Bump numpy from 1.26.4 to 2.1.3 in /jupyter-notebook

[dependabot]

Bumps numpy from 1.26.4 to 2.1.3.

Release notes

Sourced from numpy's releases.

2.1.3 (Nov 2, 2024)

NumPy 2.1.3 Release Notes

NumPy 2.1.3 is a maintenance release that fixes bugs and regressions discovered after the 2.1.2 release. This release also adds support for free threaded Python 3.13 on Windows.

The Python versions supported by this release are 3.10-3.13.

Improvements

• Fixed a number of issues around promotion for string ufuncs with StringDType arguments. Mixing StringDType and the fixed-width DTypes using the string ufuncs should now generate much more uniform results.

  (gh-27636)

Changes

• numpy.fix now won't perform casting to a floating data-type for integer and boolean data-type input arrays.

  (gh-26766)

Contributors

A total of 15 people contributed to this release. People with a "+" by their names contributed a patch for the first time.

• Abhishek Kumar +
• Austin +
• Benjamin A. Beasley +
• Charles Harris
• Christian Lorentzen
• Marcel Telka +
• Matti Picus
• Michael Davidsaver +
• Nathan Goldbaum
• Peter Hawkins
• Raghuveer Devulapalli
• Ralf Gommers
• Sebastian Berg
• dependabot[bot]
• kp2pml30 +

Pull requests merged

A total of 21 pull requests were merged for this release.

... (truncated)

Changelog

Sourced from numpy's changelog.

This is a walkthrough of the NumPy 2.1.0 release on Linux, modified for building with GitHub Actions and cibuildwheels and uploading to the anaconda.org staging repository for NumPy <https://anaconda.org/multibuild-wheels-staging/numpy>_. The commands can be copied into the command line, but be sure to replace 2.1.0 by 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.
• You can use the keyring app to store the PyPI password for twine. See the online twine documentation for details.

Prior to release

Add/drop Python versions

When adding or dropping Python versions, three files need to be edited:

• .github/workflows/wheels.yml # for github cibuildwheel
• tools/ci/cirrus_wheels.yml # for cibuildwheel aarch64/arm64 builds
• pyproject.toml # for classifier and minimum version check.

Make these changes in an ordinary PR against main and backport if necessary. Add [wheel build] at the end of the title line of the commit summary so that wheel builds will be run to test the changes. We currently release wheels for new Python versions after the first Python rc once manylinux and cibuildwheel support it. For Python 3.11 we were able to release within a week of the rc1 announcement.

Backport pull requests

Changes that have been marked for this release must be backported to the maintenance/2.1.x branch.

Update 2.1.0 milestones

... (truncated)

Commits

• 98464cc Merge pull request #27690 from charris/prepare-2.1.3
• cbda85b REL: Prepare for the NumPy 2.1.3 release [wheel build]
• daa8699 Merge pull request #27672 from charris/backport-27666
• 614ca19 Merge pull request #27673 from charris/backport-27636
• e6b02d7 DOC: add release note
• 54fd729 BUG: substantially simplify and fix issue with justification promoter
• a90fe7c BUG: fix more issues with string ufunc promotion
• a121864 BUG: fixes for StringDType/unicode promoters
• f055fb9 BUG: Fix a reference count leak in npy_find_descr_for_scalar.
• 5895c02 Merge pull request #27669 from charris/backport-27663
• Additional commits viewable in compare view

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