`numpy.__array_namespace_info__().dtypes()["float64"] == None` is `True` but `numpy.float64 == None` is `False`

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#359 opened on Nov 2, 2025 2 comments 0 reactions 0 assignees View on GitHub

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Assessment

Difficulty: 3/5
Estimated time: 1-2 days
Newbie friendliness: 35/100

Issue type: Bug
Clarity: Mostly clear
Activity status: Stale
Tech stack: numpy, python
Domain: data

Research direction

Start by reproducing the discrepancy with array_api_compat.numpy.array_namespace_info().dtypes()["float64"] and np.float64, then compare the behavior with the Array API specification linked in the issue. Done means resolving the inconsistent comparison behavior for the NumPy backend and covering the reported case with an appropriate test.

Written by the indexing model from the issue text.

Description

In my understanding, dtype can be any Python object in array API specification, and therefore may be None depending on the library. If the device is somewhat set to None while using numpy backend in array API compatible code, the above specification (https://github.com/numpy/numpy/issues/18434) causes various problems when working with dtypes.

> from array_api_compat import numpy as np
> np.__array_namespace_info__().dtypes()["float64"]
dtype('float64')
> np.float64
<class 'numpy.float64'>
> np.__array_namespace_info__().dtypes()["float64"] == np.float64
True
> np.__array_namespace_info__().dtypes()["float64"] == None
True
> np.float64 == None
False

Dominant language: Python
Stars: 131
Forks: 49
Avg merge: 2d 8h
Merged PRs (30d): 6

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