Reinstate __array__ on Python 3.10/3.11

Author: crusaderky

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

@@ -11,12 +11,16 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.12', '3.13']
-        numpy-version: ['1.26', '2.2', 'dev']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
+        numpy-version: ['1.26', '2.3', 'dev']
         exclude:
+          - python-version: '3.10'
+            numpy-version: '2.3'
+          - python-version: '3.10'
+            numpy-version: 'dev'            
           - python-version: '3.13'
             numpy-version: '1.26'
-
+      fail-fast: false
     steps:
     - name: Checkout array-api-strict
       uses: actions/checkout@v4

.github/workflows/tests.yml

@@ -6,11 +6,15 @@ jobs:
     strategy:
       matrix:
         python-version: ['3.10', '3.11', '3.12', '3.13']
-        numpy-version: ['1.26', 'dev']
+        numpy-version: ['1.26', '2.3', 'dev']
         exclude:
+          - python-version: '3.10'
+            numpy-version: '2.3'
+          - python-version: '3.10'
+            numpy-version: 'dev'            
           - python-version: '3.13'
             numpy-version: '1.26'
-      fail-fast: true
+      fail-fast: false
     steps:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v5

array_api_strict/_array_object.py

@@ -16,6 +16,7 @@
 from __future__ import annotations
 
 import operator
+import sys
 from collections.abc import Iterator
 from enum import IntEnum
 from types import EllipsisType, ModuleType
@@ -67,8 +68,6 @@ def __hash__(self) -> int:
 CPU_DEVICE = Device()
 ALL_DEVICES = (CPU_DEVICE, Device("device1"), Device("device2"))
 
-_default = object()
-
 
 class Array:
     """
@@ -149,29 +148,40 @@ def __repr__(self) -> str:
 
     __str__ = __repr__
 
-    # `__array__` 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).
-
-    # 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.")
+            raise RuntimeError(
+                # NumPy swallows this exception and falls back to __array__.
+                f"Can't extract host buffer from array on the '{self._device}' device."
+            )
         return self._array.__buffer__(flags)
 
-    # We do not define __release_buffer__, per the discussion at
-    # https://github.com/data-apis/array-api-strict/pull/115#pullrequestreview-2917178729
-
-    def __array__(self, *args, **kwds):
-        # a stub for python < 3.12; otherwise numpy silently produces object arrays
-        import sys
-        minor, major = sys.version_info.minor, sys.version_info.major
-        if major < 3 or minor < 12:
+    # `__array__` is not part of the Array API. Ideally we want to support
+    # `xp.asarray(Array)` exclusively through the __buffer__ protocol; however this is
+    # only possible on Python >=3.12. Additionally, when __buffer__ raises (e.g. because
+    # the array is not on the CPU device, NumPy will try to fall back on __array__ but,
+    # if that doesn't exist, create a scalar numpy array of objects which contains the
+    # array_api_strict.Array. So we can't get rid of __array__ entirely.
+    def __array__(
+        self, dtype: None | np.dtype[Any] = None, copy: None | bool = None
+    ) -> npt.NDArray[Any]:
+        if self._device != CPU_DEVICE:
+            # We arrive here from np.asarray() on Python >=3.12 when __buffer__ raises.
+            raise RuntimeError(
+                f"Can't convert array on the '{self._device}' device to a "
+                "NumPy array."
+            )
+        if sys.version_info >= (3, 12):
             raise TypeError(
-                "Interoperation with NumPy requires python >= 3.12. Please upgrade."
+                "The __array__ method is not supported by the Array API. "
+                "Please use the __buffer__ interface instead."
             )
 
+        # copy keyword is new in 2.0
+        if np.__version__[0] < '2':
+            return np.asarray(self._array, dtype=dtype)
+        return np.asarray(self._array, dtype=dtype, copy=copy)
+
     # 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
     # NumPy behavior

array_api_strict/tests/test_array_object.py

@@ -559,36 +559,54 @@ 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
-    # __array__, which is only used in asarray when converting lists of
-    # arrays.
+    # __array__ on Python 3.10~3.11 and in __buffer__ on Python >=3.12.
     a = ones((2, 3))
-    np.asarray(a)
+    na = np.asarray(a)
+    assert na.shape == (2, 3)
+    assert na.dtype == np.float64
+    na[0, 0] = 10
+    assert a[0, 0] == 10  # return view when possible
+
+    a = arange(5, dtype=uint8)
+    na = np.asarray(a)
+    assert na.dtype == np.uint8
 
     for device in ("device1", "device2"):
         a = ones((2, 3), device=array_api_strict.Device(device))
-        with pytest.raises((RuntimeError, ValueError)):
+        with pytest.raises(RuntimeError, match=device):
             np.asarray(a)
 
-    # __buffer__ should work for now for conversion to numpy
-    a = ones((2, 3))
-    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"
+@pytest.mark.skipif(np.__version__ < "2", reason="np.asarray has no copy kwarg")
+def test_array_conversion_copy():
+    a = arange(5)
+    na = np.asarray(a, copy=False)
+    na[0] = 10
+    assert a[0] == 10
+
+    a = arange(5)
+    na = np.asarray(a, copy=True)
+    na[0] = 10
+    assert a[0] == 0
+
+    a = arange(5)
+    with pytest.raises(ValueError):
+        np.asarray(a, dtype=np.uint8, copy=False)
+
+
+@pytest.mark.skipif(
+    sys.version_info < (3, 12), reason="Python <3.12 has no __buffer__ interface"
 )
-def test_array_conversion_2():
+def test_no_array_interface():
+    """When the __buffer__ interface is available, the __array__ interface is not."""
     a = ones((2, 3))
-    with pytest.raises(TypeError):
-        np.array(a)
+    with pytest.raises(TypeError, match="not supported"):
+        # Because NumPy prefers __buffer__ when available, we can't trigger this
+        # exception from np.asarray().
+        a.__array__()
 
 
 def test_allow_newaxis():

docs/changelog.md

@@ -1,5 +1,34 @@
 # Changelog
 
+## 2.4.1 (unreleased)
+
+### Major Changes
+
+- The array object defines `__array__` again when `__buffer__` is not available.
+
+- Support for Python versions 3.10 and 3.11 has been reinstated.
+
+
+### Minor Changes
+
+- Fix bug in `np.asarray(a)`, where `a` is a `array_api_strict.Array` on a device
+  that is not CPU_DEVICE, which caused NumPy to return a scalar object array wrapping
+  around the whole Array instead of raising.
+
+- Arithmetic operations no longer accept NumPy arrays.
+
+- Disallow `__setitem__` for invalid dtype combinations (e.g. setting a float value
+into an integer array)
+
+
+### Contributors
+
+The following users contributed to this release:
+
+Evgeni Burovski,
+Guido Imperiale
+
+
 ## 2.4.0 (2025-06-16)
 
 ### Major Changes