From 3da840e59f820c3287ad820ae496faf4e99a5f11 Mon Sep 17 00:00:00 2001
From: Nick <24689722+ntjohnson1@users.noreply.github.com>
Date: Wed, 23 Oct 2024 12:36:11 -0400
Subject: [PATCH 1/5] Nick/numpy 2 (#307)

* DOCTEST: Support Numpy 2.0 (check backwards compatbility)
* Convert numpy scalars to python with .item
* Make sure inputs to numpy groupies first arg is a row vector
* Replace in1d

* Numpy 2.0: Passing all standard tests
* Convert numpy scalars to python with .item
* Fix some minor typing changes

* DOCS: Fix incorrect sphinx keyword

* Remove typing_extensions dependecy since we aren't using inheritance to justify it

* Add verification of non-dev deps

* Might as well start covering 3.12

* Fix some type errors newer mypy found (one follow up)

* Fix workflow typo

* Pin numpy below 2.0 for stablization release.
---
 .github/workflows/regression-tests.yml | 15 ++++++-------
 pyproject.toml                         |  2 +-
 pyttb/gcp/handles.py                   |  6 ++++--
 pyttb/gcp/samplers.py                  |  7 ++++--
 pyttb/ktensor.py                       | 15 +++++++------
 pyttb/pyttb_utils.py                   | 30 +++++++++++++++++++++++++-
 pyttb/sptenmat.py                      |  2 +-
 pyttb/sptensor.py                      | 21 ++++++++++++------
 pyttb/sumtensor.py                     | 14 +++++++-----
 pyttb/tenmat.py                        |  9 +++++---
 pyttb/tensor.py                        | 28 +++++++++++++-----------
 pyttb/ttensor.py                       |  7 ++++--
 tests/test_tenmat.py                   |  2 +-
 13 files changed, 106 insertions(+), 52 deletions(-)

diff --git a/.github/workflows/regression-tests.yml b/.github/workflows/regression-tests.yml
index 7b960e98..5f5af7e0 100644
--- a/.github/workflows/regression-tests.yml
+++ b/.github/workflows/regression-tests.yml
@@ -16,7 +16,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.8", "3.9", "3.10", "3.11"]
+        python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
 
     steps:
     - uses: actions/checkout@v3
@@ -24,20 +24,19 @@ jobs:
       uses: actions/setup-python@v4
       with:
         python-version: ${{ matrix.python-version }}
-    - name: Install dependencies
+    - name: Install base dependencies
       run: |
         python -m pip install --upgrade pip
+        pip install .
+        # Basic check for minimal deployed env requirements
+        python -c "import pyttb"
+    - name: Install dev dependencies
+      run: |
         python -m pip install --upgrade coverage coveralls sphinx_rtd_theme
         pip install ".[dev]"
     - name: Check auto-formatters
       run: |
         black --check .
-#    - name: Lint with flake8
-#      run: |
-#        # stop the build if there are Python syntax errors or undefined names
-#        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
-#        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
-#        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
     - name: Run tests
       run: |
         coverage run --source pyttb -m pytest tests/
diff --git a/pyproject.toml b/pyproject.toml
index d6a08ef2..9786b957 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -10,7 +10,7 @@ readme = "README.md"
 requires-python = ">=3.8"
 
 dependencies = [
-    "numpy",
+    "numpy < 2",
     "numpy_groupies",
     "scipy",
 ]
diff --git a/pyttb/gcp/handles.py b/pyttb/gcp/handles.py
index c95ceab8..06a8dfff 100644
--- a/pyttb/gcp/handles.py
+++ b/pyttb/gcp/handles.py
@@ -115,15 +115,17 @@ def huber_grad(data: ttb.tensor, model: ttb.tensor, threshold: float) -> np.ndar
     ) * np.logical_not(below_threshold)
 
 
+# FIXME: Num trials should be enforced as integer here and in MATLAB
+# requires updating our regression test values to calculate MATLAB integer version
 def negative_binomial(
-    data: np.ndarray, model: np.ndarray, num_trials: int
+    data: np.ndarray, model: np.ndarray, num_trials: float
 ) -> np.ndarray:
     """Return objective function for negative binomial distributions"""
     return (num_trials + data) * np.log(model + 1) - data * np.log(model + EPS)
 
 
 def negative_binomial_grad(
-    data: np.ndarray, model: np.ndarray, num_trials: int
+    data: np.ndarray, model: np.ndarray, num_trials: float
 ) -> np.ndarray:
     """Return gradient function for negative binomial distributions"""
     return (num_trials + 1) / (1 + model) - data / (model + EPS)
diff --git a/pyttb/gcp/samplers.py b/pyttb/gcp/samplers.py
index 161571a4..d7dbda02 100644
--- a/pyttb/gcp/samplers.py
+++ b/pyttb/gcp/samplers.py
@@ -349,7 +349,7 @@ def zeros(
 
     # Select out just the zeros
     tmpidx = tt_sub2ind(data.shape, tmpsubs)
-    iszero = np.logical_not(np.in1d(tmpidx, nz_idx))
+    iszero = np.logical_not(np.isin(tmpidx, nz_idx))
     tmpsubs = tmpsubs[iszero, :]
 
     # Trim back to desired numb of samples
@@ -425,7 +425,7 @@ def semistrat(data: ttb.sptensor, num_nonzeros: int, num_zeros: int) -> sample_t
 
 
 def stratified(
-    data: ttb.sptensor,
+    data: Union[ttb.sptensor, ttb.tensor],
     nz_idx: np.ndarray,
     num_nonzeros: int,
     num_zeros: int,
@@ -450,6 +450,9 @@ def stratified(
     -------
     Subscripts, values, and weights of samples (Nonzeros then zeros).
     """
+    assert isinstance(
+        data, ttb.sptensor
+    ), "For stratified sampling Sparse Tensor must be provided"
     [nonzero_subs, nonzero_vals] = nonzeros(data, num_nonzeros, with_replacement=True)
     nonzero_weights = np.ones((num_nonzeros,))
     if num_nonzeros > 0:
diff --git a/pyttb/ktensor.py b/pyttb/ktensor.py
index 475f892c..38a0a256 100644
--- a/pyttb/ktensor.py
+++ b/pyttb/ktensor.py
@@ -22,13 +22,13 @@
 
 import numpy as np
 import scipy.sparse.linalg
-from typing_extensions import Self
 
 import pyttb as ttb
 from pyttb.pyttb_utils import (
     get_mttkrp_factors,
     isrow,
     isvector,
+    np_to_python,
     tt_dimscheck,
     tt_ind2sub,
 )
@@ -695,7 +695,8 @@ def extract(
                         invalid_entries.append(component)
                 if len(invalid_entries) > 0:
                     assert False, (
-                        f"Invalid component indices to be extracted: {invalid_entries} "
+                        f"Invalid component indices to be extracted: "
+                        f"{np_to_python(invalid_entries)} "
                         f"not in range({self.ncomponents})"
                     )
                 new_weights = self.weights[components]
@@ -706,7 +707,7 @@ def extract(
         else:
             assert False, "Input parameter must be an int, tuple, list or numpy.ndarray"
 
-    def fixsigns(self, other: Optional[ktensor] = None) -> Self:  # noqa: PLR0912
+    def fixsigns(self, other: Optional[ktensor] = None) -> ktensor:  # noqa: PLR0912
         """
         Change the elements of a :class:`pyttb.ktensor` in place so that the
         largest magnitude entries for each column vector in each factor
@@ -1184,7 +1185,7 @@ def normalize(
         sort: Optional[bool] = False,
         normtype: float = 2,
         mode: Optional[int] = None,
-    ) -> Self:
+    ) -> ktensor:
         """
         Normalize the columns of the factor matrices of a
         :class:`pyttb.ktensor` in place, then optionally
@@ -1405,7 +1406,7 @@ def permute(self, order: np.ndarray) -> ktensor:
 
         return ttb.ktensor([self.factor_matrices[i] for i in order], self.weights)
 
-    def redistribute(self, mode: int) -> Self:
+    def redistribute(self, mode: int) -> ktensor:
         """
         Distribute weights of a :class:`pyttb.ktensor` to the specified mode.
         The redistribution is performed in place.
@@ -1621,7 +1622,7 @@ def score(
 
             # Rearrange the components of A according to the best matching
             foo = np.arange(RA)
-            tf = np.in1d(foo, best_perm)
+            tf = np.isin(foo, best_perm)
             best_perm[RB : RA + 1] = foo[~tf]
             A.arrange(permutation=best_perm)
             return best_score, A, flag, best_perm
@@ -1999,7 +2000,7 @@ def ttv(
             factor_matrices.append(self.factor_matrices[i])
         return ttb.ktensor(factor_matrices, new_weights, copy=False)
 
-    def update(self, modes: Union[int, Iterable[int]], data: np.ndarray) -> Self:
+    def update(self, modes: Union[int, Iterable[int]], data: np.ndarray) -> ktensor:
         """
         Updates a :class:`pyttb.ktensor` in the specific dimensions with the
         values in `data` (in vector or matrix form). The value of `modes` must
diff --git a/pyttb/pyttb_utils.py b/pyttb/pyttb_utils.py
index 2a467b67..84bace2b 100644
--- a/pyttb/pyttb_utils.py
+++ b/pyttb/pyttb_utils.py
@@ -7,7 +7,16 @@
 
 from enum import Enum
 from inspect import signature
-from typing import List, Literal, Optional, Tuple, Union, get_args, overload
+from typing import (
+    Iterable,
+    List,
+    Literal,
+    Optional,
+    Tuple,
+    Union,
+    get_args,
+    overload,
+)
 
 import numpy as np
 
@@ -921,3 +930,22 @@ def gather_wrap_dims(
 
     assert rdims is not None and cdims is not None
     return rdims.astype(int), cdims.astype(int)
+
+
+def np_to_python(
+    iterable: Iterable,
+) -> Iterable:
+    """Convert a structure containing numpy scalars to pure python types.
+
+    Mostly useful for prettier printing post numpy 2.0.
+
+    Parameters
+    ----------
+    iterable:
+        Structure potentially containing numpy scalars.
+    """
+    output_type = type(iterable)
+    return output_type(  # type: ignore [call-arg]
+        element.item() if isinstance(element, np.generic) else element
+        for element in iterable
+    )
diff --git a/pyttb/sptenmat.py b/pyttb/sptenmat.py
index 8e8f6471..5f99b398 100644
--- a/pyttb/sptenmat.py
+++ b/pyttb/sptenmat.py
@@ -129,7 +129,7 @@ def __init__(  # noqa: PLR0913
             # Sum the corresponding values
             # Squeeze to convert from column vector to row vector
             newvals = accumarray(
-                loc, np.squeeze(vals, axis=1), size=newsubs.shape[0], func=sum
+                loc.flatten(), np.squeeze(vals, axis=1), size=newsubs.shape[0], func=sum
             )
 
         # Find the nonzero indices of the new values
diff --git a/pyttb/sptensor.py b/pyttb/sptensor.py
index de1f4d23..28690a79 100644
--- a/pyttb/sptensor.py
+++ b/pyttb/sptensor.py
@@ -33,6 +33,7 @@
     gather_wrap_dims,
     get_index_variant,
     get_mttkrp_factors,
+    np_to_python,
     tt_dimscheck,
     tt_ind2sub,
     tt_intersect_rows,
@@ -325,7 +326,10 @@ def from_aggregator(
             # Sum the corresponding values
             # Squeeze to convert from column vector to row vector
             newvals = accumarray(
-                loc, np.squeeze(vals), size=newsubs.shape[0], func=function_handle
+                loc.flatten(),
+                np.squeeze(vals),
+                size=newsubs.shape[0],
+                func=function_handle,
             )
 
         # Find the nonzero indices of the new values
@@ -445,7 +449,10 @@ def collapse(
 
         # Check for the case where we accumulate over *all* dimensions
         if remdims.size == 0:
-            return function_handle(self.vals.transpose()[0])
+            result = function_handle(self.vals.transpose()[0])
+            if isinstance(result, np.generic):
+                result = result.item()
+            return result
 
         # Calculate the size of the result
         newsize = np.array(self.shape)[remdims]
@@ -1319,7 +1326,7 @@ def nnz(self) -> int:
             return 0
         return self.subs.shape[0]
 
-    def norm(self) -> np.floating:
+    def norm(self) -> float:
         """
         Compute the norm (i.e., Frobenius norm, or square root of the sum of
         squares of entries) of the :class:`pyttb.sptensor`.
@@ -1339,7 +1346,7 @@ def norm(self) -> np.floating:
         >>> S.norm() # doctest: +ELLIPSIS
         5.47722557...
         """
-        return np.linalg.norm(self.vals)
+        return np.linalg.norm(self.vals).item()
 
     def nvecs(self, n: int, r: int, flipsign: bool = True) -> np.ndarray:
         """
@@ -1945,7 +1952,7 @@ def ttv(  # noqa: PLR0912
 
         # Case 0: If all dimensions were used, then just return the sum
         if remdims.size == 0:
-            return np.sum(newvals)
+            return np.sum(newvals).item()
 
         # Otherwise, figure out new subscripts and accumulate the results.
         newsiz = np.array(self.shape, dtype=int)[remdims]
@@ -3439,10 +3446,10 @@ def __repr__(self):  # pragma: no cover
         """
         nz = self.nnz
         if nz == 0:
-            s = f"empty sparse tensor of shape {self.shape!r}"
+            s = f"empty sparse tensor of shape {np_to_python(self.shape)!r}"
             return s
 
-        s = f"sparse tensor of shape {self.shape!r}"
+        s = f"sparse tensor of shape {np_to_python(self.shape)!r}"
         s += f" with {nz} nonzeros\n"
 
         # Stop insane printouts
diff --git a/pyttb/sumtensor.py b/pyttb/sumtensor.py
index c0683d5e..b1cbc1ae 100644
--- a/pyttb/sumtensor.py
+++ b/pyttb/sumtensor.py
@@ -13,6 +13,7 @@
 import numpy as np
 
 import pyttb as ttb
+from pyttb.pyttb_utils import np_to_python
 
 
 class sumtensor:
@@ -115,7 +116,10 @@ def __repr__(self):
         """
         if len(self.parts) == 0:
             return "Empty sumtensor"
-        s = f"sumtensor of shape {self.shape} with {len(self.parts)} parts:"
+        s = (
+            f"sumtensor of shape {np_to_python(self.shape)} "
+            f"with {len(self.parts)} parts:"
+        )
         for i, part in enumerate(self.parts):
             s += f"\nPart {i}: \n"
             s += indent(str(part), prefix="\t")
@@ -298,15 +302,15 @@ def innerprod(
 
         Examples
         --------
-        >>> T1 = ttb.tensor(np.array([[1, 0], [0, 4]]))
+        >>> T1 = ttb.tensor(np.array([[1., 0.], [0., 4.]]))
         >>> T2 = T1.to_sptensor()
         >>> S = ttb.sumtensor([T1, T2])
         >>> T1.innerprod(T1)
-        17
+        17.0
         >>> T1.innerprod(T2)
-        17
+        17.0
         >>> S.innerprod(T1)
-        34
+        34.0
         """
         result = self.parts[0].innerprod(other)
         for part in self.parts[1:]:
diff --git a/pyttb/tenmat.py b/pyttb/tenmat.py
index 24d3cab7..64a2eea9 100644
--- a/pyttb/tenmat.py
+++ b/pyttb/tenmat.py
@@ -30,7 +30,7 @@ def __init__(  # noqa: PLR0912
     ):
         """
         Construct a :class:`pyttb.tenmat` from explicit components.
-        If you already have a tensor see :method:`pyttb.tensor.to_tenmat`.
+        If you already have a tensor see :meth:`pyttb.tensor.to_tenmat`.
 
         Parameters
         ----------
@@ -176,9 +176,12 @@ def copy(self) -> tenmat:
         >>> TM2 = TM1
         >>> TM3 = TM1.copy()
         >>> TM1[0,0] = 3
-        >>> TM1[0,0] == TM2[0,0]
+
+        # Item to convert numpy boolean to python boolena for nicer printing
+
+        >>> (TM1[0,0] == TM2[0,0]).item()
         True
-        >>> TM1[0,0] == TM3[0,0]
+        >>> (TM1[0,0] == TM3[0,0]).item()
         False
         """
         # Create tenmat
diff --git a/pyttb/tensor.py b/pyttb/tensor.py
index b02b40ed..c3da3e86 100644
--- a/pyttb/tensor.py
+++ b/pyttb/tensor.py
@@ -23,6 +23,7 @@
     gather_wrap_dims,
     get_index_variant,
     get_mttkrp_factors,
+    np_to_python,
     tt_dimscheck,
     tt_ind2sub,
     tt_sub2ind,
@@ -254,7 +255,10 @@ def collapse(
 
         # Check for the case where we accumulate over *all* dimensions
         if remdims.size == 0:
-            return fun(self.data.flatten("F"))
+            result = fun(self.data.flatten("F"))
+            if isinstance(result, np.generic):
+                result = result.item()
+            return result
 
         ## Calculate the shape of the result
         newshape = tuple(np.array(self.shape)[remdims])
@@ -320,7 +324,7 @@ def contract(self, i1: int, i2: int) -> Union[np.ndarray, tensor]:
 
         # Easy case - returns a scalar
         if self.ndims == 2:
-            return np.trace(self.data)
+            return np.trace(self.data).item()
 
         # Remaining dimensions after trace
         remdims = np.setdiff1d(np.arange(0, self.ndims), np.array([i1, i2])).astype(int)
@@ -546,9 +550,9 @@ def to_tenmat(
         # Verify inputs
         if rdims is None and cdims is None:
             assert False, "Either rdims or cdims or both must be specified."
-        if rdims is not None and not sum(np.in1d(rdims, alldims)) == len(rdims):
+        if rdims is not None and not sum(np.isin(rdims, alldims)) == len(rdims):
             assert False, "Values in rdims must be in [0, source.ndims]."
-        if cdims is not None and not sum(np.in1d(cdims, alldims)) == len(cdims):
+        if cdims is not None and not sum(np.isin(cdims, alldims)) == len(cdims):
             assert False, "Values in cdims must be in [0, source.ndims]."
 
         rdims, cdims = gather_wrap_dims(n, rdims, cdims, cdims_cyclic)
@@ -587,19 +591,19 @@ def innerprod(
 
         Examples
         --------
-        >>> T = ttb.tensor(np.array([[1, 0], [0, 4]]))
+        >>> T = ttb.tensor(np.array([[1., 0.], [0., 4.]]))
         >>> T.innerprod(T)
-        17
+        17.0
         >>> S = T.to_sptensor()
         >>> T.innerprod(S)
-        17
+        17.0
         """
         if isinstance(other, ttb.tensor):
             if self.shape != other.shape:
                 assert False, "Inner product must be between tensors of the same size"
             x = np.reshape(self.data, (self.data.size,), order="F")
             y = np.reshape(other.data, (other.data.size,), order="F")
-            return x.dot(y)
+            return x.dot(y).item()
         if isinstance(other, (ttb.ktensor, ttb.sptensor, ttb.ttensor)):
             # Reverse arguments and call specializer code
             return other.innerprod(self)
@@ -1018,7 +1022,7 @@ def norm(self) -> float:
         # default of np.linalg.norm is to vectorize the data and compute the vector
         # norm, which is equivalent to the Frobenius norm for multidimensional arrays.
         # However, the argument 'fro' only works for 1-D and 2-D arrays currently.
-        return float(np.linalg.norm(self.data))
+        return np.linalg.norm(self.data).item()
 
     def nvecs(self, n: int, r: int, flipsign: bool = True) -> np.ndarray:
         """
@@ -1670,7 +1674,7 @@ def ttv(
         # If needed, convert the final result back to tensor
         if n > 0:
             return ttb.tensor(c, tuple(sz[0:n]), copy=False)
-        return c[0]
+        return c[0].item()
 
     def ttsv(
         self,
@@ -1978,7 +1982,7 @@ def __getitem__(self, item):  # noqa: PLR0912
             # If the size is zero, then the result is returned as a scalar
             # otherwise, we convert the result to a tensor
             if newsiz.size == 0:
-                a = newdata
+                a = newdata.item()
             else:
                 a = ttb.tensor(newdata, copy=False)
             return a
@@ -2508,7 +2512,7 @@ def __repr__(self):
             return s
 
         s = ""
-        s += f"tensor of shape {self.shape}"
+        s += f"tensor of shape {np_to_python(self.shape)}"
 
         if self.ndims == 1:
             s += "\ndata"
diff --git a/pyttb/ttensor.py b/pyttb/ttensor.py
index 8767f02f..7a4d42f4 100644
--- a/pyttb/ttensor.py
+++ b/pyttb/ttensor.py
@@ -106,9 +106,12 @@ def copy(self) -> ttensor:
         >>> second = first
         >>> third = second.copy()
         >>> first.factor_matrices[0][0,0] = 2
-        >>> first.factor_matrices[0][0,0] == second.factor_matrices[0][0,0]
+
+        # Item to convert numpy boolean to python boolena for nicer printing
+
+        >>> (first.factor_matrices[0][0,0] == second.factor_matrices[0][0,0]).item()
         True
-        >>> first.factor_matrices[0][0,0] == third.factor_matrices[0][0,0]
+        >>> (first.factor_matrices[0][0,0] == third.factor_matrices[0][0,0]).item()
         False
         """
         return ttb.ttensor(self.core, self.factor_matrices, copy=True)
diff --git a/tests/test_tenmat.py b/tests/test_tenmat.py
index ad8db719..04a426f4 100644
--- a/tests/test_tenmat.py
+++ b/tests/test_tenmat.py
@@ -355,7 +355,7 @@ def test_tenmat_ctranspose(sample_tenmat_4way):
 def test_tenmat_double(sample_tenmat_4way):
     (params, tenmatInstance) = sample_tenmat_4way
 
-    assert (tenmatInstance.double() == tenmatInstance.data.astype(np.float_)).all()
+    assert (tenmatInstance.double() == tenmatInstance.data.astype(np.float64)).all()
 
 
 def test_tenmat_ndims(sample_tenmat_4way):

From 1014abbcc06bb7b450bba8fbee380133517124b4 Mon Sep 17 00:00:00 2001
From: Danny Dunlavy <dmdunla@sandia.gov>
Date: Wed, 23 Oct 2024 10:52:37 -0600
Subject: [PATCH 2/5] Updating actions: versions plus pypi workflow. (#317)

* Updating actions: versions plus pypi workflow.

* Fixing formatting error.

Closes #316
---
 .github/workflows/markdown-check.yml   |  2 +-
 .github/workflows/pre-commit-check.yml |  6 +--
 .github/workflows/python-publish.yml   | 65 ++++++++++++++++----------
 .github/workflows/regression-tests.yml |  4 +-
 4 files changed, 47 insertions(+), 30 deletions(-)

diff --git a/.github/workflows/markdown-check.yml b/.github/workflows/markdown-check.yml
index 10c17a7b..89441ebd 100644
--- a/.github/workflows/markdown-check.yml
+++ b/.github/workflows/markdown-check.yml
@@ -10,5 +10,5 @@ jobs:
   markdown-link-check:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - uses: gaurav-nelson/github-action-markdown-link-check@v1
\ No newline at end of file
diff --git a/.github/workflows/pre-commit-check.yml b/.github/workflows/pre-commit-check.yml
index 04f86a39..441f55f8 100644
--- a/.github/workflows/pre-commit-check.yml
+++ b/.github/workflows/pre-commit-check.yml
@@ -9,6 +9,6 @@ jobs:
   pre-commit:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v3
-    - uses: actions/setup-python@v3
-    - uses: pre-commit/action@v3.0.0
\ No newline at end of file
+    - uses: actions/checkout@v4
+    - uses: actions/setup-python@v5
+    - uses: pre-commit/action@v3.0.1
\ No newline at end of file
diff --git a/.github/workflows/python-publish.yml b/.github/workflows/python-publish.yml
index ec703542..e27e5645 100644
--- a/.github/workflows/python-publish.yml
+++ b/.github/workflows/python-publish.yml
@@ -1,10 +1,6 @@
 # This workflow will upload a Python Package using Twine when a release is created
-# For more information see: https://help.github.com/en/actions/language-and-framework-guides/using-python-with-github-actions#publishing-to-package-registries
-
-# This workflow uses actions that are not certified by GitHub.
-# They are provided by a third-party and are governed by
-# separate terms of service, privacy policy, and support
-# documentation.
+# For more information see: 
+# https://packaging.python.org/en/latest/guides/publishing-package-distribution-releases-using-github-actions-ci-cd-workflows/
 
 name: Upload Python Package
 
@@ -12,28 +8,49 @@ on:
   release:
     types: [published]
 
-permissions:
-  contents: read
-
 jobs:
-  deploy:
-
+  build:
+    name: Build distribution
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Set up Python
-      uses: actions/setup-python@v3
+      uses: actions/setup-python@v5
+      with:
+        python-version: "3.x"
+    - name: Install pypa/build
+      run: >-
+        python3 -m
+        pip install
+        build
+        --user
+    - name: Build a binary wheel and a source tarball
+      run: python3 -m build
+    - name: Store the distribution packages
+      uses: actions/upload-artifact@v4
       with:
-        python-version: '3.x'
-    - name: Install dependencies
-      run: |
-        python -m pip install --upgrade pip
-        pip install build
-    - name: Build package
-      run: python -m build
-    - name: Publish package
-      uses: pypa/gh-action-pypi-publish@27b31702a0e7fc50959f5ad993c78deac1bdfc29
+        name: python-package-distributions
+        path: dist/
+  
+  publish-to-pypi:
+    name: >-
+      Publish Python distribution to PyPI
+    needs:
+    - build
+    runs-on: ubuntu-latest
+    environment:
+      name: pypi
+      url: https://pypi.org/p/pyttb
+    permissions:
+      id-token: write
+
+    steps:
+    - name: Download all the dists
+      uses: actions/download-artifact@v4
       with:
-        user: __token__
-        password: ${{ secrets.PYPI_API_TOKEN }}
+        name: python-package-distributions
+        path: dist/
+    - name: Publish distribution 📦 to PyPI
+      uses: pypa/gh-action-pypi-publish@release/v1
+
diff --git a/.github/workflows/regression-tests.yml b/.github/workflows/regression-tests.yml
index 5f5af7e0..dd3ecc93 100644
--- a/.github/workflows/regression-tests.yml
+++ b/.github/workflows/regression-tests.yml
@@ -19,9 +19,9 @@ jobs:
         python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install base dependencies

From cd391b6635acce5d1b1a274ca004baf655933bc9 Mon Sep 17 00:00:00 2001
From: Danny Dunlavy <dmdunla@sandia.gov>
Date: Wed, 23 Oct 2024 12:35:52 -0600
Subject: [PATCH 3/5] Update CONTRIBUTORS.md

---
 CONTRIBUTORS.md | 16 ++++++++++------
 1 file changed, 10 insertions(+), 6 deletions(-)

diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md
index 56f484d6..b4b435ff 100644
--- a/CONTRIBUTORS.md
+++ b/CONTRIBUTORS.md
@@ -12,15 +12,19 @@ U.S. Government retains certain rights in this software.
 
 **Main Developers:**
 
-- [Danny Dunlavy](https://github.com/dmdunla) - original author, `sptensor`, `ktensor`, `tensor`, `tenmat`, `cp_als`, `cp_apr`, 
+- [Danny Dunlavy](https://github.com/dmdunla) - original author
 [PRs](https://github.com/sandialabs/pyttb/commits?author=dmdunla) 
-- [Nick Johnson](https://github.com/ntjohnson1) - original author, `sptensor`, `ktensor`, `tensor`, `ttensor`, `cp_als`, `cp_apr`, 
+- [Nick Johnson](https://github.com/ntjohnson1) - original author
 [PRs](https://github.com/sandialabs/pyttb/commits?author=ntjohnson1)
-- [Jordan Medina](https://github.com/DeepBlockDeepak) - documentation, tutorials,
-[PRs](https://github.com/sandialabs/pyttb/commits?author=DeepBlockDeepak)
+- [Jeremy Myers](https://github.com/jeremy-myers) - bug fixes, documentation
+[PRs](https://github.com/sandialabs/pyttb/commits?author=jeremy-myers)
 
 **Other Contributors:**
-- [Brian Kelley](https://github.com/brian-kelley) - `numpy` compatability, 
+- [Brian Kelley](https://github.com/brian-kelley) - dependencies 
 [PRs](https://github.com/sandialabs/pyttb/commits?author=brian-kelley)
-- [Derek Tucker](https://github.com/jdtuck)[#1] - `tensor`, 
+- [Jordan Medina](https://github.com/DeepBlockDeepak) - bug fixes, documentation
+[PRs](https://github.com/sandialabs/pyttb/commits?author=DeepBlockDeepak)
+- [Eric Phipps](https://github.com/etphipp) - bug fixes
+[PRs](https://github.com/sandialabs/pyttb/commits?author=etphipp)
+- [Derek Tucker](https://github.com/jdtuck) - bug fixes
 [PRs](https://github.com/sandialabs/pyttb/commits?author=jdtuck)

From 153de3ebcb10921f4d5b826814aa117365f9d5b5 Mon Sep 17 00:00:00 2001
From: Danny Dunlavy <dmdunla@sandia.gov>
Date: Wed, 23 Oct 2024 12:36:34 -0600
Subject: [PATCH 4/5] Bump version

---
 pyttb/__init__.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyttb/__init__.py b/pyttb/__init__.py
index 06c061cd..78bf5864 100644
--- a/pyttb/__init__.py
+++ b/pyttb/__init__.py
@@ -5,7 +5,7 @@
 # U.S. Government retains certain rights in this software.
 from __future__ import annotations
 
-__version__ = "1.6.2"
+__version__ = "1.7.0"
 
 
 import warnings

From 24c84802ea05a7187f733e24c4d087e909926c50 Mon Sep 17 00:00:00 2001
From: Danny Dunlavy <dmdunla@sandia.gov>
Date: Wed, 23 Oct 2024 12:46:04 -0600
Subject: [PATCH 5/5] Updating docs for 3.12 support

---
 pyproject.toml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pyproject.toml b/pyproject.toml
index 9786b957..41a0a3a6 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -22,6 +22,7 @@ classifiers = [
     "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
 ]
 
 [project.urls]