].lower() + display_name[1:]
+            else:
+                assert label == expected_result
+
+    @pytest.mark.parametrize(
+        "test_dn",
+        list(TEST_DN_DICT.keys()),
+        ids=list(TEST_DN_DICT.keys()),
+    )
+    @pytest.mark.parametrize(
+        "data_model_labels",
+        ["display_label", "class_label"],
+        ids=["display_label", "class_label"],
+    )
+    def test_get_label_from_display_name(self, test_dn: str, data_model_labels: str):
+        display_name = test_dn
+        for entry_type, expected_result in TEST_DN_DICT[test_dn].items():
+            label = ""
+
+            try:
+                label = get_label_from_display_name(
+                    entry_type=entry_type,
+                    display_name=display_name,
+                    data_model_labels=data_model_labels,
+                )
+            except:
+                # Under these conditions should only fail if the display name cannot be used as a label.
+                assert test_dn in [
+                    "Bio Things",
+                    "bio things",
+                    "Bio-things",
+                    "bio_things",
+                ]
+            if label:
+                if data_model_labels == "display_label":
+                    if test_dn in ["Bio Things", "bio things", "Bio-things"]:
+                        assert label == expected_result
+
+                    else:
+                        assert label == test_dn
+                else:
+                    # The dash has an odd handling
+                    if display_name == "Bio-things":
+                        if entry_type == "property":
+                            assert label == "bio-things"
+                        else:
+                            assert label == "Bio-things"
+                    else:
+                        assert label == expected_result
+
+            else:
+                return
+        return
+
 
 class TestValidateUtils:
     def test_validate_schema(self, helpers):
-        '''
-        Previously did:
-        se_obj = helpers.get_schema_explorer("example.model.jsonld")
-        actual = validate_utils.validate_schema(se_obj.schema)
-
-        schema is defined as: self.schema = load_json(schema)
+        """
+        """
 
-        TODO: Validate this is doing what its supposed to.
-        '''
         # Get data model path
         data_model_path = helpers.get_data_path("example.model.jsonld")
         schema = io_utils.load_json(data_model_path)
-        #need to pass the jsonschema
+        # need to pass the jsonschema
         actual = validate_utils.validate_schema(schema)
 
         assert actual is None
 
-
     def test_validate_class_schema(self, helpers):
         """
         Get a class template, fill it out with mock data, and validate against a JSON Schema
@@ -435,12 +974,11 @@ def test_validate_class_schema(self, helpers):
         mock_class["@type"] = "rdfs:Class"
         mock_class["@rdfs:comment"] = "This is a mock class"
         mock_class["@rdfs:label"] = "MockClass"
-        mock_class["rdfs:subClassOf"].append({"@id":"bts:Patient"})
+        mock_class["rdfs:subClassOf"].append({"@id": "bts:Patient"})
 
         error = validate_utils.validate_class_schema(mock_class)
 
         assert error is None
-        
 
     def test_validate_property_schema(self, helpers):
         """
@@ -454,13 +992,13 @@ def test_validate_property_schema(self, helpers):
         mock_class["@id"] = "bts:MockProperty"
         mock_class["@type"] = "rdf:Property"
         mock_class["@rdfs:comment"] = "This is a mock Patient class"
-        mock_class["@rdfs:label"] = "MockProperty"      
-        mock_class["schema:domainIncludes"].append({"@id":"bts:Patient"})
+        mock_class["@rdfs:label"] = "MockProperty"
+        mock_class["schema:domainIncludes"].append({"@id": "bts:Patient"})
 
         error = validate_utils.validate_property_schema(mock_class)
 
         assert error is None
-        
+
 
 class TestCsvUtils:
     def test_csv_to_schemaorg(self, helpers, tmp_path):
@@ -473,9 +1011,9 @@ def test_csv_to_schemaorg(self, helpers, tmp_path):
         csv_path = helpers.get_data_path("example.model.csv")
 
         # Instantiate DataModelParser
-        data_model_parser = DataModelParser(path_to_data_model = csv_path)
-        
-        #Parse Model
+        data_model_parser = DataModelParser(path_to_data_model=csv_path)
+
+        # Parse Model
         parsed_data_model = data_model_parser.parse_model()
 
         # Instantiate DataModelGraph
diff --git a/tests/test_validation.py b/tests/test_validation.py
index df1211cfb..8e028b6fe 100644
--- a/tests/test_validation.py
+++ b/tests/test_validation.py
@@ -17,437 +17,585 @@
 from schematic.schemas.data_model_json_schema import DataModelJSONSchema
 
 from schematic.utils.validate_rules_utils import validation_rule_info
+
 logging.basicConfig(level=logging.DEBUG)
 logger = logging.getLogger(__name__)
 
+
 @pytest.fixture(name="dmge")
 def DMGE(helpers):
     dmge = helpers.get_data_model_graph_explorer(path="example.model.jsonld")
     yield dmge
 
+
 @pytest.fixture
 def metadataModel(helpers):
     metadataModel = MetadataModel(
-        inputMModelLocation = helpers.get_data_path("example.model.jsonld"),
-        inputMModelLocationType = "local"
-        )
+        inputMModelLocation=helpers.get_data_path("example.model.jsonld"),
+        inputMModelLocationType="local",
+        data_model_labels="class_label",
+    )
 
     yield metadataModel
 
+
 def get_rule_combinations():
     rule_info = validation_rule_info()
     for base_rule, indiv_info in rule_info.items():
-        complementary_rules = indiv_info['complementary_rules']
+        complementary_rules = indiv_info["complementary_rules"]
         if complementary_rules:
             for second_rule in complementary_rules:
                 yield base_rule, second_rule
         else:
             continue
-    
+
+
 class TestManifestValidation:
     # check if suite has been created. If so, delete it
     if os.path.exists("great_expectations/expectations/Manifest_test_suite.json"):
         os.remove("great_expectations/expectations/Manifest_test_suite.json")
 
-    def test_valid_manifest(self,helpers,metadataModel):
+    def test_valid_manifest(self, helpers, metadataModel):
         manifestPath = helpers.get_data_path("mock_manifests/Valid_Test_Manifest.csv")
-        rootNode = 'MockComponent'
+        rootNode = "MockComponent"
 
         errors, warnings = metadataModel.validateModelManifest(
             manifestPath=manifestPath,
             rootNode=rootNode,
-            project_scope = ["syn23643250"],
-            )
-            
-        assert errors == []
-        assert warnings ==  []
+            project_scope=["syn23643250"],
+        )
 
+        assert errors == []
+        assert warnings == []
 
-    def test_invalid_manifest(self,helpers, dmge,metadataModel):
+    def test_invalid_manifest(self, helpers, dmge, metadataModel):
         manifestPath = helpers.get_data_path("mock_manifests/Invalid_Test_Manifest.csv")
-        rootNode = 'MockComponent'
+        rootNode = "MockComponent"
 
         errors, warnings = metadataModel.validateModelManifest(
             manifestPath=manifestPath,
             rootNode=rootNode,
-            project_scope = ["syn23643250"],
-            )
+            project_scope=["syn23643250"],
+        )
 
-        #Check errors
-        assert GenerateError.generate_type_error(
-            val_rule = 'num',
-            row_num = '3',
-            attribute_name = 'Check Num', 
-            invalid_entry = 'c',
-            dmge = dmge,
-            )[0] in errors
-
-        assert GenerateError.generate_type_error(
-            val_rule = 'int',
-            row_num = '3',
-            attribute_name = 'Check Int', 
-            invalid_entry = '5.63',
-            dmge = dmge,
-            )[0] in errors
-
-        assert GenerateError.generate_type_error(
-            val_rule = 'str',
-            row_num = '3',
-            attribute_name = 'Check String', 
-            invalid_entry = '94',
-            dmge = dmge,
-            )[0] in errors
-
-        assert GenerateError.generate_list_error(
-            val_rule = 'list strict',
-            list_string = 'invalid list values',
-            row_num = '3',
-            attribute_name = 'Check List',
-            list_error = "not_comma_delimited",
-            invalid_entry = 'invalid list values',
-            dmge = dmge,
-            )[0] in errors
-
-        assert GenerateError.generate_list_error(
-            val_rule = 'list strict',
-            list_string = 'ab cd ef',
-            row_num = '3',
-            attribute_name = 'Check Regex List',
-            list_error = "not_comma_delimited",
-            invalid_entry = 'ab cd ef',
-            dmge = dmge,
-            )[0] in errors
-
-        assert GenerateError.generate_regex_error(
-            val_rule = 'regex',
-            reg_expression = '[a-f]',
-            row_num = '3',
-            attribute_name = 'Check Regex Format',
-            module_to_call = 'match',
-            invalid_entry = 'm',
-            dmge = dmge,
-            )[0] in errors   
-
-        assert GenerateError.generate_regex_error(
-            val_rule = 'regex',
-            reg_expression = '[a-f]',
-            row_num = '3',
-            attribute_name = 'Check Regex Single',
-            module_to_call = 'search',
-            invalid_entry = 'q',
-            dmge = dmge,
-            )[0] in errors
-
-        assert GenerateError.generate_regex_error(
-            val_rule = 'regex',
-            reg_expression = '^\d+$',
-            row_num = '2',
-            attribute_name = 'Check Regex Integer',
-            module_to_call = 'search',
-            invalid_entry = '5.4',
-            dmge = dmge,
-            )[0] in errors 
-
-        assert GenerateError.generate_url_error(
-            val_rule = 'url',
-            url = 'http://googlef.com/',
-            url_error = 'invalid_url',
-            row_num = '3',
-            attribute_name = 'Check URL',
-            argument = None,
-            invalid_entry = 'http://googlef.com/',
-            dmge = dmge,
-            )[0] in errors
+        # Check errors
+        assert (
+            GenerateError.generate_type_error(
+                val_rule="num",
+                row_num="3",
+                attribute_name="Check Num",
+                invalid_entry="c",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
 
+        assert (
+            GenerateError.generate_type_error(
+                val_rule="int",
+                row_num="3",
+                attribute_name="Check Int",
+                invalid_entry="5.63",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
 
-        date_err = GenerateError.generate_content_error(
-            val_rule = 'date',
-            attribute_name = 'Check Date',
-            dmge = dmge,
-            row_num = ['2','3','4'],
-            error_val = ['84-43-094', '32-984', 'notADate'],
+        assert (
+            GenerateError.generate_type_error(
+                val_rule="str",
+                row_num="3",
+                attribute_name="Check String",
+                invalid_entry="94",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_list_error(
+                val_rule="list strict",
+                list_string="invalid list values",
+                row_num="3",
+                attribute_name="Check List",
+                list_error="not_comma_delimited",
+                invalid_entry="invalid list values",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_list_error(
+                val_rule="list strict",
+                list_string="ab cd ef",
+                row_num="3",
+                attribute_name="Check Regex List",
+                list_error="not_comma_delimited",
+                invalid_entry="ab cd ef",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_regex_error(
+                val_rule="regex",
+                reg_expression="[a-f]",
+                row_num="3",
+                attribute_name="Check Regex Format",
+                module_to_call="match",
+                invalid_entry="m",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_regex_error(
+                val_rule="regex",
+                reg_expression="[a-f]",
+                row_num="3",
+                attribute_name="Check Regex Single",
+                module_to_call="search",
+                invalid_entry="q",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_regex_error(
+                val_rule="regex",
+                reg_expression="^\d+$",
+                row_num="2",
+                attribute_name="Check Regex Integer",
+                module_to_call="search",
+                invalid_entry="5.4",
+                dmge=dmge,
             )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_url_error(
+                val_rule="url",
+                url="http://googlef.com/",
+                url_error="invalid_url",
+                row_num="3",
+                attribute_name="Check URL",
+                argument=None,
+                invalid_entry="http://googlef.com/",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        date_err = GenerateError.generate_content_error(
+            val_rule="date",
+            attribute_name="Check Date",
+            dmge=dmge,
+            row_num=["2", "3", "4"],
+            error_val=["84-43-094", "32-984", "notADate"],
+        )[0]
         error_in_list = [date_err[2] in error for error in errors]
         assert any(error_in_list)
 
-        assert GenerateError.generate_content_error(
-            val_rule = 'unique error', 
-            attribute_name = 'Check Unique',
-            dmge = dmge,
-            row_num = ['2','3','4'],
-            error_val = ['str1'],  
-            )[0] in errors
-
-        assert GenerateError.generate_content_error(
-            val_rule = 'inRange 50 100 error', 
-            attribute_name = 'Check Range',
-            dmge = dmge,
-            row_num = ['3'],
-            error_val = ['30'], 
-            )[0] in errors
-
-        #check warnings
-        assert GenerateError.generate_content_error(
-            val_rule = 'recommended', 
-            attribute_name = 'Check Recommended',
-            dmge = dmge,
-            )[1] in warnings
-        
-        assert GenerateError.generate_content_error(
-            val_rule = 'protectAges', 
-            attribute_name = 'Check Ages',
-            dmge = dmge,
-            row_num = ['2','3'],
-            error_val = ['6549','32851'], 
-            )[1] in warnings
-
-        assert GenerateError.generate_cross_warning(
-            val_rule = 'matchAtLeastOne',
-            row_num = ['3'],
-            attribute_name='Check Match at Least',
-            invalid_entry = ['7163'],
-            missing_manifest_ID = ['syn27600110', 'syn29381803'],
-            dmge = dmge,
-            )[1] in warnings
-
-        assert  GenerateError.generate_cross_warning(
-            val_rule = 'matchAtLeastOne MockComponent.checkMatchatLeastvalues value',
-            row_num = ['3'],
-            attribute_name = 'Check Match at Least values',
-            invalid_entry = ['51100'],
-            dmge = dmge,
-            )[1] in warnings      
-
-        assert \
+        assert (
+            GenerateError.generate_content_error(
+                val_rule="unique error",
+                attribute_name="Check Unique",
+                dmge=dmge,
+                row_num=["2", "3", "4"],
+                error_val=["str1"],
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_content_error(
+                val_rule="inRange 50 100 error",
+                attribute_name="Check Range",
+                dmge=dmge,
+                row_num=["3"],
+                error_val=["30"],
+            )[0]
+            in errors
+        )
+
+        # check warnings
+        assert (
+            GenerateError.generate_content_error(
+                val_rule="recommended",
+                attribute_name="Check Recommended",
+                dmge=dmge,
+            )[1]
+            in warnings
+        )
+
+        assert (
+            GenerateError.generate_content_error(
+                val_rule="protectAges",
+                attribute_name="Check Ages",
+                dmge=dmge,
+                row_num=["2", "3"],
+                error_val=["6549", "32851"],
+            )[1]
+            in warnings
+        )
+
+        assert (
             GenerateError.generate_cross_warning(
-            val_rule = 'matchExactlyOne',
-            attribute_name='Check Match Exactly',
-            matching_manifests = ['syn29862078', 'syn27648165'],
-            dmge = dmge,
-            )[1] in warnings \
-            or \
+                val_rule="matchAtLeastOne",
+                row_num=["3"],
+                attribute_name="Check Match at Least",
+                invalid_entry=["7163"],
+                missing_manifest_ID=["syn27600110", "syn29381803"],
+                dmge=dmge,
+            )[1]
+            in warnings
+        )
+
+        assert (
             GenerateError.generate_cross_warning(
-            val_rule = 'matchExactlyOne',
-            attribute_name='Check Match Exactly',
-            matching_manifests = ['syn29862066', 'syn27648165'],
-            dmge = dmge,
-            )[1] in warnings
+                val_rule="matchAtLeastOne MockComponent.checkMatchatLeastvalues value",
+                row_num=["3"],
+                attribute_name="Check Match at Least values",
+                invalid_entry=["51100"],
+                dmge=dmge,
+            )[1]
+            in warnings
+        )
 
+        assert (
+            GenerateError.generate_cross_warning(
+                val_rule="matchExactlyOne",
+                attribute_name="Check Match Exactly",
+                matching_manifests=["syn29862078", "syn27648165"],
+                dmge=dmge,
+            )[1]
+            in warnings
+            or GenerateError.generate_cross_warning(
+                val_rule="matchExactlyOne",
+                attribute_name="Check Match Exactly",
+                matching_manifests=["syn29862066", "syn27648165"],
+                dmge=dmge,
+            )[1]
+            in warnings
+        )
 
         cross_warning = GenerateError.generate_cross_warning(
-            val_rule = 'matchExactlyOne MockComponent.checkMatchExactlyvalues MockComponent.checkMatchExactlyvalues value',
-            row_num = ['2', '3', '4'],
-            attribute_name='Check Match Exactly values',
-            invalid_entry = ['71738', '98085', '210065'],
-            dmge = dmge,
-            )[1]
+            val_rule="matchExactlyOne MockComponent.checkMatchExactlyvalues MockComponent.checkMatchExactlyvalues value",
+            row_num=["2", "3", "4"],
+            attribute_name="Check Match Exactly values",
+            invalid_entry=["71738", "98085", "210065"],
+            dmge=dmge,
+        )[1]
         warning_in_list = [cross_warning[1] in warning for warning in warnings]
         assert any(warning_in_list)
 
-        
-        
 
-    def test_in_house_validation(self,helpers,dmge,metadataModel):
+    def test_in_house_validation(self, helpers, dmge, metadataModel):
         manifestPath = helpers.get_data_path("mock_manifests/Invalid_Test_Manifest.csv")
-        rootNode = 'MockComponent'
+        rootNode = "MockComponent"
 
         errors, warnings = metadataModel.validateModelManifest(
             manifestPath=manifestPath,
             rootNode=rootNode,
             restrict_rules=True,
-            project_scope = ["syn23643250"],
-            )  
-
-        #Check errors
-        assert GenerateError.generate_type_error(
-            val_rule = 'num',
-            row_num = '3',
-            attribute_name = 'Check Num', 
-            invalid_entry = 'c',
-            dmge = dmge,
-            )[0] in errors
-
-        assert GenerateError.generate_type_error(
-            val_rule = 'int',
-            row_num = '3',
-            attribute_name = 'Check Int', 
-            invalid_entry = '5.63',
-            dmge = dmge,
-            )[0] in errors
-
-        assert GenerateError.generate_type_error(
-            val_rule = 'str',
-            row_num = '3',
-            attribute_name = 'Check String', 
-            invalid_entry = '94',
-            dmge = dmge,
-            )[0] in errors
-        
-        assert GenerateError.generate_type_error(
-            val_rule = 'int',
-            row_num = '3',
-            attribute_name = 'Check NA', 
-            invalid_entry = '9.5',
-            dmge = dmge,
-            )[0] in errors
-            
-        assert GenerateError.generate_list_error(
-            val_rule = 'list strict',
-            list_string = 'invalid list values',
-            row_num = '3',
-            attribute_name = 'Check List',
-            list_error = "not_comma_delimited",
-            invalid_entry = 'invalid list values',
-            dmge = dmge,
-            )[0] in errors
-
-        assert GenerateError.generate_list_error(
-            val_rule = 'list strict',
-            list_string = 'ab cd ef',
-            row_num = '3',
-            attribute_name = 'Check Regex List',
-            list_error = "not_comma_delimited",
-            invalid_entry = 'ab cd ef',
-            dmge = dmge,
-            )[0] in errors
-
-        assert GenerateError.generate_regex_error(
-            val_rule = 'regex',
-            reg_expression = '[a-f]',
-            row_num = '3',
-            attribute_name = 'Check Regex Single',
-            module_to_call = 'search',
-            invalid_entry = 'q',
-            dmge = dmge,
-            )[0] in errors 
-
-        assert GenerateError.generate_regex_error(
-            val_rule = 'regex',
-            reg_expression = '[a-f]',
-            row_num = '3',
-            attribute_name = 'Check Regex Format',
-            module_to_call = 'match',
-            invalid_entry = 'm',
-            dmge = dmge,
-            )[0] in errors     
-
-        assert GenerateError.generate_url_error(
-            val_rule = 'url',
-            url = 'http://googlef.com/',
-            url_error = 'invalid_url',
-            row_num = '3',
-            attribute_name = 'Check URL',
-            argument = None,
-            invalid_entry = 'http://googlef.com/',
-            dmge = dmge,
-            )[0] in errors
-
-        
-        #Check Warnings
-        assert GenerateError.generate_cross_warning(
-            val_rule = 'matchAtLeastOne',
-            row_num = ['3'],
-            attribute_name='Check Match at Least',
-            invalid_entry = ['7163'],
-            missing_manifest_ID = ['syn27600110', 'syn29381803'],
-            dmge = dmge,
-            )[1] in warnings
-
-        assert  GenerateError.generate_cross_warning(
-            val_rule = 'matchAtLeastOne MockComponent.checkMatchatLeastvalues value',
-            row_num = ['3'],
-            attribute_name = 'Check Match at Least values',
-            invalid_entry = ['51100'],
-            dmge = dmge,
-            )[1] in warnings      
-
-        assert \
+            project_scope=["syn23643250"],
+        )
+
+        # Check errors
+        assert (
+            GenerateError.generate_type_error(
+                val_rule="num",
+                row_num="3",
+                attribute_name="Check Num",
+                invalid_entry="c",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_type_error(
+                val_rule="int",
+                row_num="3",
+                attribute_name="Check Int",
+                invalid_entry="5.63",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_type_error(
+                val_rule="str",
+                row_num="3",
+                attribute_name="Check String",
+                invalid_entry="94",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_type_error(
+                val_rule="int",
+                row_num="3",
+                attribute_name="Check NA",
+                invalid_entry="9.5",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_list_error(
+                val_rule="list strict",
+                list_string="invalid list values",
+                row_num="3",
+                attribute_name="Check List",
+                list_error="not_comma_delimited",
+                invalid_entry="invalid list values",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_list_error(
+                val_rule="list strict",
+                list_string="ab cd ef",
+                row_num="3",
+                attribute_name="Check Regex List",
+                list_error="not_comma_delimited",
+                invalid_entry="ab cd ef",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_regex_error(
+                val_rule="regex",
+                reg_expression="[a-f]",
+                row_num="3",
+                attribute_name="Check Regex Single",
+                module_to_call="search",
+                invalid_entry="q",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_regex_error(
+                val_rule="regex",
+                reg_expression="[a-f]",
+                row_num="3",
+                attribute_name="Check Regex Format",
+                module_to_call="match",
+                invalid_entry="m",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        assert (
+            GenerateError.generate_url_error(
+                val_rule="url",
+                url="http://googlef.com/",
+                url_error="invalid_url",
+                row_num="3",
+                attribute_name="Check URL",
+                argument=None,
+                invalid_entry="http://googlef.com/",
+                dmge=dmge,
+            )[0]
+            in errors
+        )
+
+        # Check Warnings
+        assert (
+            GenerateError.generate_cross_warning(
+                val_rule="matchAtLeastOne",
+                row_num=["3"],
+                attribute_name="Check Match at Least",
+                invalid_entry=["7163"],
+                missing_manifest_ID=["syn27600110", "syn29381803"],
+                dmge=dmge,
+            )[1]
+            in warnings
+        )
+
+        assert (
+            GenerateError.generate_cross_warning(
+                val_rule="matchAtLeastOne MockComponent.checkMatchatLeastvalues value",
+                row_num=["3"],
+                attribute_name="Check Match at Least values",
+                invalid_entry=["51100"],
+                dmge=dmge,
+            )[1]
+            in warnings
+        )
+
+        assert (
             GenerateError.generate_cross_warning(
-            val_rule = 'matchExactlyOne',
-            attribute_name='Check Match Exactly',
-            matching_manifests = ['syn29862078', 'syn27648165'],
-            dmge = dmge,
-            )[1] in warnings \
-            or \
+                val_rule="matchExactlyOne",
+                attribute_name="Check Match Exactly",
+                matching_manifests=["syn29862078", "syn27648165"],
+                dmge=dmge,
+            )[1]
+            in warnings
+            or GenerateError.generate_cross_warning(
+                val_rule="matchExactlyOne",
+                attribute_name="Check Match Exactly",
+                matching_manifests=["syn29862066", "syn27648165"],
+                dmge=dmge,
+            )[1]
+            in warnings
+        )
+
+        assert (
             GenerateError.generate_cross_warning(
-            val_rule = 'matchExactlyOne',
-            attribute_name='Check Match Exactly',
-            matching_manifests = ['syn29862066', 'syn27648165'],
-            dmge = dmge,
-            )[1] in warnings
-                    
-        assert  GenerateError.generate_cross_warning(
-            val_rule = 'matchExactlyOne MockComponent.checkMatchExactlyvalues MockComponent.checkMatchExactlyvalues value',
-            row_num = ['2', '3', '4'],
-            attribute_name='Check Match Exactly values',
-            invalid_entry = ['71738', '98085', '210065'],
-            dmge = dmge,
-            )[1] in warnings 
-    
-
-    @pytest.mark.rule_combos(reason = 'This introduces a great number of tests covering every possible rule combination that are only necessary on occasion.')
+                val_rule="matchExactlyOne MockComponent.checkMatchExactlyvalues MockComponent.checkMatchExactlyvalues value",
+                row_num=["2", "3", "4"],
+                attribute_name="Check Match Exactly values",
+                invalid_entry=["71738", "98085", "210065"],
+                dmge=dmge,
+            )[1]
+            in warnings
+        )
+
+    @pytest.mark.parametrize(
+        "manifest_path",
+        [
+            "mock_manifests/example.biospecimen_component_rule.manifest.csv",
+            "mock_manifests/example.patient_component_rule.manifest.csv",
+        ],
+        ids=["biospecimen_manifest", "patient_manifest"],
+    )
+    def test_component_validations(self, helpers, manifest_path, dmge):
+        full_manifest_path = helpers.get_data_path(manifest_path)
+        manifest = helpers.get_data_frame(full_manifest_path)
+
+        root_node = manifest["Component"][0]
+
+        data_model_js = DataModelJSONSchema(
+            jsonld_path=helpers.get_data_path("example.model.csv"),
+            graph=dmge.graph,
+        )
+
+        json_schema = data_model_js.get_json_validation_schema(
+            source_node=root_node, schema_name=root_node + "_validation"
+        )
+
+        validateManifest = ValidateManifest(
+            errors=[],
+            manifest=manifest,
+            manifestPath=full_manifest_path,
+            dmge=dmge,
+            jsonSchema=json_schema,
+        )
+
+        _, vmr_errors, vmr_warnings = validateManifest.validate_manifest_rules(
+            manifest=manifest,
+            dmge=dmge,
+            restrict_rules=False,
+            project_scope=None,
+        )
+
+        if root_node == "Biospecimen":
+            assert (
+                vmr_errors
+                and vmr_errors[0][0] == ["2", "3"]
+                and vmr_errors[0][-1] == ["123"]
+            )
+            assert vmr_warnings == []
+        elif root_node == "Patient":
+            assert vmr_errors == []
+            assert (
+                vmr_warnings
+                and vmr_warnings[0][0] == ["2", "3"]
+                and vmr_warnings[0][-1] == ["123"]
+            )
+
+
+    @pytest.mark.rule_combos(
+        reason="This introduces a great number of tests covering every possible rule combination that are only necessary on occasion."
+    )
     @pytest.mark.parametrize("base_rule, second_rule", get_rule_combinations())
-    def test_rule_combinations(self, helpers, dmge, base_rule, second_rule, metadataModel):
+    def test_rule_combinations(
+        self, helpers, dmge, base_rule, second_rule, metadataModel
+    ):
         """
         TODO: Describe what this test is doing.
         Updating the data model graph to allow testing of allowable rule combinations.
         Works one rule combo at a time using (get_rule_combinations.)
         """
-        rule_regex = re.compile(base_rule+'.*')
-        rootNode = 'MockComponent'
+        rule_regex = re.compile(base_rule + ".*")
+        rootNode = "MockComponent"
 
         manifestPath = helpers.get_data_path("mock_manifests/Rule_Combo_Manifest.csv")
         manifest = helpers.get_data_frame(manifestPath)
-        
+
         # Get a view of the node data
         all_node_data = dmge.graph.nodes.data()
-        
+
         # Update select validation rules in the data model graph for columns in the manifest
         for attribute in manifest.columns:
             # Get the node label
             node_label = dmge.get_node_label(attribute)
-            
+
             # Get a view of the recorded info for current node
             node_info = all_node_data[node_label]
-            if node_info['validationRules']:
-                
-                if node_info['displayName'] == 'Check NA':
+            if node_info["validationRules"]:
+                if node_info["displayName"] == "Check NA":
                     # Edit the node info -in place-
-                    node_info['validationRules'].remove('int')
+                    node_info["validationRules"].remove("int")
                     break
-                
-                if base_rule in node_info['validationRules'] or re.match(rule_regex, node_info['validationRules'][0]):
-                    if second_rule.startswith('matchAtLeastOne') or second_rule.startswith('matchExactlyOne'):
+
+                if base_rule in node_info["validationRules"] or re.match(
+                    rule_regex, node_info["validationRules"][0]
+                ):
+                    if second_rule.startswith(
+                        "matchAtLeastOne"
+                    ) or second_rule.startswith("matchExactlyOne"):
                         rule_args = f" MockComponent.{node_label} Patient.PatientID"
-                    elif second_rule.startswith('inRange'):
-                        rule_args = ' 1 1000 warning'
-                    elif second_rule.startswith('regex'):
-                        rule_args = ' search [a-f]'
+                    elif second_rule.startswith("inRange"):
+                        rule_args = " 1 1000 warning"
+                    elif second_rule.startswith("regex"):
+                        rule_args = " search [a-f]"
                     else:
-                        rule_args = ''
+                        rule_args = ""
                     # Edit the node info -in place-
-                    node_info['validationRules'].append(second_rule + rule_args)
+                    node_info["validationRules"].append(second_rule + rule_args)
                     break
 
-        # Update the manifest to only contain the Component and attribute column where the rule was changed.        
-        manifest = manifest[['Component', attribute]]
-         
-        data_model_js = DataModelJSONSchema(jsonld_path=helpers.get_data_path('example.model.jsonld'), graph=dmge.graph)
-        json_schema = data_model_js.get_json_validation_schema(source_node=rootNode, schema_name=rootNode + "_validation")
+        # Update the manifest to only contain the Component and attribute column where the rule was changed.
+        manifest = manifest[["Component", attribute]]
 
-        validateManifest = ValidateManifest(
-            errors = [],
-            manifest = manifest,
-            manifestPath = manifestPath,
-            dmge = dmge,
-            jsonSchema = json_schema
+        data_model_js = DataModelJSONSchema(
+            jsonld_path=helpers.get_data_path("example.model.jsonld"), graph=dmge.graph
+        )
+        json_schema = data_model_js.get_json_validation_schema(
+            source_node=rootNode, schema_name=rootNode + "_validation"
         )
 
+        validateManifest = ValidateManifest(
+            errors=[],
+            manifest=manifest,
+            manifestPath=manifestPath,
+            dmge=dmge,
+            jsonSchema=json_schema,
+        )
 
-        #perform validation with no exceptions raised
+        # perform validation with no exceptions raised
         _, errors, warnings = validateManifest.validate_manifest_rules(
-            manifest = manifest, 
-            dmge = dmge,
-            restrict_rules = False,
-            project_scope = None,
-            )
+            manifest=manifest,
+            dmge=dmge,
+            restrict_rules=False,
+            project_scope=None,
+        )
diff --git a/tests/test_validator.py b/tests/test_validator.py
index 641fcccea..37ae008f6 100644
--- a/tests/test_validator.py
+++ b/tests/test_validator.py
@@ -13,17 +13,17 @@
 from schematic.schemas.data_model_jsonld import DataModelJsonLD, convert_graph_to_jsonld
 
 
-
 logging.basicConfig(level=logging.DEBUG)
 logger = logging.getLogger(__name__)
 
+
 def graph_data_model_func(helpers, data_model_name):
     path_to_data_model = helpers.get_data_path(data_model_name)
 
     # Instantiate Parser
     data_model_parser = DataModelParser(path_to_data_model=path_to_data_model)
 
-    #Parse Model
+    # Parse Model
     parsed_data_model = data_model_parser.parse_model()
 
     # Convert parsed model to graph
@@ -36,74 +36,87 @@ def graph_data_model_func(helpers, data_model_name):
     return graph_data_model
 
 
-
 class TestDataModelValidator:
     def test_check_blacklisted_characters(self, helpers):
         # Get graph data model
-        graph_data_model = graph_data_model_func(helpers, data_model_name='validator_test.model.csv')
-        
+        graph_data_model = graph_data_model_func(
+            helpers, data_model_name="validator_test.model.csv"
+        )
+
         # Instantiate Data Model Validator
         DMV = DataModelValidator(graph_data_model)
-        
+
         # Run validation
         validator_errors = DMV.check_blacklisted_characters()
 
         # Expected Error
-        expected_error = ['Node: Patient) contains a blacklisted character(s): ), they will be striped if used in Synapse annotations.',
-                          'Node: Patient ID. contains a blacklisted character(s): ., they will be striped if used in Synapse annotations.',
-                          'Node: Sex- contains a blacklisted character(s): -, they will be striped if used in Synapse annotations.',
-                          'Node: Year of Birth( contains a blacklisted character(s): (, they will be striped if used in Synapse annotations.',
-                          'Node: Bulk RNA-seq Assay contains a blacklisted character(s): -, they will be striped if used in Synapse annotations.',
-                          ]
+        expected_error = [
+            "Node: Patient) contains a blacklisted character(s): ), they will be striped if used in Synapse annotations.",
+            "Node: Patient ID. contains a blacklisted character(s): ., they will be striped if used in Synapse annotations.",
+            "Node: Sex- contains a blacklisted character(s): -, they will be striped if used in Synapse annotations.",
+            "Node: Year of Birth( contains a blacklisted character(s): (, they will be striped if used in Synapse annotations.",
+            "Node: Bulk RNA-seq Assay contains a blacklisted character(s): -, they will be striped if used in Synapse annotations.",
+        ]
 
         assert expected_error == validator_errors
 
     def test_check_reserved_names(self, helpers):
         # Get graph data model
-        graph_data_model = graph_data_model_func(helpers, data_model_name='validator_test.model.csv')
-        
+        graph_data_model = graph_data_model_func(
+            helpers, data_model_name="validator_test.model.csv"
+        )
+
         # Instantiate Data Model Validator
         DMV = DataModelValidator(graph_data_model)
-        
+
         # Run validation
         validator_errors = DMV.check_reserved_names()
 
         # Expected Error
-        expected_error = ['Your data model entry name: EntityId overlaps with the reserved name: entityId. Please change this name in your data model.']
+        expected_error = [
+            "Your data model entry name: EntityId overlaps with the reserved name: entityId. Please change this name in your data model."
+        ]
         assert expected_error == validator_errors
-    
+
     def test_check_graph_has_required_node_fields(self, helpers):
         # Get graph data model
-        graph_data_model = graph_data_model_func(helpers, data_model_name='validator_test.model.csv')
+        graph_data_model = graph_data_model_func(
+            helpers, data_model_name="validator_test.model.csv"
+        )
 
         # Remove a field from an entry graph
-        del graph_data_model.nodes['Cancer']['label']
+        del graph_data_model.nodes["Cancer"]["label"]
 
         # Instantiate Data Model Validator
         DMV = DataModelValidator(graph_data_model)
-        
+
         # Run validation
         validator_errors = DMV.check_graph_has_required_node_fields()
 
         # Expected Error
-        expected_error = ['For entry: Cancer, the required field label is missing in the data model graph, please double check your model and generate the graph again.']
+        expected_error = [
+            "For entry: Cancer, the required field label is missing in the data model graph, please double check your model and generate the graph again."
+        ]
         assert expected_error == validator_errors
 
     def test_dag(self, helpers):
-        # TODO: The schema validator currently doesn't catch the Diagnosis-Diagnosis self loop. 
+        # TODO: The schema validator currently doesn't catch the Diagnosis-Diagnosis self loop.
         # It is an expected error but it will need to be decided if the validator should prevent or allow such self loops
 
         # Get graph data model
-        graph_data_model = graph_data_model_func(helpers, data_model_name='validator_dag_test.model.csv')
+        graph_data_model = graph_data_model_func(
+            helpers, data_model_name="validator_dag_test.model.csv"
+        )
 
         # Instantiate Data Model Validator
         DMV = DataModelValidator(graph_data_model)
-        
+
         # Run validation
         validator_errors = DMV.check_is_dag()
 
         # nodes could be in different order so need to account for that
-        expected_errors = ['Schematic requires models be a directed acyclic graph (DAG). Please inspect your model.']
+        expected_errors = [
+            "Schematic requires models be a directed acyclic graph (DAG). Please inspect your model."
+        ]
 
         assert validator_errors[0] in expected_errors
-        
diff --git a/tests/test_viz.py b/tests/test_viz.py
index df344ad6e..3837620af 100644
--- a/tests/test_viz.py
+++ b/tests/test_viz.py
@@ -12,42 +12,56 @@
 logging.basicConfig(level=logging.DEBUG)
 logger = logging.getLogger(__name__)
 
+
 @pytest.fixture
 def attributes_explorer(helpers):
-
     # Get JSONLD file path
     path_to_jsonld = helpers.get_data_path("example.model.jsonld")
-    
+
     # Initialize TangledTree
-    attributes_explorer = AttributesExplorer(path_to_jsonld)
+    attributes_explorer = AttributesExplorer(
+        path_to_jsonld,
+        data_model_labels="class_label",
+    )
     yield attributes_explorer
 
+
 @pytest.fixture
 def tangled_tree(helpers):
-    figure_type = 'component'
+    figure_type = "component"
 
     # Get JSONLD file path
     path_to_jsonld = helpers.get_data_path("example.model.jsonld")
-    
+
     # Initialize TangledTree
-    tangled_tree = TangledTree(path_to_jsonld, figure_type)
+    tangled_tree = TangledTree(
+        path_to_jsonld, figure_type, data_model_labels="class_label"
+    )
     yield tangled_tree
 
+
 class TestVisualization:
     def test_ae(self, helpers, attributes_explorer):
         attributes_str = attributes_explorer.parse_attributes(save_file=False)
-        
-        df = pd.read_csv(StringIO(attributes_str)).drop(columns=['Unnamed: 0'])
+
+        df = pd.read_csv(StringIO(attributes_str)).drop(columns=["Unnamed: 0"])
 
         # For the attributes df define expected columns
-        expect_col_names = ['Attribute', 'Label', 'Description',
-                            'Required', 'Cond_Req', 'Valid Values', 'Conditional Requirements',
-                            'Component']
-        expected_components = ['Biospecimen', 'Patient', 'BulkRNA-seqAssay']
-        
+        expect_col_names = [
+            "Attribute",
+            "Label",
+            "Description",
+            "Required",
+            "Cond_Req",
+            "Valid Values",
+            "Conditional Requirements",
+            "Component",
+        ]
+        expected_components = ["Biospecimen", "Patient", "BulkRNA-seqAssay"]
+
         # Get actual values
         actual_column_names = df.columns.tolist()
-        actual_components = df.loc[df['Attribute']== 'Component']['Component'].tolist()
+        actual_components = df.loc[df["Attribute"] == "Component"]["Component"].tolist()
 
         assert actual_column_names == expect_col_names
         assert actual_components == expected_components
@@ -58,15 +72,24 @@ def test_ce(self, component, attributes_explorer):
         Test the output of parse_component_attributes
         """
         # get attributes string
-        component_attributes_str = attributes_explorer.parse_component_attributes(component=component,save_file=False, include_index=False)
+        component_attributes_str = attributes_explorer.parse_component_attributes(
+            component=component, save_file=False, include_index=False
+        )
         # convert to dataframe
         component_attributes = pd.read_csv(StringIO(component_attributes_str))
 
         # For the attributes df define expected columns
-        expect_col_names = ['Attribute', 'Label', 'Description',
-                            'Required', 'Cond_Req', 'Valid Values', 'Conditional Requirements',
-                            'Component']
-        
+        expect_col_names = [
+            "Attribute",
+            "Label",
+            "Description",
+            "Required",
+            "Cond_Req",
+            "Valid Values",
+            "Conditional Requirements",
+            "Component",
+        ]
+
         actual_column_names = component_attributes.columns.tolist()
 
         # assert all columns are present
@@ -74,28 +97,29 @@ def test_ce(self, component, attributes_explorer):
         # assert all attributes belong to the same component
         assert (component_attributes.Component == component).all()
 
-
     def test_text(self, helpers, tangled_tree):
-        text_format = 'plain'
+        text_format = "plain"
 
         # Get text for tangled tree.
         text_str = tangled_tree.get_text_for_tangled_tree(text_format, save_file=False)
-        
-        df= pd.read_csv(StringIO(text_str)).drop(columns=['Unnamed: 0'])
-        
+
+        df = pd.read_csv(StringIO(text_str)).drop(columns=["Unnamed: 0"])
+
         # Define expected text associated with 'Patient' and 'Imaging' tree
-        expected_patient_text = ['Biospecimen', 'BulkRNA-seqAssay']
+        expected_patient_text = ["Biospecimen", "BulkRNA-seqAssay"]
+
+        expected_Biospecimen_text = ["BulkRNA-seqAssay"]
 
-        expected_Biospecimen_text = ['BulkRNA-seqAssay']
-        
         # Get actual text
-        actual_patient_text = df.loc[df['Component'] == 'Patient']['name'].tolist()
+        actual_patient_text = df.loc[df["Component"] == "Patient"]["name"].tolist()
+
+        actual_Biospecimen_text = df.loc[df["Component"] == "Biospecimen"][
+            "name"
+        ].tolist()
 
-        actual_Biospecimen_text = df.loc[df['Component'] == 'Biospecimen']['name'].tolist()
-        
         # Check some random pieces of text we would assume to be in the plain text.
-        assert ((df['Component'] == 'Patient') & (df['name'] == 'Biospecimen')).any()
-        
+        assert ((df["Component"] == "Patient") & (df["name"] == "Biospecimen")).any()
+
         # Check the extracted text matches expected text.
         assert actual_patient_text == expected_patient_text
         assert actual_Biospecimen_text == expected_Biospecimen_text
@@ -104,46 +128,36 @@ def test_layers(self, helpers, tangled_tree):
         layers_str = tangled_tree.get_tangled_tree_layers(save_file=False)[0]
 
         # Define what we expect the layers list to be.
-        expected_layers_list = [[
-                                        {
-                                        "id": "Patient",
-                                        "parents": [],
-                                        "direct_children": [
-                                            "Biospecimen"
-                                        ],
-                                        "children": [
-                                            "BulkRNA-seqAssay",
-                                            "Biospecimen",
-                                        ]
-                                        }
-                                    ],
-                                    [
-                                        {
-                                        "id": "Biospecimen",
-                                        "parents": [
-                                            "Patient"
-                                        ],
-                                        "direct_children": [
-                                            "BulkRNA-seqAssay"
-                                        ],
-                                        "children": [
-                                            "BulkRNA-seqAssay"
-                                        ]
-                                        }
-                                    ],
-                                    [
-                                        {
-                                        "id": "BulkRNA-seqAssay",
-                                        "parents": [
-                                            "Biospecimen"
-                                        ],
-                                        "direct_children": [],
-                                        "children": []
-                                        }
-                                    ]
-                                ]
-
-                                
+        expected_layers_list = [
+            [
+                {
+                    "id": "Patient",
+                    "parents": [],
+                    "direct_children": ["Biospecimen"],
+                    "children": [
+                        "BulkRNA-seqAssay",
+                        "Biospecimen",
+                    ],
+                }
+            ],
+            [
+                {
+                    "id": "Biospecimen",
+                    "parents": ["Patient"],
+                    "direct_children": ["BulkRNA-seqAssay"],
+                    "children": ["BulkRNA-seqAssay"],
+                }
+            ],
+            [
+                {
+                    "id": "BulkRNA-seqAssay",
+                    "parents": ["Biospecimen"],
+                    "direct_children": [],
+                    "children": [],
+                }
+            ],
+        ]
+
         # Get actual layers.
         actual_layers_list = json.loads(layers_str)
 
@@ -151,7 +165,12 @@ def test_layers(self, helpers, tangled_tree):
         for index, item in enumerate(actual_layers_list):
             assert item[0]["id"] == expected_layers_list[index][0]["id"]
             assert item[0]["parents"] == expected_layers_list[index][0]["parents"]
-            assert item[0]["direct_children"] == expected_layers_list[index][0]["direct_children"]
+            assert (
+                item[0]["direct_children"]
+                == expected_layers_list[index][0]["direct_children"]
+            )
 
             # ensure that order of children doesn't matterß
-            assert set(item[0]["children"]) == set(expected_layers_list[index][0]["children"])
+            assert set(item[0]["children"]) == set(
+                expected_layers_list[index][0]["children"]
+            )
diff --git a/uwsgi-nginx-entrypoint.sh b/uwsgi-nginx-entrypoint.sh
index 0fa2e6188..722d49941 100644
--- a/uwsgi-nginx-entrypoint.sh
+++ b/uwsgi-nginx-entrypoint.sh
@@ -22,6 +22,8 @@ else
     content_server=$content_server'    proxy_read_timeout 300;\n'
     content_server=$content_server'    proxy_connect_timeout 300;\n'
     content_server=$content_server'    proxy_send_timeout 300;\n'
+    content_server=$content_server'    send_timeout 300;\n'
+    content_server=$content_server'    uwsgi_read_timeout 300;\n'
     content_server=$content_server'    location / {\n'
     content_server=$content_server'        try_files $uri @app;\n'
     content_server=$content_server'    }\n'