RFC: rm __array__, add __buffer__

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

@@ -11,11 +11,11 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.9', '3.10', '3.11', '3.12']
-        numpy-version: ['1.26', 'dev']
+        python-version: ['3.12', '3.13']
+        numpy-version: ['1.26', '2.2', 'dev']
         exclude:
-          - python-version: '3.8'
-            numpy-version: 'dev'
+          - python-version: '3.13'
+            numpy-version: '1.26'
 
     steps:
     - name: Checkout array-api-strict
@@ -38,7 +38,7 @@ jobs:
         if [[ "${{ matrix.numpy-version }}" == "dev" ]]; then
           python -m pip install --pre --extra-index https://pypi.anaconda.org/scientific-python-nightly-wheels/simple numpy;
         else
-          python -m pip install 'numpy>=1.26,<2.0';
+          python -m pip install 'numpy=='${{ matrix.numpy-version }};
         fi
         python -m pip install ${GITHUB_WORKSPACE}/array-api-strict
         python -m pip install -r ${GITHUB_WORKSPACE}/array-api-tests/requirements.txt

array_api_strict/_array_object.py

@@ -66,9 +66,6 @@ def __hash__(self):
 
 _default = object()
 
-# See https://github.com/data-apis/array-api-strict/issues/67 and the comment
-# on __array__ below.
-_allow_array = True
 
 class Array:
     """
@@ -157,26 +154,22 @@ def __repr__(self: Array, /) -> str:
     # This was implemented historically for compatibility, and removing it has
     # caused issues for some libraries (see
     # https://github.com/data-apis/array-api-strict/issues/67).
-    def __array__(self, dtype: None | np.dtype[Any] = None, copy: None | bool = None) -> npt.NDArray[Any]:
-        # We have to allow this to be internally enabled as there's no other
-        # easy way to parse a list of Array objects in asarray().
-        if _allow_array:
-            if self._device != CPU_DEVICE:
-                raise RuntimeError(f"Can not convert array on the '{self._device}' device to a Numpy array.")
-            # copy keyword is new in 2.0.0; for older versions don't use it
-            # retry without that keyword.
-            if np.__version__[0] < '2':
-                return np.asarray(self._array, dtype=dtype)
-            elif np.__version__.startswith('2.0.0-dev0'):
-                # Handle dev version for which we can't know based on version
-                # number whether or not the copy keyword is supported.
-                try:
-                    return np.asarray(self._array, dtype=dtype, copy=copy)
-                except TypeError:
-                    return np.asarray(self._array, dtype=dtype)
-            else:
-                return np.asarray(self._array, dtype=dtype, copy=copy)
-        raise ValueError("Conversion from an array_api_strict array to a NumPy ndarray is not supported")
+
+    # Instead of `__array__` we now implement the buffer protocol.
+    # Note that it makes array-apis-strict requiring python>=3.12
+    def __buffer__(self, flags):
+        if self._device != CPU_DEVICE:
+            raise RuntimeError(f"Can not convert array on the '{self._device}' device to a Numpy array.")
+        return memoryview(self._array)
+    def __release_buffer(self, buffer):
+        # XXX anything to do here?
+        pass
+
+    def __array__(self, *args, **kwds):
+        # a stub for python < 3.12; otherwise numpy silently produces object arrays
+        raise TypeError(
+            "Interoperation with NumPy requires python >= 3.12. Please upgrade."
+        )
 
     # These are various helper functions to make the array behavior match the
     # spec in places where it either deviates from or is more strict than

array_api_strict/_creation_functions.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-from contextlib import contextmanager
 from typing import TYPE_CHECKING, List, Optional, Tuple, Union
 
 if TYPE_CHECKING:
@@ -16,19 +15,6 @@
 
 import numpy as np
 
-@contextmanager
-def allow_array():
-    """
-    Temporarily enable Array.__array__. This is needed for np.array to parse
-    list of lists of Array objects.
-    """
-    from . import _array_object
-    original_value = _array_object._allow_array
-    try:
-        _array_object._allow_array = True
-        yield
-    finally:
-        _array_object._allow_array = original_value
 
 def _check_valid_dtype(dtype):
     # Note: Only spelling dtypes as the dtype objects is supported.
@@ -112,8 +98,8 @@ def asarray(
         # Give a better error message in this case. NumPy would convert this
         # to an object array. TODO: This won't handle large integers in lists.
         raise OverflowError("Integer out of bounds for array dtypes")
-    with allow_array():
-        res = np.array(obj, dtype=_np_dtype, copy=copy)
+
+    res = np.array(obj, dtype=_np_dtype, copy=copy)
     return Array._new(res, device=device)
 
 

array_api_strict/tests/test_array_object.py

@@ -1,3 +1,4 @@
+import sys
 import operator
 from builtins import all as all_
 
@@ -351,6 +352,10 @@ def test_array_properties():
     assert b.mT.shape == (3, 2)
 
 
+@pytest.mark.xfail(sys.version_info.major*100 + sys.version_info.minor < 312,
+                   reason="array conversion relies on buffer protocol, and "
+                          "requires python >= 3.12"
+)
 def test_array_conversion():
     # Check that arrays on the CPU device can be converted to NumPy
     # but arrays on other devices can't. Note this is testing the logic in
@@ -361,25 +366,23 @@ def test_array_conversion():
 
     for device in ("device1", "device2"):
         a = ones((2, 3), device=array_api_strict.Device(device))
-        with pytest.raises(RuntimeError, match="Can not convert array"):
+        with pytest.raises((RuntimeError, TypeError)):
             asarray([a])
 
-def test__array__():
-    # __array__ should work for now
+    # __buffer__ should work for now for conversion to numpy
     a = ones((2, 3))
-    np.array(a)
-
-    # Test the _allow_array private global flag for disabling it in the
-    # future.
-    from .. import _array_object
-    original_value = _array_object._allow_array
-    try:
-        _array_object._allow_array = False
-        a = ones((2, 3))
-        with pytest.raises(ValueError, match="Conversion from an array_api_strict array to a NumPy ndarray is not supported"):
-            np.array(a)
-    finally:
-        _array_object._allow_array = original_value
+    na = np.array(a)
+    assert na.shape == (2, 3)
+    assert na.dtype == np.float64
+
+@pytest.mark.skipif(not sys.version_info.major*100 + sys.version_info.minor < 312,
+                    reason="conversion to numpy errors out unless python >= 3.12"
+)
+def test_array_conversion_2():
+    a = ones((2, 3))
+    with pytest.raises(TypeError):
+        np.array(a)
+
 
 def test_allow_newaxis():
     a = ones(5)

array_api_strict/tests/test_creation_functions.py

@@ -1,3 +1,4 @@
+import sys
 import warnings
 
 from numpy.testing import assert_raises
@@ -97,7 +98,12 @@ def test_asarray_copy():
     a[0] = 0
     assert all(b[0] == 0)
 
-def test_asarray_list_of_lists():
+
+@pytest.mark.xfail(sys.version_info.major*100 + sys.version_info.minor < 312,
+                   reason="array conversion relies on buffer protocol, and "
+                          "requires python >= 3.12"
+)
+def test_asarray_list_of_arrays():
     a = asarray(1, dtype=int16)
     b = asarray([1], dtype=int16)
     res = asarray([a, a])