Mailman 3 - NumPy-Discussion

Fwd: Optional control over 0D array return behavior in PyArray_Return
by Breno Augusto Favaretto April 12, 2026

April 12, 2026

Hello NumPy developers, I would like to propose an optional mechanism to control the behavior of 0-dimensional array return conversion in PyArray_Return. Currently, 0D NumPy arrays are automatically converted into Python scalars in many operations. In some workflows, it is desirable to preserve the ndarray object instead. Proposed idea: - Introduce an opt-in mechanism (initially implemented as a global flag) to control whether 0D arrays are converted to scalars or preserved as ndarray objects. - Default behavior remains unchanged for full backward compatibility. Motivation: In certain array-centric workflows, implicit scalar conversion of 0D arrays can lead to loss of consistency when uniform ndarray behavior is desired. I have implemented a prototype PR here: <https://github.com/numpy/numpy/pull/31221> However, I was informed that this kind of change requires prior discussion on the mailing list before proceeding further. I would appreciate feedback on: - whether this direction is acceptable - whether a global flag is appropriate - or if an alternative design (context-local, function-level, etc.) would be preferred Thank you for your time.

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next NumPy triage meeting - Wednesday, February 18th, 2026 at 18:00 UTC
by Inessa Pawson April 12, 2026

April 12, 2026

Our next triage meeting will be held this Wednesday, February 18th at 18:00 (6 pm) UTC. This is a meeting where we synchronously triage prioritized PRs and issues. Everyone is welcome to attend and contribute to a conversation. Join us via Zoom: https://numfocus-org.zoom.us/j/82096749952?pwd=MW9oUmtKQ1c3a2gydGk1RTdYUUVX… If there are PRs or issues you’d like us to review, please add GitHub links to them to the meeting agenda: https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg -- Cheers, Inessa Inessa Pawson GitHub: inessapawson

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SPy: a new companion static language for Python; thoughts?
by PIERRE AUGIER April 8, 2026

April 8, 2026

Hello, Do any of you follow SPy (https://github.com/spylang/spy), the new statically compiled variant of Python created by Antonio Cuni? I have been looking into it recently and became convinced it could have a significant impact on the Python ecosystem, including for numerical computing and libraries like NumPy. I wrote up my thoughts in a post entitled "SPy: a vision for its impact on the Python community": https://fluiddyn.pages.heptapod.net/spy-book/impact-on-python/ I would be very interested to hear what this community thinks, both about SPy itself and about the ideas in the post. Best, Pierre Augier (CNRS researcher in fluid mechanics, Grenoble)

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next NumPy community meeting - Wednesday, April 9th, 2025 at 5 pm UTC - now meeting ONE HOUR EARLIER
by Inessa Pawson April 5, 2026

April 5, 2026

The next NumPy community meeting will be held this Wednesday, April 9th at 17:00 (5 pm) UTC. Please note the TIME CHANGE! Join us via Zoom: https://numfocus-org.zoom.us/j/83278611437?pwd=ekhoLzlHRjdWc0NOY2FQM0NPemdk… Everyone is welcome and encouraged to attend. To add to the meeting agenda the topics you’d like to discuss, follow the link: https://hackmd.io/76o-IxCjQX2mOXO_wwkcpg?both For the notes from the previous meetings, visit: https://github.com/numpy/archive/tree/main/community_meetings -- Cheers, Inessa Inessa Pawson GitHub: inessapawson

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next NumPy Optimization Team meeting - Monday, January 20th, 2025 at 5 pm UTC
by Inessa Pawson April 3, 2026

April 3, 2026

Hi, all! The next NumPy Optimization Team meeting will be held on Monday, January 20th at 17:00 UTC. Join us via Zoom: https://numfocus-org.zoom.us/j/81261288210?pwd=iwV99tGSjR61RTGEERKM4QKxe46g… Everyone is welcome and encouraged to attend. To add to the meeting agenda the topics you’d like to discuss, follow the link: https://hackmd.io/dVdSlQ0TThWkOk0OkmGsmw?both For the notes from the previous meetings, visit: https://github.com/numpy/archive/tree/main/optim_team_meetings -- Cheers, Inessa Inessa Pawson GitHub: inessapawson

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Deprecating unitless timedelta/datetime
by Sebastian Berg March 29, 2026

March 29, 2026

Hi all, I just merged a PR: https://github.com/numpy/numpy/pull/29619 to deprecate unitless timdeldta/datetime64. This is a step in a direction that should be e.g. very helpful for pandas to make timedelta/datetimes less weird. That said, we didn't touch this for a long time, because it is also very hard to really understand how and if users might be impacted. So if you notice this, or maybe even think you may be mixing timedeltas with normal integers/floats a lot you may want to try this branch. This is a `DeprecationWarning`, so it shouldn't out-right break code in production. Note that there are also specific things we could try to make more gentle, even something niche like specifically allowing: `timdelta_arr == 0` (although `timedelta_arr.astype(bool)` should be a plausible replacement as well, I think). Or generally keep allowing `timedelta_arr + integer_arr`, etc. which, with this PR, I believe should give a warning. Cheers, Sebastian

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NumPy 2.4.4 Released
by Charles R Harris March 29, 2026

March 29, 2026

Hi All, On behalf of the NumPy team, I'm pleased to announce the release of NumPy 2.4.4. NumPy 2.4.4 is a patch release that fixes bugs discovered after the 2.4.3 release. It should finally close issue #30816, the OpenBLAS threading problem on ARM. This release supports Python versions 3.11-3.14. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/2.4.4>; release notes and the changelog are available on Github <https://github.com/numpy/numpy/releases/tag/v2.4.4>. *Contributors* A total of 8 people contributed to this release. People with a \"+\" by their names contributed a patch for the first time. - Charles Harris - Daniel Haag + - Denis Prokopenko + - Harshith J + - Koki Watanabe - Marten van Kerkwijk - Matti Picus - Nathan Goldbaum *Pull requests merged* A total of 7 pull requests were merged for this release. - #30978: MAINT: Prepare 2.4.x for further development - #31049: BUG: Add test to reproduce problem described in #30816 (#30818) - #31052: BUG: fix FNV-1a 64-bit selection by using NPY_SIZEOF_UINTP (#31035) - #31053: BUG: avoid warning on ufunc with where=True and no output - #31058: DOC: document caveats of ndarray.resize on 3.14 and newer - #31079: TST: fix POWER VSX feature mapping (#30801) - #31084: MAINT: numpy.i: Replace deprecated `sprintf` with `snprintf`... Cheers, Charles Harris

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Localization of The NumPy Documentation
by Haowei Hsu March 21, 2026

March 21, 2026

Hello, NumPy Community, I am the author of the Localize The Docs organization on GitHub: https://github.com/localizethedocs And I’m glad to announce that the 🎉 numpy-docs-l10n 🎉 project is published now: 🚀 Preview: https://projects.localizethedocs.org/numpy-docs-l10n 🌐 Crowdin: https://localizethedocs.crowdin.com/numpy-docs-l10n 🐙 GitHub: https://github.com/localizethedocs/numpy-docs-l10n The goal of this project is to translate The NumPy Documentation into multiple languages. Translations are contributed via the Crowdin platform, automatically synchronized with the GitHub repository, and can be previewed on GitHub Pages. We welcome anyone interested in documentation translation to join us.

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NumPy Triage Team permissions review
by Inessa Pawson March 17, 2026

March 17, 2026

Hi, all! The NumPy Steering Council is currently reviewing permissions across all project repositories. As part of this process, we will be removing triage rights from members of the Triage Team who have not performed triage activities in the past 12+ months. If your access is removed but you would like to resume contributing to triage, please reach out to the Steering Council via numpy-team(a)googlegroups.com We will review requests for reinstatement on a case-by-case basis. -- Cheers, Inessa Inessa Pawson GitHub: inessapawson

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Code Coverage for C and Python
by Ganesh Kathiresan March 16, 2026

March 16, 2026

Hi all, I wanted to get a wider feedback on adding a code coverage CI for C and Python. Prototype PR Link: https://github.com/numpy/numpy/pull/30911 *Why add this CI:* - diff-cover provides a way to see coverage only on the changed files, which is good for big PRs to understand the UT compared to the main branch. - With the new GH actions-upload (v7), we can get a clickable link to the report in a single file. For now the PR implements a MD file format as HTML file leads to ~250MB file *Why not to add this CI:* - Today code coverage and dead code can be calculated locally by following this: https://numpy.org/doc/stable/dev/index.html#test-coverage. So there is not much value in running this for every PR Please let us know your thoughts on having this new CI action. Thanks, Ganesh (https://github.com/ganesh-k13)

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