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@dependabot dependabot bot commented on behalf of github Dec 22, 2025

Updates the requirements on numpy to permit the latest version.

Release notes

Sourced from numpy's releases.

2.4.0 (Dec 20, 2025)

NumPy 2.4.0 Release Notes

The NumPy 2.4.0 release continues the work to improve free threaded Python support, user dtypes implementation, and annotations. There are many expired deprecations and bug fixes as well.

This release supports Python versions 3.11-3.14

Highlights

Apart from annotations and same_value kwarg, the 2.4 highlights are mostly of interest to downstream developers. They should help in implementing new user dtypes.

  • Many annotation improvements. In particular, runtime signature introspection.
  • New casting kwarg 'same_value' for casting by value.
  • New PyUFunc_AddLoopsFromSpec function that can be used to add user sort loops using the ArrayMethod API.
  • New __numpy_dtype__ protocol.

Deprecations

Setting the strides attribute is deprecated

Setting the strides attribute is now deprecated since mutating an array is unsafe if an array is shared, especially by multiple threads. As an alternative, you can create a new view (no copy) via:

  • np.lib.stride_tricks.strided_window_view if applicable,
  • np.lib.stride_tricks.as_strided for the general case,
  • or the np.ndarray constructor (buffer is the original array) for a light-weight version.

(gh-28925)

Positional out argument to np.maximum, np.minimum is deprecated

Passing the output array out positionally to numpy.maximum and numpy.minimum is deprecated. For example, np.maximum(a, b, c) will emit a deprecation warning, since c is treated as the output buffer rather than a third input.

Always pass the output with the keyword form, e.g. np.maximum(a, b, out=c). This makes intent clear and simplifies type annotations.

(gh-29052)

align= must be passed as boolean to np.dtype()

... (truncated)

Changelog

Sourced from numpy's changelog.

Update 2.4.0 milestones

Look at the issues/prs with 2.4.0 milestones and either push them off to a later version, or maybe remove the milestone. You may need to add a milestone.

Check the numpy-release repo

The things to check are the cibuildwheel version in .github/workflows/wheels.yml and the openblas versions in openblas_requirements.txt.

Make a release PR

Four documents usually need to be updated or created for the release PR:

  • The changelog
  • The release notes
  • The .mailmap file
  • The pyproject.toml file

These changes should be made in an ordinary PR against the maintenance branch. Other small, miscellaneous fixes may be part of this PR. The commit message might be something like::

REL: Prepare for the NumPy 2.4.0 release
  • Create 2.4.0-changelog.rst.
  • Update 2.4.0-notes.rst.
  • Update .mailmap.
  • Update pyproject.toml

Set the release version

Check the pyproject.toml file and set the release version and update the classifier if needed::

$ gvim pyproject.toml

Check the doc/source/release.rst file

make sure that the release notes have an entry in the release.rst file::

... (truncated)

Commits

Most Recent Ignore Conditions Applied to This Pull Request
Dependency Name Ignore Conditions
numpy [>= 1.26.a, < 1.27]

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Updates the requirements on [numpy](https://github.com/numpy/numpy) to permit the latest version.
- [Release notes](https://github.com/numpy/numpy/releases)
- [Changelog](https://github.com/numpy/numpy/blob/main/doc/RELEASE_WALKTHROUGH.rst)
- [Commits](numpy/numpy@v2.3.4...v2.4.0)

---
updated-dependencies:
- dependency-name: numpy
  dependency-version: 2.4.0
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update Python code labels Dec 22, 2025
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