Bump numpy to 2.4.3, ase to 3.28.0, scipy to 1.17.1 and structuretoolkit to 0.0.41

[dependabot]

Bumps numpy from 2.3.5 to 2.4.0.

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

• c5ab79c Merge pull request #30487 from charris/prepare-2.4.0.2
• 05e379a REL: Prepare for the NumPy 2.4.0 release (2)
• 485f1c4 REL: Prepare for the NumPy 2.4.0 release (1) (#30486)
• c683481 REL: Prepare for the NumPy 2.4.0 release (#30439)
• 11d9ed2 Merge pull request #30459 from charris/backport-30456
• 2a17ddb TYP: restore generic.__hash__ (#30456)
• d04a429 Merge pull request #30432 from charris/backport-30426
• f94a148 fix more data races in mtrand.pyx (#30426)
• 06a9d42 Merge pull request #30420 from charris/backport-30418
• 30819cd Merge pull request #30419 from charris/backport-30373
• Additional commits viewable in compare view

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[Copilot]

Pull request overview

Updates pinned scientific Python and related parsing/tooling dependencies across packaging and conda environment definitions, aiming to keep runtime, docs, CI, and Binder environments in sync with newer upstream releases.

Changes:

• Bump core dependencies: numpy (2.3.5 → 2.4.3), ase (3.27.0 → 3.28.0), scipy (1.17.0 → 1.17.1).
• Bump optional tooling/libs: structuretoolkit (0.0.40 → 0.0.41), plus lammpsparser/vaspparser (0.0.1 → 0.0.2) where pinned.
• Update conda environments for Binder and CI/docs/lammps to reflect new pins (with one noted inconsistency).

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 2 comments.

Show a summary per file

File	Description
pyproject.toml	Updates pip dependency pins for core + optional extras (phonopy/lammps/vasp).
binder/environment.yml	Updates Binder conda environment pins to match the bumped dependencies.
.ci_support/environment.yml	Updates CI conda environment pins, but currently pins NumPy differently than other files.
.ci_support/environment-lammps.yml	Updates lammps CI environment to use lammpsparser 0.0.2.
.ci_support/environment-docs.yml	Updates docs conda environment pins to match bumped dependencies.

Comments suppressed due to low confidence (1)

pyproject.toml:54

• This PR also bumps lammpsparser and vaspparser (to 0.0.2), but those changes aren’t reflected in the PR title/description. Consider updating the PR metadata to mention these additional dependency bumps so the scope is clear.

    "pylammpsmpi==0.3.11",
    "jinja2==3.1.6",
    "pandas==2.3.3",
    "lammpsparser==0.0.2",
]

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[Copilot]

PR description/release notes text references bumping NumPy to 2.4.0, but this PR pins numpy==2.4.3. Please update the PR description (or align the pinned version) so reviewers and downstream automation aren’t misled about which version is being introduced.

[jan-janssen]

      The following packages are incompatible
      ├─ ase =3.28.0 * is requested and can be installed;
      └─ sphinx_parser =0.1.6 * is not installable because it requires
         └─ ase >=3.23.0,<3.28.0 *, which conflicts with any installable versions