Bump the python-dependencies group with 4 updates

[dependabot]

Updates the requirements on numpy, scipy, cvxpy and pytest to permit the latest version.
Updates numpy to 2.5.0

Release notes

Sourced from numpy's releases.

v2.5.0 (June 21, 2026)

NumPy 2.5.0 Release Notes

Numpy 2.5.0 is a transitional release. It drops support for Python 3.11, marking the end of distutils, and expires a large number of deprecations made in the 2.0.x release. It also improves free threading and brings sorting into compliance with the array-api standard with the addition of descending sorts. There is also a fair amount of preparation for Python 3.15, which will be supported starting with the first rc.

This release supports Python versions 3.12-3.14.

Highlights

• Distutils has been removed,
• Many expired deprecations, see below,
• Many new deprecations, see below,
• Many static typing improvements.
• Improved support for free threading,
• Support for descending sorts,

See New Features below for other additions.

Deprecations

• numpy.char.chararray is deprecated. Use an ndarray with a string or bytes dtype instead.

  (gh-30605)

• numpy.take now correctly checks if the result can be cast to the provided out=out under the same-kind rule. A DeprecationWarning is given now when this check fails. Previously, take incorrectly checked if out could be cast to the result (the wrong direction). This deprecation also affects compress and possibly other functions. (Future versions of NumPy may tighten the casting check further.)

  (gh-30615)

• The numpy.char.[as]array functions are deprecated. Use an numpy.[as]array with a string or bytes dtype instead.

  (gh-30802)

• Setting the dtype attribute is deprecated because mutating an array is unsafe if an array is shared, especially by multiple threads. As an alternative, you can create a view with a new dtype via array.view(dtype=new_dtype).

  (gh-29244)

... (truncated)

Changelog

Sourced from numpy's changelog.

This is a walkthrough of the NumPy 2.4.0 release on Linux, which will be the first feature release using the numpy/numpy-release <https://github.com/numpy/numpy-release>__ repository.

The commands can be copied into the command line, but be sure to replace 2.4.0 with the correct version. This should be read together with the :ref:general release guide <prepare_release>.

Facility preparation

Before beginning to make a release, use the requirements/*_requirements.txt files to ensure that you have the needed software. Most software can be installed with pip, but some will require apt-get, dnf, or whatever your system uses for software. You will also need a GitHub personal access token (PAT) to push the documentation. There are a few ways to streamline things:

• Git can be set up to use a keyring to store your GitHub personal access token. Search online for the details.

Prior to release

Add/drop Python versions

When adding or dropping Python versions, multiple config and CI files need to be edited in addition to changing the minimum version in pyproject.toml. Make these changes in an ordinary PR against main and backport if necessary. We currently release wheels for new Python versions after the first Python RC once manylinux and cibuildwheel support that new Python version.

Backport pull requests

Changes that have been marked for this release must be backported to the maintenance/2.4.x branch.

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

... (truncated)

Commits

• 6910b28 Merge pull request #31706 from charris/prepare-2.5.0-release
• e0acd2b REL: Prepare for the NumPy 2.5.0 release.
• 8d928b7 Merge pull request #31704 from charris/backport-31649
• c2055ba MAINT: update openblas to 0.3.33.112.0 (#31649)
• ce17c81 Merge pull request #31703 from charris/backport-31609
• 3de6203 BUG: fix StringDType distinct-allocator bugs and add tests (#31609)
• c723971 Merge pull request #31700 from charris/backport-31694
• 64513b2 MAINT: Bump pypa/cibuildwheel from 3.4.1 to 4.1.0
• 04707f0 Merge pull request #31698 from charris/try-fix-emscripten
• 5cf0686 MAINT: Try to fix emscripten wheel build.
• Additional commits viewable in compare view

Updates scipy to 1.18.0

Release notes

Sourced from scipy's releases.

SciPy 1.18.0 Release Notes

SciPy 1.18.0 is the culmination of 6 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been a number of deprecations and API changes in this release, which are documented below. All users are encouraged to upgrade to this release, as there are a large number of bug-fixes and optimizations. Before upgrading, we recommend that users check that their own code does not use deprecated SciPy functionality (to do so, run your code with python -Wd and check for DeprecationWarning s). Our development attention will now shift to bug-fix releases on the 1.18.x branch, and on adding new features on the main branch.

This release requires Python 3.12-3.14 and NumPy 2.0.0 or greater.

Highlights of this release

• SciPy now supports three different build modes for BLAS and LAPACK LP64/ILP64 support, and machinery is provided for downstream cython_lapack consumers to gracefully handle LP64/ILP64 backend builds. ILP64 support has been substantially improved across the SciPy library.
• Remaining Fortran to C translations have been completed---an experimental Fortran-free build option is now available to developers for testing purposes. Developer feedback is welcome on Fortran-free builds.
• scipy.signal.whittaker_henderson now provides access to Whittaker-Henderson smoothing of a discrete signal.
• A large number of scipy.stats functions now support lazy arrays and JAX JIT. Array API support has been improved substantially in SciPy, with at least 21 functions gaining new support in this release. 16 scipy.stats functions have also gained support for MArray input.

New features

scipy.fft improvements

• SciPy's internal FFT backend has switched from pocketfft to its successor package ducc0.fft, which features several incremental improvements. The most significant of those from SciPy's perspective is probably that storage requirements for internally cached plans have been significantly reduced for most long 1D transforms. Plans that require more storage than 1MB will no longer be cached; this mainly affects huge 1D transforms of prime and near-prime sizes.

scipy.interpolate improvements

... (truncated)

Commits

• 54ef542 REL: 1.18.0 release commit
• a45e463 Merge pull request #25395 from tylerjereddy/treddy_prep_1.18.0_final
• ee2442e TYP, MAINT, TST: PR 25395 revisions
• 3225154 DOC: PR 25395 revisions
• 14c7bd7 TYP: Fix mypy errors with pytest==9.1.0 (#25410)
• 71522e9 DOC: revise SciPy 1.18.0 release notes
• 92f8482 MAINT: fix errors from pytest 9.1 (#25378)
• 7b27bf4 TST, MAINT: modernize spatial tests for pytest 10 (#25376)
• d05b640 Merge pull request #25347 from tylerjereddy/treddy_version_bump_1.18.0rc3
• e60fe8b REL: set to 1.18.0rc3 unreleased
• Additional commits viewable in compare view

Updates cvxpy to 1.9.2

Commits

• 7cb26d3 Release v1.9.2
• bcad203 Patch/1.9.2
• fac9f6f CI: install Moreau from PyPI instead of private Fury index
• a89e5cf Fix N-D parametric matmul in the COO and SCIPY canonicalization backends (#3401)
• c6ac6c7 Add missing numpy_numeric decorator to entr.numeric (#3379)
• 6ba794a Fix scrambled ExpCone duals for matrix-shaped arguments (#3377)
• eeddbb7 fix cone head lb (#3364)
• 20ae79d Dedup identical subtrees in Dcp2Cone canonicalization (#3355)
• eeb13c3 Updates to the wishlist (#3421)
• 951e8b8 Fix factor-2 error in Hermitian PSD constraint dual recovery (#3388)
• Additional commits viewable in compare view

Updates pytest to 9.1.1

Release notes

Sourced from pytest's releases.

9.1.1

pytest 9.1.1 (2026-06-19)

Bug fixes

• #14220: Fixed a logic bug in pytest.RaisesGroup which would might cause it to display incorrect "It matches FooError() which was paired with BarError" messages.
• #14591: Fixed a regression in pytest 9.1.0 which caused overriding a parametrized fixture with an indirect @​pytest.mark.parametrize to fail with "duplicate parametrization of '<fixture name>'".
• #14606: Fixed list-item typing errors from mypy in @pytest.mark.parametrize <pytest.mark.parametrize ref> argvalues parameter.
• #14608: Fixed a regression in pytest 9.1.0 where conftest.py files located in <invocation dir>/test* were no longer loaded as initial conftests when invoked without arguments. This could cause certain hooks (like pytest_addoption) in these files to not fire.

Commits

• cf470ec Prepare release version 9.1.1
• e0c8ce6 Merge pull request #14625 from pytest-dev/patchback/backports/9.1.x/a07c31a97...
• 1b82d16 Merge pull request #14624 from pytest-dev/patchback/backports/9.1.x/b375b79ec...
• 501c4bc Merge pull request #14596 from bluetech/doc-classmethod
• b61f588 Merge pull request #14622 from chrisburr/fix-14608-initial-conftest-test-subdir
• 9a567e0 [automated] Update plugin list (#14617) (#14618)
• ef8b299 Merge pull request #14620 from pytest-dev/patchback/backports/9.1.x/680f9f3ed...
• 66abd07 Merge pull request #14220 from bysiber/fix-stale-iexp-raisesgroup
• 79fbf93 Merge pull request #14612 from pytest-dev/patchback/backports/9.1.x/974ed48b6...
• 0d312eb Merge pull request #14611 from bluetech/parametrize-argvalues-typing
• Additional commits viewable in compare view

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[dependabot]

Looks like these dependencies are updatable in another way, so this is no longer needed.