Make numpy.array_api dtypes issue a warning when compared against numpy dtypes

This is to prevent user error, since something like numpy.array_api.float32 ==
numpy.float32 gives False.

Original NumPy Commit: 595342c933b5db00a9baddbc142676448ffe8228

Author: asmeurer

array_api_strict/_dtypes.py

@@ -1,3 +1,5 @@
+import warnings
+
 import numpy as np
 
 # Note: we wrap the NumPy dtype objects in a bare class, so that none of the
@@ -12,6 +14,15 @@ def __repr__(self):
         return f"np.array_api.{self._np_dtype.name}"
 
     def __eq__(self, other):
+        # See https://github.com/numpy/numpy/pull/25370/files#r1423259515.
+        # Avoid the user error of array_api_strict.float32 == numpy.float32,
+        # which gives False. Making == error is probably too egregious, so
+        # warn instead.
+        if isinstance(other, np.dtype) or (isinstance(other, type) and issubclass(other, np.generic)):
+            warnings.warn("""You are comparing a array_api_strict dtype against \
+a NumPy native dtype object, but you probably don't want to do this. \
+array_api_strict dtype objects compare unequal to their NumPy equivalents. Such \
+cross-library comparison is not supported by the standard.""")
         if not isinstance(other, _DType):
             return NotImplemented
         return self._np_dtype == other._np_dtype

array_api_strict/tests/test_creation_functions.py

@@ -1,3 +1,5 @@
+import warnings
+
 from numpy.testing import assert_raises
 import numpy as np
 
@@ -25,7 +27,11 @@ def test_asarray_errors():
     # Test various protections against incorrect usage
     assert_raises(TypeError, lambda: Array([1]))
     assert_raises(TypeError, lambda: asarray(["a"]))
-    assert_raises(ValueError, lambda: asarray([1.0], dtype=np.float16))
+    with assert_raises(ValueError), warnings.catch_warnings(record=True) as w:
+        warnings.simplefilter("always")
+        asarray([1.0], dtype=np.float16)
+        assert len(w) == 1
+        assert issubclass(w[-1].category, UserWarning)
     assert_raises(OverflowError, lambda: asarray(2**100))
     # Preferably this would be OverflowError
     # assert_raises(OverflowError, lambda: asarray([2**100]))

array_api_strict/tests/test_data_type_functions.py

@@ -1,3 +1,5 @@
+import warnings
+
 import pytest
 
 from numpy.testing import assert_raises
@@ -24,7 +26,15 @@ def test_isdtype_strictness():
     assert_raises(ValueError, lambda: xp.isdtype(xp.float64, 'f8'))
 
     assert_raises(TypeError, lambda: xp.isdtype(xp.float64, (('integral',),)))
-    assert_raises(TypeError, lambda: xp.isdtype(xp.float64, np.object_))
+    with assert_raises(TypeError), warnings.catch_warnings(record=True) as w:
+        warnings.simplefilter("always")
+        xp.isdtype(xp.float64, np.object_)
+        assert len(w) == 1
+        assert issubclass(w[-1].category, UserWarning)
 
     assert_raises(TypeError, lambda: xp.isdtype(xp.float64, None))
-    assert_raises(TypeError, lambda: xp.isdtype(xp.float64, np.float64))
+    with assert_raises(TypeError), warnings.catch_warnings(record=True) as w:
+        warnings.simplefilter("always")
+        xp.isdtype(xp.float64, np.float64)
+        assert len(w) == 1
+        assert issubclass(w[-1].category, UserWarning)