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"
@@ -39,41 +43,44 @@ jobs:
  tests:
  runs-on: ubuntu-latest
  strategy:
+ fail-fast: false
  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

@@ -4,15 +4,24 @@ jobs:
  tests:
  runs-on: ubuntu-latest
  strategy:
+ fail-fast: false
  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'
+
  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/)