@asmeurer noted in #110 (comment) that NumPy proper (i.e. numpy, as opposed to numpy.array_api) wasn't working with the test suite due to the following code. The problem was that the dtype attribute of NumPy-proper arrays were being used in conjuction with namespaced dtypes—these two are different objects, and thus have different hashes so they look like different keys in a dict.

>>> import numpy as np
>>> dtypes_map = {np.int64: "foo"}
>>> dtypes_map[np.asarray(0).dtype]
KeyError

This behaviour is isn't specifically ruled out in the spec, as the spec only says dtypes need equality, which NumPy-proper does conform to.

>>> np.asarray(0).dtype == np.int64
True

So the test suite should phase out assumptions of namespaced dtypes and array dtypes sharing the same hash, instead relying on equality.