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Initialize dev
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Inspirol authored Jan 11, 2024
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3 changes: 3 additions & 0 deletions .deploy_cfg
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[auth]
hostname = 7407

91 changes: 91 additions & 0 deletions .github/workflows/pull_request_coverage.yml
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name: Pull Request Coverage Report

on:
pull_request:
branches: [main, dev]

jobs:
run_coverage:
if: '${{ github.event.pull_request.head.repo.full_name == github.repository }}'
runs-on: ubuntu-latest

permissions:
issues: write
pull-requests: write
repository-projects: read
contents: read

steps:
- uses: actions/checkout@v1
with:
fetch-depth: 1

- name: Set up Python 3.11
uses: actions/setup-python@v1
with:
python-version: 3.11

# Cache the installation of Poetry itself, e.g. the next step. This prevents the workflow
# from installing Poetry every time, which can be slow. Note the use of the Poetry version
# number in the cache key, and the "-0" suffix: this allows you to invalidate the cache
# manually if/when you want to upgrade Poetry, or if something goes wrong. This could be
# mildly cleaner by using an environment variable, but I don't really care.
- name: cache poetry install
uses: actions/cache@v2
with:
path: ~/.local
key: poetry

# Install Poetry. You could do this manually, or there are several actions that do this.
# `snok/install-poetry` seems to be minimal yet complete, and really just calls out to
# Poetry's default install script, which feels correct. I pin the Poetry version here
# because Poetry does occasionally change APIs between versions and I don't want my
# actions to break if it does.
#
# The key configuration value here is `virtualenvs-in-project: true`: this creates the
# venv as a `.venv` in your testing directory, which allows the next step to easily
# cache it.
# - uses: snok/install-poetry@v1
# with:
# # version: 1.1.12
# virtualenvs-create: true
# virtualenvs-in-project: true

- run: pipx install poetry
# Cache your dependencies (i.e. all the stuff in your `pyproject.toml`). Note the cache
# key: if you're using multiple Python versions, or multiple OSes, you'd need to include
# them in the cache key. I'm not, so it can be simple and just depend on the poetry.lock.
- name: cache deps
id: cache-deps
uses: actions/cache@v2
with:
path: .venv
key: pydeps-${{ hashFiles('**/poetry.lock') }}

# Install dependencies. `--no-root` means "install all dependencies but not the project
# itself", which is what you want to avoid caching _your_ code. The `if` statement
# ensures this only runs on a cache miss.
- run: poetry install --no-interaction --no-root
if: steps.cache-deps.outputs.cache-hit != 'true'

# Now install _your_ project. This isn't necessary for many types of projects -- particularly
# things like Django apps don't need this. But it's a good idea since it fully-exercises the
# pyproject.toml and makes that if you add things like console-scripts at some point that
# they'll be installed and working.
- run: poetry install --no-interaction

# And finally run tests. I'm using pytest and all my pytest config is in my `pyproject.toml`
# so this line is super-simple. But it could be as complex as you need.
- run: poetry run coverage run --branch robot.py test --coverage-mode

- run: poetry run coverage xml --omit=mechanism_setup.py

- name: Get Cover
uses: orgoro/[email protected]
with:
coverageFile: coverage.xml
token: ${{ secrets.GITHUB_TOKEN }}
thresholdAll: .7
thresholdNew: .8
passIcon: '🎉'
failIcon: '💩'
59 changes: 59 additions & 0 deletions .github/workflows/tests.yml
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name: Tests

on:
push:
pull_request:
branches: [master]

jobs:
test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v1
with:
fetch-depth: 1

- name: Set up Python 3.11
uses: actions/setup-python@v1
with:
python-version: 3.11

# Cache the installation of Poetry itself, e.g. the next step. This prevents the workflow
# from installing Poetry every time, which can be slow. Note the use of the Poetry version
# number in the cache key, and the "-0" suffix: this allows you to invalidate the cache
# manually if/when you want to upgrade Poetry, or if something goes wrong. This could be
# mildly cleaner by using an environment variable, but I don't really care.
- name: cache poetry install
uses: actions/cache@v2
with:
path: ~/.local
key: poetry

# Install Poetry.
- run: pipx install poetry

# Cache your dependencies (i.e. all the stuff in your `pyproject.toml`). Note the cache
# key: if you're using multiple Python versions, or multiple OSes, you'd need to include
# them in the cache key. I'm not, so it can be simple and just depend on the poetry.lock.
- name: cache deps
id: cache-deps
uses: actions/cache@v2
with:
path: .venv
key: pydeps-${{ hashFiles('**/poetry.lock') }}

# Install dependencies. `--no-root` means "install all dependencies but not the project
# itself", which is what you want to avoid caching _your_ code. The `if` statement
# ensures this only runs on a cache miss.
- run: poetry install --no-interaction --no-root
if: steps.cache-deps.outputs.cache-hit != 'true'

# Now install _your_ project. This isn't necessary for many types of projects -- particularly
# things like Django apps don't need this. But it's a good idea since it fully-exercises the
# pyproject.toml and makes that if you add things like console-scripts at some point that
# they'll be installed and working.
- run: poetry install --no-interaction

# And finally run tests. I'm using pytest and all my pytest config is in my `pyproject.toml`
# so this line is super-simple. But it could be as complex as you need.
- run: poetry run coverage run robot.py test
161 changes: 161 additions & 0 deletions .gitignore
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# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class

# C extensions
*.so

# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
*.wpilog
MANIFEST

# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec

# Installer logs
pip-log.txt
pip-delete-this-directory.txt

# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/

# Translations
*.mo
*.pot

# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal

# Flask stuff:
instance/
.webassets-cache

# Scrapy stuff:
.scrapy

# Sphinx documentation
docs/_build/

# PyBuilder
.pybuilder/
target/

# Jupyter Notebook
.ipynb_checkpoints

# IPython
profile_default/
ipython_config.py

# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version

# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock

# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock

# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
# in version control.
# https://pdm.fming.dev/#use-with-ide
.pdm.toml

# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/

# Celery stuff
celerybeat-schedule
celerybeat.pid

# SageMath parsed files
*.sage.py

# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/

# Spyder project settings
.spyderproject
.spyproject

# Rope project settings
.ropeproject

# mkdocs documentation
/site

# mypy
.mypy_cache/
.dmypy.json
dmypy.json

# Pyre type checker
.pyre/

# pytype static type analyzer
.pytype/

# Cython debug symbols
cython_debug/

# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
.idea/
42 changes: 42 additions & 0 deletions .pre-commit-config.yaml
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repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v3.2.0
hooks:
- id: trailing-whitespace
- id: mixed-line-ending
- id: check-added-large-files
args: ['--maxkb=1000']
- id: end-of-file-fixer
- id: requirements-txt-fixer
- id: check-yaml
- id: check-json
- id: pretty-format-json
args: ['--autofix']
- id: check-merge-conflict
- id: check-case-conflict
- id: check-docstring-first

- repo: local
hooks:
- id: isort
name: isort
stages: [commit]
language: system
entry: isort
types: [python]

- id: black
name: black
stages: [commit]
language: system
entry: black
types: [python]

- id: flake8
name: flake8
stages: [commit]
language: system
entry: flake8
types: [python]
args: ['--max-line-length=120']
exclude: setup.py
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