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Updates the requirements on numpy, scipy, matplotlib, pandas, scikit-learn, scikit-image, statsmodels and jupyter-book to permit the latest version.
Updates numpy from 2.2.5 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

Updates scipy from 1.15.2 to 1.16.3

Release notes

Sourced from scipy's releases.

SciPy 1.16.3 Release Notes

SciPy 1.16.3 is a bug-fix release with no new features compared to 1.16.2.

Authors

  • Name (commits)
  • ChrisAB (1) +
  • Lucas Colley (1)
  • Ralf Gommers (3)
  • Matt Haberland (8)
  • Nick ODell (2)
  • Ilhan Polat (1)
  • Tyler Reddy (28)
  • Lucas Roberts (2)

A total of 8 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete.

The full issue and pull request lists, and the release asset hashes are available in the associated README.txt file.

SciPy 1.16.2 Release Notes

SciPy 1.16.2 is a bug-fix release with no new features compared to 1.16.1. This is the first stable release of SciPy to provide Windows on ARM wheels on PyPI.

Authors

  • Name (commits)
  • Dietrich Brunn (1)
  • Ralf Gommers (6)
  • Adam Jones (1)
  • Gleb Khmyznikov (1) +
  • Jost Migenda (1) +
  • newyork_loki (1)
  • Nick ODell (3)
  • Dimitri Papadopoulos Orfanos (1)
  • Ilhan Polat (2)
  • Tyler Reddy (26)
  • Mugunthan Selvanayagam (1) +
  • Shuhei Watanabe (1) +

A total of 12 people contributed to this release.

... (truncated)

Commits
  • b9105cc REL: 1.16.3 rel commit [wheel build]
  • 4b7699c Merge pull request #23805 from tylerjereddy/treddy_backports_1.16.3
  • 874b75b MAINT: PR 23805 wheel builds [wheel build]
  • de06a58 DOC: PR 23805 revisions
  • f642304 TST: linalg.svd: skip on 32-bit due to limited memory
  • df47908 CI: PR 23805 revisions
  • f584063 TST: stats.boxcox_llf: bump test tolerance for Accelerate (#23864)
  • fc60b2f DOC: PR 23805 revisions
  • 0dd12ec BLD: stats.multivariate_normal: silence pythran build warning
  • d3b1e62 Revert "BLD: stats.multivariate_normal: suppress pythran build warning"
  • Additional commits viewable in compare view

Updates matplotlib from 3.10.1 to 3.10.8

Release notes

Sourced from matplotlib's releases.

REL: v3.10.8

This is a bugfix release in the 3.10.x series.

The primary highlights of this release are:

  • Properly allow freethreaded mode in the MacOS backend
  • Better error handling for MacOS backend

REL: v3.10.7

This is the latest bugfix release in the 3.10.x series.

The most important update in this release is that the minimum version of pyparsing has been updated to version 3.0.

REL: v3.10.6

This is a bugfix release in the 3.10.x series.

Highlights from this release include:

- Fix regression of hi-dpi support for Qt
- Fix race condition in TexManager.make_dvi & make_png
- Various documentation and other bugfixes

REL: v3.10.5

This is the fourth bugfix release of the 3.10.x series.

Included in this release is distributed wheels for Python 3.14 (including freethreaded) and Windows ARM.

There are also several smaller bugfixes.

REL: v3.10.3

This is the third bugfix release of the 3.10.x series

Commits
  • 1392cbe REL: v3.10.8
  • 0b9ebb3 Doc release prep v3.10.8
  • bc7b5c4 Merge branch 'v3.10.7-doc' into v3.10.x
  • 86b38d3 Github stats v3.10.8
  • 9512188 Merge pull request #30717 from meeseeksmachine/auto-backport-of-pr-30714-on-v...
  • d300769 Backport PR #30714: FIX: Gracefully handle numpy arrays as input to check_in_...
  • 799bc95 Merge pull request #30711 from ngoldbaum/v3.10.x
  • 134000b Merge pull request #30697 from ngoldbaum/fix-plotting-on-worker-threads
  • 5b8e219 TST: Run macosx backends in a subprocess
  • 878e71a Backport PR #29810: Declare free-threaded support in MacOS backend extension ...
  • Additional commits viewable in compare view

Updates pandas from 2.2.3 to 2.3.3

Release notes

Sourced from pandas's releases.

Pandas 2.3.3

We are pleased to announce the release of pandas 2.3.3. This release includes some improvements and fixes to the future string data type (preview feature for the upcoming pandas 3.0). We recommend that all users upgrade to this version.

See the full whatsnew for a list of all the changes. Pandas 2.3.3 supports Python 3.9 and higher, and is the first release to support Python 3.14.

The release will be available on the conda-forge channel:

conda install pandas --channel conda-forge

Or via PyPI:

python3 -m pip install --upgrade pandas

Please report any issues with the release on the pandas issue tracker.

Thanks to all the contributors who made this release possible.

Pandas 2.3.2

We are pleased to announce the release of pandas 2.3.2. This release includes some improvements and fixes to the future string data type (preview feature for the upcoming pandas 3.0). We recommend that all users upgrade to this version.

See the full whatsnew for a list of all the changes. Pandas 2.3.2 supports Python 3.9 and higher.

The release will be available on the conda-forge channel:

conda install pandas --channel conda-forge

Or via PyPI:

python3 -m pip install --upgrade pandas

Please report any issues with the release on the pandas issue tracker.

Thanks to all the contributors who made this release possible.

Pandas 2.3.1

We are pleased to announce the release of pandas 2.3.1. This release includes some improvements and fixes to the future string data type (preview feature for the upcoming pandas 3.0). We recommend that all users upgrade to this version.

See the full whatsnew for a list of all the changes. Pandas 2.3.1 supports Python 3.9 and higher.

The release will be available on the conda-forge channel:

conda install pandas --channel conda-forge

Or via PyPI:

... (truncated)

Commits
  • 9c8bc3e RLS: 2.3.3
  • 6aa788a [backport 2.3.x] DOC: prepare 2.3.3 whatsnew notes for release (#62499) (#62508)
  • b64f0df [backport 2.3.x] BUG: avoid validation error for ufunc with string[python] ar...
  • 058eb2b [backport 2.3.x] BUG: String[pyarrow] comparison with mixed object (#62424) (...
  • 2ca088d [backport 2.3.x] DEPR: remove the Period resampling deprecation (#62480) (#62...
  • 92bf98f [backport 2.3.x] BUG: fix .str.isdigit to honor unicode superscript for older...
  • e57c7d6 Backport PR #62452 on branch 2.3.x (TST: Adjust tests for numexpr 2.13) (#62454)
  • e0fe9a0 Backport to 2.3.x: REGR: from_records not initializing subclasses properly (#...
  • 23a1085 BUG: improve future warning for boolean operations with missaligned indexes (...
  • 6113696 Backport PR #62396 on branch 2.3.x (PKG/DOC: indicate Python 3.14 support in ...
  • Additional commits viewable in compare view

Updates scikit-learn from 1.6.1 to 1.8.0

Release notes

Sourced from scikit-learn's releases.

Release 1.8.0

We're happy to announce the 1.8.0 release.

You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_8_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v1.8.html

This version supports Python versions 3.11 to 3.14 and features support of free-threaded CPython.

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds can be installed using:

conda install -c conda-forge scikit-learn

Scikit-learn 1.7.2

We're happy to announce the 1.7.2 release.

This release contains a few bug fixes and is the first version supporting Python 3.14.

You can see the changelog here: https://scikit-learn.org/stable/whats_new/v1.7.html#version-1-7-2

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds can be installed using:

conda install -c conda-forge scikit-learn

Thanks to everyone who contributed to this release !

Scikit-learn 1.7.1

We're happy to announce the 1.7.1 release.

This release contains fixes for a few regressions introduced in 1.7.

You can see the changelog here: https://scikit-learn.org/stable/whats_new/v1.7.html#version-1-7-1

You can upgrade with pip as usual:

</tr></table>

... (truncated)

Commits
  • 646da0f [cd build]
  • 4f4f283 Generate changelog
  • 967dcde Set version
  • cb1424b DOC Release highlights for 1.8 (#32809)
  • 5645b27 🔒 🤖 CI Update lock files for main CI build(s) 🔒 🤖 (#32859)
  • 6b9fb11 🔒 🤖 CI Update lock files for free-threaded CI build(s) 🔒 :rob...
  • a0f6d88 🔒 🤖 CI Update lock files for array-api CI build(s) 🔒 🤖 ...
  • c1de8fc FIX Make get_namespace handle pandas dataframe input (#32838)
  • 764249a Fix _safe_indexing with non integer arrays on array API inputs (#32840)
  • eca5e0a FIX Add new default max_samples=None in Bagging estimators (#32825)
  • Additional commits viewable in compare view

Updates scikit-image from 0.25.2 to 0.26.0

Release notes

Sourced from scikit-image's releases.

v0.26.0

scikit-image 0.26.0

We're happy to announce the release of scikit-image 0.26.0!

New Features

  • Add new parameter max_step_cost to skimage.graph.MCP.find_costs which allows limiting the maximal stepping cost between points (#7625).
  • In skimage.transform, add the identity class constructor to all geometric transforms. For example, you can now use skimage.transform.PolynomialTransform(dimensionality=2) (#7754).
  • Add new property intensity_median to skimage.measure.regionprops (#7745).
  • binary_blobs now supports a mode parameter for the Gaussian filter, allowing periodic boundary conditions with mode="wrap" (#7909).

API Changes

  • In skimage.morphology, deprecate binary_erosion, binary_dilation, binary_opening, and binary_closing in favor of erosion, dilation, opening, and closing respectively. The binary versions weren't actually significantly faster than their non-binary counterparts and sometimes significantly slower. In the future, we might add optimizations internally to the remaining (general, non-binary) functions for when they're used with binary inputs (#7665).
  • Deprecate parameter max_cost in skimage.graph.MCP.find_costs which previously did nothing. Use the new parameter max_step_cost instead (#7625).
  • Deprecate parameter max_cumulative_cost in skimage.graph.MCP.find_costs which did nothing (#7625).
  • In skimage.morphology.remove_small_objects, deprecate the min_size parameter in favor of the new max_size parameter to make API and behavior clearer. This new threshold removes objects smaller than or equal to its value, while the previous parameter only removed smaller ones (#7739).
  • In skimage.morphology.remove_small_holes, deprecate the area_threshold parameter in favor of the new max_size parameter to make API and behavior clearer. This new threshold removes holes smaller than or equal to its value, while the previous parameter only removed smaller ones (#7739).
  • In skimage.transform, deprecate the use of scalar scale, with dimensionality=3 where this can be passed to a geometric transform contructor. This allows us to generalize the use of the constructors to the case where the parameters must specify the dimensionality, unless you mean to construct an identity transform (#7754).
  • In skimage.transform, turn all input parameters to transform constructors keyword-only (other than matrix). This avoids confusion due to the positional parameter order being different from the order by which they are applied in AffineTransform (#7754).
  • Deprecate parameter num_threads in skimage.restoration.rolling_ball; use workers instead (#7302).
  • Deprecate parameter num_workers in skimage.restoration.cycle_spin; use workers instead (#7302).
  • Officially deprecate old properties in skimage.measure.regionprops and related functions. While we removed the documentation for these some time ago, they where still accessible as keys (via __get_item__) or attributes. Going forward, using deprecated keys or attributes, will emit an appropriate warning (#7778).
  • In skimage.measure, add a new class method and constructor from_estimate for LineModelND, CircleModel, and EllipseModel. This replaces the old API—the now deprecated estimate method—which required initalizing a model with undefined parameters before calling estimate (#7771).
  • In skimage.transform, add a new class method and constructor from_estimate for AffineTransform, EssentialMatrixTransform, EuclideanTransform, FundamentalMatrixTransform, PiecewiseAffineTransform, PolynomialTransform, ProjectiveTransform, SimilarityTransform, and ThinPlateSplineTransform. This replaces the old API—the now deprecated estimate method—which required initializing an undefined transform before calling estimate (#7771).
  • Deprecate skimage.measure.fit.BaseModel; after we expire the other *Model* deprecations, there is no work for an ancestor class to do (#7789).
  • In skimage.measure, deprecate .params attributes of the models CircleModel, EllipseModel, and LineModelND. Instead set model-specific attributes: origin, direction for LineModelND; center, radius for CircleModel, center, ax_lens, theta for EllipseModel (#7789).
  • In skimage.measure, deprecate use of model constructor calls without arguments leaving an uninitialized instance (for example CircleModel()). This applies to CircleModel, EllipseModel, and LineModelND. Instead prefer input arguments to define instances (for example CircleModel(center, radius)). This follows on from prior deprecation of the estimate method, which had implied the need for the no-argument constructor, of form cm = CircleMoldel(); cm.estimate(data) (#7789).
  • In skimage.measure, deprecate use of params arguments to predict* calls of model objects. This applies to CircleModel, EllipseModel, and LineModelND. We now ask instead that the user provide initialization equivalent to the params content in the class construction. For example, prefer cm = CircleModel((2, 3), 4); x = cm.predict_x(t) to cm = CircleMoldel(); x = cm.predict_x(t, params=(2, 3, 4))) (#7789).

Enhancements

  • Raise a ValueError instead of a TypeError in CircleModel, EllipseModel, and LineModelND in skimage.measure. This applies when failing to pass a value for params (or passing params=None) to predict methods of an uninitialized transform (#7789).
  • In skimage.measure, the RegionProperties class that is returned by regionprops, now has a formatted string representation (__repr__). This representation includes the label of the region and its bounding box (#7887).

Performance

  • Use greedy einsum optimization in skimage.measure.moments_central (#7947).
  • Add lazy loading to skimage.segmentation (#7035).

Bug Fixes

  • Make deconvolution example scientifically sensible (#7589).
  • In skimage.filters.sobel/scharr/prewitt/farid, when mode="constant" is used ensure that cval has an effect. It didn't previously (#7826).
  • Ensure skimage.graph.cut_normalized is deterministic when seeded with the rng parameter and when SciPy 1.17.0.dev0 or newer is installed. With earlier SciPy versions the internally used function scipy.linalg.eigsh is not deterministic and can lead to different results (#7912).
  • Avoid potential integer overflow in skimage.morphology.reconstruction (#7938).
  • Handle negative axis lengths due to numerical errors in axis_major_length and axis_minor_length properties of skimage.measure.regionprops (#7916).
  • In skimage.util.random_noise, ensure that clip argument is handled consistently for various modes (#7924).
  • Apparent fix for Hough transform stray j (#7974).

... (truncated)

Commits
  • ee0a7a3 Designate 0.26.0 release
  • b0e3c2d Clarify RELEASE.txt after v0.26.0rc2 (#7990)
  • a12ddfa Bump version in skimage init to 0.26.0rc3.dev0
  • ab3bd14 Bump version in skimage init to 0.26.0rc2
  • c27ac8f Designate 0.26.0rc2 release (#7987)
  • 211223b Clarify non-native support for masked array in the documentation (#7968)
  • b3da953 Mark test_wrap_around as xfail on macOS until 2026-02-01 (#7985)
  • 2799d12 Note issue number tracking the flakiness
  • 52996fd Set exception type in xfail
  • dd49f1f xfail on macOS and make mark temporary until 2026-02-01
  • Additional commits viewable in compare view

Updates statsmodels from 0.14.4 to 0.14.6

Release notes

Sourced from statsmodels's releases.

Release 0.14.6

This patch release fixes an issue with pandas 3.0.0 that prevented statsmodels from importing. It also addresses some minor changes that improve future compatibility in NumPy.

Release 0.14.5

This patch release fixes an issue with recent SciPy releases (1.16+) that prevented statsmodels from importing. It also addresses some small changes that improve future compatibility.

Commits
  • 40e6a84 Merge pull request #9701 from bashtage/doc-0.14.6-changes
  • 120ad27 DOC: Release note for 0.14.6
  • e8b0ab0 Merge pull request #9700 from bashtage/final-0.14.6-changes
  • 8ad398a MAINT: Improve compatability wiht recent NumPy
  • 9495808 Merge pull request #9633 from bashtage/changes-0-14-6
  • b44854a STY: Fix linting fails
  • e7b2fa5 MAINT: Update for recent changes
  • 1107ea5 Merge pull request #9591 from bashtage/rls-0-14-5-notes
  • f3b362a MAINT: Update CI
  • e2249ab DOC: Final fixes
  • Additional commits viewable in compare view

Updates jupyter-book to 2.1.0

Release notes

Sourced from jupyter-book's releases.

v2.1.0

2.1.0

(Full Changelog)

Enhancements made

Maintenance and upkeep improvements

Documentation improvements

Other merged PRs

Contributors to this release

(GitHub contributors page for this release)

@​agoose77 | @​akhmerov | @​bsipocz | @​choldgraf | @​FreekPols | @​JimMadge | @​matthew-brett | @​rgaiacs | @​rowanc1 | @​stefanv | @​surodeep26

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@dependabot
Bump the actions group across 1 directory with 8 updates
b2b759b 
Updates the requirements on [numpy](https://github.com/numpy/numpy), [scipy](https://github.com/scipy/scipy), [matplotlib](https://github.com/matplotlib/matplotlib), [pandas](https://github.com/pandas-dev/pandas), [scikit-learn](https://github.com/scikit-learn/scikit-learn), [scikit-image](https://github.com/scikit-image/scikit-image), [statsmodels](https://github.com/statsmodels/statsmodels) and [jupyter-book](https://github.com/jupyter-book/jupyter-book) to permit the latest version.

Updates `numpy` from 2.2.5 to 2.4.0
- [Release notes](https://github.com/numpy/numpy/releases)
- [Changelog](https://github.com/numpy/numpy/blob/main/doc/RELEASE_WALKTHROUGH.rst)
- [Commits](numpy/numpy@v2.2.5...v2.4.0)

Updates `scipy` from 1.15.2 to 1.16.3
- [Release notes](https://github.com/scipy/scipy/releases)
- [Commits](scipy/scipy@v1.15.2...v1.16.3)

Updates `matplotlib` from 3.10.1 to 3.10.8
- [Release notes](https://github.com/matplotlib/matplotlib/releases)
- [Commits](matplotlib/matplotlib@v3.10.1...v3.10.8)

Updates `pandas` from 2.2.3 to 2.3.3
- [Release notes](https://github.com/pandas-dev/pandas/releases)
- [Commits](pandas-dev/pandas@v2.2.3...v2.3.3)

Updates `scikit-learn` from 1.6.1 to 1.8.0
- [Release notes](https://github.com/scikit-learn/scikit-learn/releases)
- [Commits](scikit-learn/scikit-learn@1.6.1...1.8.0)

Updates `scikit-image` from 0.25.2 to 0.26.0
- [Release notes](https://github.com/scikit-image/scikit-image/releases)
- [Changelog](https://github.com/scikit-image/scikit-image/blob/main/RELEASE.txt)
- [Commits](scikit-image/scikit-image@v0.25.2...v0.26.0)

Updates `statsmodels` from 0.14.4 to 0.14.6
- [Release notes](https://github.com/statsmodels/statsmodels/releases)
- [Changelog](https://github.com/statsmodels/statsmodels/blob/main/CHANGES.md)
- [Commits](statsmodels/statsmodels@v0.14.4...v0.14.6)

Updates `jupyter-book` to 2.1.0
- [Release notes](https://github.com/jupyter-book/jupyter-book/releases)
- [Commits](jupyter-book/jupyter-book@v1.0.0...v2.1.0)

---
updated-dependencies:
- dependency-name: numpy
  dependency-version: 2.4.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: actions
- dependency-name: scipy
  dependency-version: 1.16.3
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: actions
- dependency-name: matplotlib
  dependency-version: 3.10.8
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: actions
- dependency-name: pandas
  dependency-version: 2.3.3
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: actions
- dependency-name: scikit-learn
  dependency-version: 1.8.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: actions
- dependency-name: scikit-image
  dependency-version: 0.26.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: actions
- dependency-name: statsmodels
  dependency-version: 0.14.6
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: actions
- dependency-name: jupyter-book
  dependency-version: 2.1.0
  dependency-type: direct:production
  dependency-group: actions
...

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@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update Python code labels Jan 1, 2026
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