Drop Python 3.9; test on Python 3.13; drop NumPy 1.21; skip CUDA install

.github/workflows/array-api-tests-dask.yml

@@ -7,7 +7,6 @@ jobs:
     uses: ./.github/workflows/array-api-tests.yml
     with:
       package-name: dask
-      package-version: '>= 2024.9.0'
       module-name: dask.array
       extra-requires: numpy
       # Dask is substantially slower then other libraries on unit tests.
@@ -16,3 +15,4 @@ jobs:
       # flakiness. Before changes to dask-xfails.txt or dask-skips.txt, please run
       # the full test suite with at least 200 examples.
       pytest-extra-args: --max-examples=5
+      python-versions: '[''3.10'', ''3.13'']'

.github/workflows/array-api-tests-numpy-1-22.yml

@@ -0,0 +1,12 @@
+name: Array API Tests (NumPy 1.22)
+
+on: [push, pull_request]
+
+jobs:
+  array-api-tests-numpy-1-22:
+    uses: ./.github/workflows/array-api-tests.yml
+    with:
+      package-name: numpy
+      package-version: '== 1.22.*'
+      xfails-file-extra: '-1-22'
+      python-versions: '[''3.10'']'

.github/workflows/array-api-tests-numpy-1-26.yml

@@ -9,3 +9,4 @@ jobs:
       package-name: numpy
       package-version: '== 1.26.*'
       xfails-file-extra: '-1-26'
+      python-versions: '[''3.10'', ''3.12'']'

.github/workflows/array-api-tests-numpy-dev.yml

@@ -9,3 +9,4 @@ jobs:
       package-name: numpy
       extra-requires: '--pre --extra-index https://pypi.anaconda.org/scientific-python-nightly-wheels/simple'
       xfails-file-extra: '-dev'
+      python-versions: '[''3.11'', ''3.13'']'

.github/workflows/array-api-tests-numpy-latest.yml

@@ -1,4 +1,4 @@
-name: Array API Tests (NumPy Latest)
+name: Array API Tests (NumPy latest)
 
 on: [push, pull_request]
 
@@ -7,3 +7,4 @@ jobs:
     uses: ./.github/workflows/array-api-tests.yml
     with:
       package-name: numpy
+      python-versions: '[''3.10'', ''3.13'']'

.github/workflows/array-api-tests-torch.yml

@@ -1,4 +1,4 @@
-name: Array API Tests (PyTorch Latest)
+name: Array API Tests (PyTorch CPU)
 
 on: [push, pull_request]
 
@@ -7,5 +7,7 @@ jobs:
     uses: ./.github/workflows/array-api-tests.yml
     with:
       package-name: torch
+      extra-requires: '--index-url https://download.pytorch.org/whl/cpu'
       extra-env-vars: |
         ARRAY_API_TESTS_SKIP_DTYPES=uint16,uint32,uint64
+      python-versions: '[''3.10'', ''3.13'']'

.github/workflows/array-api-tests.yml

@@ -16,6 +16,10 @@ on:
         required: false
         type: string
         default: '>= 0'
+      python-versions:
+        required: true
+        type: string
+        description: JSON array of Python versions to test against.
       pytest-extra-args:
         required: false
         type: string
@@ -30,7 +34,7 @@ on:
       extra-env-vars:
         required: false
         type: string
-        description: "Multiline string of environment variables to set for the test run."
+        description: Multiline string of environment variables to set for the test run.
 
 env:
   PYTEST_ARGS: "--max-examples 200 -v -rxXfE --ci ${{ inputs.pytest-extra-args }} --hypothesis-disable-deadline --durations 10"
@@ -40,40 +44,42 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        # Min version of dask we need dropped support for Python 3.9
-        # There is no numpy git tip for Python 3.9 or 3.10
-        python-version: ${{ (inputs.package-name == 'dask' && fromJson('[''3.10'', ''3.11'', ''3.12'']')) || (inputs.package-name == 'numpy' && inputs.xfails-file-extra == '-dev' && fromJson('[''3.11'', ''3.12'']')) || fromJson('[''3.9'', ''3.10'', ''3.11'', ''3.12'']') }}
+        python-version: ${{ fromJson(inputs.python-versions) }}
 
     steps:
     - name: Checkout array-api-compat
       uses: actions/checkout@v4
       with:
         path: array-api-compat
+
     - name: Checkout array-api-tests
       uses: actions/checkout@v4
       with:
         repository: data-apis/array-api-tests
         submodules: 'true'
         path: array-api-tests
+
     - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
+
     - name: Set Extra Environment Variables
       # Set additional environment variables if provided
       if: inputs.extra-env-vars
       run: |
         echo "${{ inputs.extra-env-vars }}" >> $GITHUB_ENV
+
     - name: Install dependencies
-      # NumPy 1.21 doesn't support Python 3.11. There doesn't seem to be a way
-      # to put this in the numpy 1.21 config file.
-      if: "! ((matrix.python-version == '3.11' || matrix.python-version == '3.12') && inputs.package-name == 'numpy' && contains(inputs.package-version, '1.21'))"
       run: |
         python -m pip install --upgrade pip
         python -m pip install '${{ inputs.package-name }} ${{ inputs.package-version }}' ${{ inputs.extra-requires }}
         python -m pip install -r ${GITHUB_WORKSPACE}/array-api-tests/requirements.txt
+
+    - name: Dump pip environment
+      run: pip freeze
+
     - name: Run the array API testsuite (${{ inputs.package-name }})
-      if: "! ((matrix.python-version == '3.11' || matrix.python-version == '3.12') && inputs.package-name == 'numpy' && contains(inputs.package-version, '1.21'))"
       env:
         ARRAY_API_TESTS_MODULE: array_api_compat.${{ inputs.module-name || inputs.package-name }}
         ARRAY_API_TESTS_VERSION: 2024.12

.github/workflows/tests.yml

@@ -5,14 +5,23 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.9', '3.10', '3.11', '3.12']
-        numpy-version: ['1.21', '1.26', '2.0', 'dev']
-        exclude:
-          - python-version: '3.11'
-            numpy-version: '1.21'
-          - python-version: '3.12'
-            numpy-version: '1.21'
-      fail-fast: true
+        include:
+          - numpy-version: '1.22'
+            python-version: '3.10'
+          - numpy-version: '1.26'
+            python-version: '3.10'
+          - numpy-version: '1.26'
+            python-version: '3.12'
+          - numpy-version: 'latest'
+            python-version: '3.10'
+          - numpy-version: 'latest'
+            python-version: '3.13'
+          - numpy-version: 'dev'
+            python-version: '3.11'
+          - numpy-version: 'dev'
+            python-version: '3.13'
+
+      fail-fast: false
     steps:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v5
@@ -21,22 +30,29 @@ jobs:
       - name: Install Dependencies
         run: |
           python -m pip install --upgrade pip
+          python -m pip install pytest
+
           if [ "${{ matrix.numpy-version }}" == "dev" ]; then
-            PIP_EXTRA='numpy --pre --extra-index-url https://pypi.anaconda.org/scientific-python-nightly-wheels/simple'
-          elif [ "${{ matrix.numpy-version }}" == "1.21" ]; then
-            PIP_EXTRA='numpy==1.21.*'
+            python -m pip install numpy --pre --extra-index-url https://pypi.anaconda.org/scientific-python-nightly-wheels/simple
+          elif [ "${{ matrix.numpy-version }}" == "1.22" ]; then
+            python -m pip install 'numpy==1.22.*'
+          elif [ "${{ matrix.numpy-version }}" == "1.26" ]; then
+            python -m pip install 'numpy==1.26.*'
           else
-            PIP_EXTRA='numpy==1.26.*'
+            # Don't `pip install .[dev]` as it would pull in the whole torch cuda stack
+            python -m pip install array-api-strict dask[array] jax[cpu] numpy sparse
+            python -m pip install torch --index-url https://download.pytorch.org/whl/cpu
+            if [ "${{ matrix.python-version }}" != "3.13" ]; then
+              # onnx wheels are not available on Python 3.13 at the moment of writing
+              python -m pip install ndonnx
+            fi
           fi
 
-          python -m pip install .[dev] $PIP_EXTRA
+      - name: Dump pip environment
+        run: pip freeze
 
-      - name: Run Tests
-        run: |
-          if [[ "${{ matrix.numpy-version }}" == "1.21" || "${{ matrix.numpy-version }}" == "dev" ]]; then
-             PYTEST_EXTRA=(-k "numpy and not jax and not torch and not dask and not sparse")
-          fi
-          pytest -v "${PYTEST_EXTRA[@]}"
+      - name: Test it installs
+        run: python -m pip install .
 
-          # Make sure it installs
-          python -m pip install .
+      - name: Run Tests
+        run: pytest -v

array_api_compat/cupy/_typing.py

@@ -10,7 +10,7 @@
 from cupy.cuda.device import Device
 
 if TYPE_CHECKING:
-    # NumPy 1.x on Python 3.9 and 3.10 fails to parse np.dtype[]
+    # NumPy 1.x on Python 3.10 fails to parse np.dtype[]
     DType = cp.dtype[
         cp.intp
         | cp.int8

array_api_compat/dask/array/_aliases.py

@@ -147,7 +147,7 @@ def asarray(
     *,
     dtype: Optional[DType] = None,
     device: Optional[Device] = None,
-    copy: Optional[Union[bool, np._CopyMode]] = None,
+    copy: Optional[bool] = None,
     **kwargs,
 ) -> Array:
     """

array_api_compat/numpy/_aliases.py

@@ -99,18 +99,12 @@ def asarray(
     """
     _helpers._check_device(np, device)
 
-    if hasattr(np, '_CopyMode'):
-        if copy is None:
-            copy = np._CopyMode.IF_NEEDED
-        elif copy is False:
-            copy = np._CopyMode.NEVER
-        elif copy is True:
-            copy = np._CopyMode.ALWAYS
-    else:
-        # Not present in older NumPys. In this case, we cannot really support
-        # copy=False.
-        if copy is False:
-            raise NotImplementedError("asarray(copy=False) requires a newer version of NumPy.")
+    if copy is None:
+        copy = np._CopyMode.IF_NEEDED
+    elif copy is False:
+        copy = np._CopyMode.NEVER
+    elif copy is True:
+        copy = np._CopyMode.ALWAYS
 
     return np.array(obj, copy=copy, dtype=dtype, **kwargs)
 

array_api_compat/numpy/_typing.py

@@ -10,7 +10,7 @@
 
 Device = Literal["cpu"]
 if TYPE_CHECKING:
-    # NumPy 1.x on Python 3.9 and 3.10 fails to parse np.dtype[]
+    # NumPy 1.x on Python 3.10 fails to parse np.dtype[]
     DType = np.dtype[
         np.intp
         | np.int8

docs/supported-array-libraries.md

@@ -36,23 +36,16 @@ deviations from the standard should be noted:
   50](https://numpy.org/neps/nep-0050-scalar-promotion.html) and
   https://github.com/numpy/numpy/issues/22341)
 
-- `asarray()` does not support `copy=False`.
-
 - Functions which are not wrapped may not have the same type annotations
   as the spec.
 
 - Functions which are not wrapped may not use positional-only arguments.
 
-The minimum supported NumPy version is 1.21. However, this older version of
+The minimum supported NumPy version is 1.22. However, this older version of
 NumPy has a few issues:
 
 - `unique_*` will not compare nans as unequal.
-- `finfo()` has no `smallest_normal`.
 - No `from_dlpack` or `__dlpack__`.
-- `argmax()` and `argmin()` do not have `keepdims`.
-- `qr()` doesn't support matrix stacks.
-- `asarray()` doesn't support `copy=True` (as noted above, `copy=False` is not
-  supported even in the latest NumPy).
 - Type promotion behavior will be value based for 0-D arrays (and there is no
   `NPY_PROMOTION_STATE=weak` to disable this).
 
@@ -72,8 +65,8 @@ version.
   attribute in the spec. Use the {func}`~.size()` helper function as a
   portable workaround.
 
-- PyTorch does not have unsigned integer types other than `uint8`, and no
-  attempt is made to implement them here.
+- PyTorch has incomplete support for unsigned integer types other
+  than `uint8`, and no attempt is made to implement them here.
 
 - PyTorch has type promotion semantics that differ from the array API
   specification for 0-D tensor objects. The array functions in this wrapper
@@ -100,8 +93,6 @@ version.
 - As with NumPy, type annotations and positional-only arguments may not
   exactly match the spec for functions that are not wrapped at all.
 
-The minimum supported PyTorch version is 1.13.
-
 (jax-support)=
 ## [JAX](https://jax.readthedocs.io/en/latest/)
 
@@ -131,8 +122,6 @@ For `linalg`, several methods are missing, for example:
 - `matrix_rank`
 Other methods may only be partially implemented or return incorrect results at times.
 
-The minimum supported Dask version is 2023.12.0.
-
 (sparse-support)=
 ## [Sparse](https://sparse.pydata.org/en/stable/)