[Numpy-discussion] NumPy 2.1.2 released.

[Charles R Harris via NumPy-Discussion]

Hi All,

On behalf of the NumPy team, I'm pleased to announce the release of NumPy
2.1.2. NumPy 2.1.2 is a maintenance release that fixes bugs and regressions
discovered after the 2.1.1 release.

This release supports Python 3.10-3.13. Wheels can be downloaded from PyPI
; source archives, release notes, and
wheel hashes are available on Github
.



*Contributors*
A total of 11 people contributed to this release.  People with a "+" by
theirnames contributed a patch for the first time.

   - Charles Harris
   - Chris Sidebottom
   - Ishan Koradia +
   - João Eiras +
   - Katie Rust +
   - Marten van Kerkwijk
   - Matti Picus
   - Nathan Goldbaum
   - Peter Hawkins
   - Pieter Eendebak
   - Slava Gorloff +


*Pull requests merged*

A total of 14 pull requests were merged for this release.

   - #27333: MAINT: prepare 2.1.x for further development
   - #27400: BUG: apply critical sections around populating the dispatch
   cache
   - #27406: BUG: Stub out get_build_msvc_version if
   distutils.msvccompiler...
   - #27416: BUILD: fix missing include for std::ptrdiff_t for C++23
   language...
   - #27433: BLD: pin setuptools to avoid breaking numpy.distutils
   - #27437: BUG: Allow unsigned shift argument for np.roll
   - #27439: BUG: Disable SVE VQSort
   - #27471: BUG: rfftn axis bug
   - #27479: BUG: Fix extra decref of PyArray_UInt8DType.
   - #27480: CI: use PyPI not scientific-python-nightly-wheels for CI doc...
   - #27481: MAINT: Check for SVE support on demand
   - #27484: BUG: initialize the promotion state to be weak
   - #27501: MAINT: Bump pypa/cibuildwheel from 2.20.0 to 2.21.2
   - #27506: BUG: avoid segfault on bad arguments in
   ndarray.__array_function__


Cheers,

Charles Harris
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[Numpy-discussion] Re: What to do with np.matrix

[Charles R Harris via NumPy-Discussion]

On Mon, Oct 14, 2024 at 8:09 AM Sebastian Berg 
wrote:

> On Sat, 2024-10-12 at 12:13 -0400, Marten van Kerkwijk wrote:
> > Hi Dan, others,
> >
>
> 
>
> > Regardless, since there have been 7 years of
> > PendingDeprecationWarning,
> > I think changing that to a regular DeprecationWarning should not
> > surprise anybody, at least not if they had built a package based on
> > np.matrix.
>
>
> `PendingDeprecationWarning` is hidden by default for all code, so only
> "well maintained" libraries are unlikely to have noticed it.
> I think there are warnings in the docs as well, though.  So hopefully,
> few new code uses it
>
> I am very happy to escalate (also to `VisibleDeprecationWarning`), but
> the question is always how many users are affected by it and how.
> And I am not that optimistic that it is few enough that we don't have
> to make dealing with the change easier in some form.
>
>
VisibleDeprecationWarning would be a good way to get things started.

>
> >
> > It is maybe good to add that it is less easy to split of matrix into
> > its
> > own package than it was for the financial routines: because matrix
> > overrides some pretty basic assumptions of arrays (mostly how shapes
> > behave), there are bits of special-casing for np.matrix throughout
> > the
> > rest of the code, which we would want to remove if np.matrix is no
> > longer part of numpy.  I.e., moving it might mean having to define
> > ``matrix.__array_function__`` and override those functions. This
> > means a
> > new package would need a bit of a champion.
>
>
> This actually made me think a bit.  We have two options (both need a
> champion, and I hope we have that here in Dan).
> An (almost) drop in package may indeed need `__array_function__`
> because NumPy has a few `matrix` isinstance checks.
>
> I am slightly curious what code still uses matrix.  If it is just some
> localized matrix-heavy code, an incredibly light-weight replacement
> might also serve the purpose well enough?
> That would never pass `isinstance()` checks in third-party packages,
> etc. so not sure it can work, though.
>
>
When I looked at the Event Horizon Telescope project code, I noticed that
it was using `matrix`. I don't know if that is still the case.


>
> In any case, overall, I am definitely in favor.  The only question is
> if we have to go to the trouble to create a drop-in replacement.
> And for that it would be nice if we can see how easy that is, because
> while tedious, it may not be all that hard.
>
>
Probably best to stick the code somewhere in case it is needed. I should
probably have done the same with the old Numeric compatibility code when I
removed it.

Chuck
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[Numpy-discussion] Re: What to do with np.matrix

[Charles R Harris via NumPy-Discussion]

On Mon, Oct 14, 2024 at 9:10 AM Nathan  wrote:

> Here's a github code search for the string "np.matrix":
>
> https://github.com/search?q=%22np.matrix%22&type=code
>
> First, if you narrow down to just Python code, there are almost 60
> thousand results, which is quite high, much higher than we we're
> comfortable with for outright removals for NumPy 2.0.
>
> Compared with code searches I did in service of the NumPy 2.0 API changes,
> this returns a lot of repositories in the flavor of "someone's homework
> assignments" rather than "core scientific python package" or "package owned
> by a billion dollar corporation".
>
> So, it's good that "important" packages don't seem to use np.matrix much,
> but also it's bad given that the code that *does* seem to use it is
> probably infrequently or poorly tested, and will require a lengthy
> deprecation period to catch, if the authors are inclined to do anything
> about it at all.
>
> In that case, I think moving things to an external pypi package along with
> a long-lived shim in NumPy that points people to the pypi package is
> probably the least disruptive thing to do, if we're going to do anything.
>
>
Putting the code on PyPI and leaving a shim behind would be the way to go.
If nothing else it will serve to educate users as to the best current usage
of NumPy. And speaking of education, we might want to do something similar
with RandomState. It is amazing how many folks still think of it as the
natural way to get random numbers in NumPy even though the preferred
Generator based rng has been out for seven years. I think a large part of
that problem comes from classrooms, books, and articles that still use
RandomState, and the remainder from people who were unaware of the new
capabilities. I think we could also make that transition in most of the
NumPy testing code.

Chuck
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[Numpy-discussion] NumPy 2.2.x has been branched

[Charles R Harris via NumPy-Discussion]

Hi All,

NumPy 2.2.x has been branched and main is now open for 2.3.0 development.

Chuck
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[Numpy-discussion] NumPy 2.2.0 Released

[Charles R Harris via NumPy-Discussion]

Hi All,

On behalf of the NumPy team, I'm pleased to announce the release of NumPy
2.2.0. The NumPy 2.2.0 release is a short release that brings us back into
sync with the usual twice yearly release cycle. There have been a number of
small cleanups, as well as work bringing the new StringDType to completion
and improving support for free threaded Python. Highlights are:

   - New functions `matvec` and `vecmat`, see below.
   - Many improved annotations.
   - Improved support for the new StringDType.
   - Improved support for free threaded Python
   - Fixes for f2py

This release supports Python 3.10-3.13. Wheels can be downloaded from PyPI
; source archives, release notes, and
wheel hashes are available on Github
.

Cheers,

Charles Harris
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[Numpy-discussion] NumPy 2.2.1 released

[Charles R Harris via NumPy-Discussion]

Hi All,

On behalf of the NumPy team, I'm pleased to announce the release of
NumPy 2.2.1. NumPy 2.2.1 is a patch release following 2.2.0. It fixes bugs
found after the 2.2.0 release and has several maintenance pins to work
around upstream changes.

There was some breakage in downstream projects following the 2.2.0 release
due to updates to NumPy typing. Because of problems due to MyPy defects, we
recommend using basedpyright for type checking, it can be installed from
PyPI. The Pylance extension for Visual Studio Code is also based on
Pyright. Typing problems that persist when using basedpyright should be
reported as issues on the NumPy github site.

This release supports Python 3.10-3.13. Wheels can be downloaded from PyPI
; source archives, release notes, and
wheel hashes are available on Github
.


*Contributors*

A total of 9 people contributed to this release.  People with a "+" by their
names contributed a patch for the first time.

   - Charles Harris
   - Joren Hammudoglu
   - Matti Picus
   - Nathan Goldbaum
   - Peter Hawkins
   - Simon Altrogge
   - Thomas A Caswell
   - Warren Weckesser
   - Yang Wang +



*Pull requests merged*
A total of 12 pull requests were merged for this release.

   - #27935: MAINT: Prepare 2.2.x for further development
   - #27950: TEST: cleanups
   - #27958: BUG: fix use-after-free error in npy_hashtable.cpp (#27955)
   - #27959: BLD: add missing include
   - #27982: BUG:fix compile error libatomic link test to meson.build
   - #27990: TYP: Fix falsely rejected value types in
   ``ndarray.__setitem__``
   - #27991: MAINT: Don't wrap ``#include `` with ``extern "C"``
   - #27993: BUG: Fix segfault in stringdtype lexsort
   - #28006: MAINT: random: Tweak module code in mtrand.pyx to fix a
   Cython...
   - #28007: BUG: Cython API was missing NPY_UINTP.
   - #28021: CI: pin scipy-doctest to 1.5.1
   - #28044: TYP: allow ``None`` in operand sequence of nditer


Cheers,

Charles Harris
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[Numpy-discussion] NumPy 2.2. 2 Release

[Charles R Harris via NumPy-Discussion]

Hi All,

On behalf of the NumPy team, I'm pleased to announce the release of
NumPy 2.2.2. NumPy 2.2.2 is a patch release that fixes bugs found after the
2.2.1 release. The number of typing fixes/updates is notable.

This release supports Python 3.10-3.13. Wheels can be downloaded from PyPI
; source archives, release notes, and
wheel hashes are available on Github
.

*Contributors*

A total of 8 people contributed to this release.  People with a "+" by their
names contributed a patch for the first time.

   - Alicia Boya García +
   - Charles Harris
   - Joren Hammudoglu
   - Kai Germaschewski +
   - Nathan Goldbaum
   - PTUsumit +
   - Rohit Goswami
   - Sebastian Berg


*Pull requests merged*

A total of 16 pull requests were merged for this release.


   - #28050: MAINT: Prepare 2.2.x for further development
   - #28055: TYP: fix ``void`` arrays not accepting ``str`` keys in
   ``__setitem__``
   - #28066: TYP: fix unnecessarily broad ``integer`` binop return types
   (#28065)
   - #28112: TYP: Better ``ndarray`` binop return types for ``float64`` &...
   - #28113: TYP: Return the correct ``bool`` from ``issubdtype``
   - #28114: TYP: Always accept ``date[time]`` in the ``datetime64``
   constructor
   - #28120: BUG: Fix auxdata initialization in ufunc slow path
   - #28131: BUG: move reduction initialization to ufunc initialization
   - #28132: TYP: Fix ``interp`` to accept and return scalars
   - #28137: BUG: call PyType_Ready in f2py to avoid data races
   - #28145: BUG: remove unnecessary call to PyArray_UpdateFlags
   - #28160: BUG: Avoid data race in PyArray_CheckFromAny_int
   - #28175: BUG: Fix f2py directives and --lower casing
   - #28176: TYP: Fix overlapping overloads issue in 2->1 ufuncs
   - #28177: TYP: preserve shape-type in ndarray.astype()
   - #28178: TYP: Fix missing and spurious top-level exports


Cheers,

Charles Harris
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[Numpy-discussion] NumPy 2.2.4 released

[Charles R Harris via NumPy-Discussion]

Hi All,

On behalf of the NumPy team, I'm pleased to announce the release of
NumPy 2.2.3. NumPy 2.2.4 is a patch release that fixes bugs found after the
2.2.3 release. There are a large number of typing improvements, the rest of
the changes are the usual mix of bug fixes and platform maintenance.

This release supports Python 3.10-3.13. Wheels can be downloaded from PyPI
; source archives, release notes, and
wheel hashes are available on Github
.


*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
   - Andrej Zhilenkov
   - Andrew Nelson
   - Charles Harris
   - Giovanni Del Monte
   - Guan Ming(Wesley) Chiu +
   - Jonathan Albrecht +
   - Joren Hammudoglu
   - Mark Harfouche
   - Matthieu Darbois
   - Nathan Goldbaum
   - Pieter Eendebak
   - Sebastian Berg
   - Tyler Reddy
   - lvllvl +



*Pull requests merged*
A total of 17 pull requests were merged for this release.

   - #28333: MAINT: Prepare 2.2.x for further development.
   - #28348: TYP: fix positional- and keyword-only params in astype,
   cross...
   - #28377: MAINT: Update FreeBSD version and fix test failure
   - #28379: BUG: numpy.loadtxt reads only 5 lines when skip_rows >=
   max_rows
   - #28385: BUG: Make np.nonzero threading safe
   - #28420: BUG: safer bincount casting (backport to 2.2.x)
   - #28422: BUG: Fix building on s390x with clang
   - #28423: CI: use QEMU 9.2.2 for Linux Qemu tests
   - #28424: BUG: skip legacy dtype multithreaded test on 32 bit runners
   - #28435: BUG: Fix searchsorted and CheckFromAny byte-swapping logic
   - #28449: BUG: sanity check ``__array_interface__`` number of dimensions
   - #28510: MAINT: Hide decorator from pytest traceback
   - #28512: TYP: Typing fixes backported from #28452, #28491, #28494
   - #28521: TYP: Backport fixes from #28505, #28506, #28508, and #28511
   - #28533: TYP: Backport typing fixes from main (2)
   - #28534: TYP: Backport typing fixes from main (3)
   - #28542: TYP: Backport typing fixes from main (4)


Cheers,

Charles Harris
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[Numpy-discussion] Re: Moving the meetings schedule to one hour earlier

[Charles R Harris via NumPy-Discussion]

On Wed, Mar 26, 2025 at 1:18 PM Sebastian Berg 
wrote:

> Hi all,
>
> it's that time of the year again where daylight savings time starts
> (the US had it already and Europe will have it now).
>
> I suggest we "realign" our meeting to this time zone (since it is
> scheduled as UTC), I think for our typical crowd that is the nicer time
> slot.
>
> (I would slightly prefer to move it, but am OK either way.)
>
>
One hour earlier would be fine with me.

Chuck
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[Numpy-discussion] NumPy 2.2.5 released

[Charles R Harris via NumPy-Discussion]

Hi All,

NumPy 2.2.5 is a patch release that fixes bugs found after the 2.2.4
release. It has a large number of typing fixes/improvements as well as the
normal bug fixes and some CI maintenance.

This release supports Python 3.10-3.13. Wheels can be downloaded from PyPI
; source archives, release notes, and
wheel hashes are available on Github
.


*Contributors*

A total of 7 people contributed to this release.  People with a "+" by
their names contributed a patch for the first time.

   - Charles Harris
   - Joren Hammudoglu
   - Baskar Gopinath +
   - Nathan Goldbaum
   - Nicholas Christensen +
   - Sayed Adel
   - karl +



*Pull requests merged*
A total of 19 pull requests were merged for this release.

   - #28545: MAINT: Prepare 2.2.x for further development
   - #28582: BUG: Fix return type of NpyIter_GetIterNext in Cython
   declarations
   - #28583: BUG: avoid deadlocks with C++ shared mutex in dispatch cache
   - #28585: TYP: fix typing errors in ``_core.strings``
   - #28631: MAINT, CI: Update Ubuntu to 22.04 in azure-pipelines
   - #28632: BUG: Set writeable flag for writeable dlpacks.
   - #28633: BUG: Fix crackfortran parsing error when a division occurs
   within...
   - #28650: TYP: fix ``ndarray.tolist()`` and ``.item()`` for unknown dtype
   - #28654: BUG: fix deepcopying StringDType arrays (#28643)
   - #28661: TYP: Accept objects that ``write()`` to ``str`` in ``savetxt``
   - #28663: CI: Replace QEMU armhf with native (32-bit compatibility mode)
   - #28682: SIMD: Resolve Highway QSort symbol linking error on
   aarch32/ASIMD
   - #28683: TYP: add missing ``"b1"`` literals for ``dtype[bool]``
   - #28705: TYP: Fix false rejection of ``NDArray[object_].__abs__()``
   - #28706: TYP: Fix inconsistent ``NDArray[float64].__[r]truediv__``
   return...
   - #28723: TYP: fix string-like ``ndarray`` rich comparison operators
   - #28758: TYP: some ``[arg]partition`` fixes
   - #28772: TYP: fix incorrect ``random.Generator.integers`` return type
   - #28774: TYP: fix ``count_nonzero`` signature


Cheers,

Charles Harris
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[Numpy-discussion] Fwd: Research Opportunity: Can we monitor your projects?

[Charles R Harris via NumPy-Discussion]

Just thought I'd pass this along for discussion.

Chuck

-- Forwarded message -
From: 
Date: Tue, Apr 29, 2025 at 4:09 PM
Subject: Research Opportunity: Can we monitor your projects?
To: Charles Harris 


Hello Charles Harris,

I'm Samuel Flint, and I'm working with Dr. Robert Dyer from the University
of Nebraska-Lincoln on a study about type annotations in dynamic
languages.  We would like your permission to monitor the following
project(s), which are highly relevant to our research, and for which you
are maintainer:

 - numpy/numpy (https://github.com/numpy/numpy)

If you agree, we will provide a bot that tracks changes related to type
annotations.  The bot will notify committers after relevant changes, asking
them to participate in the study (no more than once every 24 hours, and
they can opt-out or request data removal at any time).

Would you be willing to have us monitor your project(s)?  If so, please
install the bot using the instructions here:
https://github.com/apps/typechangebot

Additional help is available from GitHub (
https://docs.github.com/en/apps/using-github-apps/installing-a-github-app-from-a-third-party
).

Thanks for considering!

Samuel W. Flint and Robert Dyer

This study as been approved by the University of Nebraska-Lincoln
Institutional Review Board (
https://research.unl.edu/researchcompliance/human-subjects-research/) with
the title "Understanding Developers' Addition and Removal of Type
Annotations", IRB# 23988.
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[Numpy-discussion] Dropping PyPy in NumPy 2.3

[Charles R Harris via NumPy-Discussion]

Hi All,

Just thought I would raise the topic of PyPy status in NumPy 2.3. PyPy for
Python 3.11 currently has a bug which has hung around for a while, and it
is also likely that there will be no PyPy for Python 3.12. It looks like
PyPy is reaching end of life, and this seems a good time to decide if we
should continue releasing wheels for it.

Thoughts?

Chuck
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[Numpy-discussion] NumPy 2.2.3 Release

[Charles R Harris via NumPy-Discussion]

Hi All,

On behalf of the NumPy team, I'm pleased to announce the release of
NumPy 2.2.3. NumPy 2.2.3 is a patch release that fixes bugs found after the
2.2.2 release. The majority of the changes are typing improvements and
fixes for free threaded Python. Both of those areas are still under
development, so if you discover new problems, please report them.

This release supports Python 3.10-3.13. Wheels can be downloaded from PyPI
; source archives, release notes, and
wheel hashes are available on Github
.

*Contributors*

A total of 9 people contributed to this release.  People with a "+" by
their names contributed a patch for the first time.

   - !amotzop
   - Charles Harris
   - Chris Sidebottom
   - Joren Hammudoglu
   - Matthew Brett
   - Nathan Goldbaum
   - Raghuveer Devulapalli
   - Sebastian Berg
   - Yakov Danishevsky +



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

   - #28185: MAINT: Prepare 2.2.x for further development
   - #28201: BUG: fix data race in a more minimal way on stable branch
   - #28208: BUG: Fix ``from_float_positional`` errors for huge pads
   - #28209: BUG: fix data race in np.repeat
   - #28212: MAINT: Use VQSORT_COMPILER_COMPATIBLE to determine if we
   should...
   - #28224: MAINT: update highway to latest
   - #28236: BUG: Add cpp atomic support (#28234)
   - #28237: BLD: Compile fix for clang-cl on WoA
   - #28243: TYP: Avoid upcasting ``float64`` in the set-ops
   - #28249: BLD: better fix for clang / ARM compiles
   - #28266: TYP: Fix ``timedelta64.__divmod__`` and
   ``timedelta64.__mod__``...
   - #28274: TYP: Fixed missing typing information of set_printoptions
   - #28278: BUG: backport resource cleanup bugfix from gh-28273
   - #28282: BUG: fix incorrect bytes to stringdtype coercion
   - #28283: TYP: Fix scalar constructors
   - #28284: TYP: stub ``numpy.matlib``
   - #28285: TYP: stub the missing ``numpy.testing`` modules
   - #28286: CI: Fix the github label for ``TYP:`` PR's and issues
   - #28305: TYP: Backport typing updates from main
   - #28321: BUG: fix race initializing legacy dtype casts
   - #28324: CI: update test_moderately_small_alpha


Cheers,

Charles Harris
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[Numpy-discussion] Re: Bumping CPU baseline to x86-64-v2

[Charles R Harris via NumPy-Discussion]

On Fri, May 16, 2025 at 4:23 AM Sayed Adel  wrote:

> Hi All,
>
> I wanted to bring your attention to an important change to NumPy that will
> affect CPU compatibility requirements on x86.
>
> PR #28896 (https://github.com/numpy/numpy/pull/28896) is reorganizing how
> NumPy handles x86 CPU features by moving from individual instruction set
> extensions to standardized microarchitecture levels. As part of this
> change,
>
> *the minimum CPU requirement for x86 systems will be raised to x86-64-v2*If
> your x86 CPU was manufactured in 2009 or later, you likely won't be
> affected, unless you're using Intel Atom CPUs released before 2013.
> We're making this change in 2025, when CPUs that don't support x86-64-v2
> are now over 15 years old. Supporting these antiquated processors increases
> maintenance burden and binary size.
> Bumping the default baseline can also increase the performance since not
> all code paths are dispatched.
> --
> Cheers,
> Sayed
>
>
Sounds good to me.

Chuck
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[Numpy-discussion] NumPy 2.2.6 released

[Charles R Harris via NumPy-Discussion]

Hi All,

NumPy 2.2.6 is a patch release that fixes bugs found after the 2.2.5
release. It is a mix of typing fixes/improvements as well as the normal
bug fixes and some CI maintenance.

This release supports Python 3.10-3.13. Wheels can be downloaded from PyPI
; source archives, release notes, and
wheel hashes are available on Github
.


*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
   - Ilhan Polat
   - Joren Hammudoglu
   - Marco Gorelli +
   - Matti Picus
   - Nathan Goldbaum
   - Peter Hawkins
   - Sayed Adel


*Pull requests merged*

A total of 11 pull requests were merged for this release.

   - #28778: MAINT: Prepare 2.2.x for further development
   - #28851: BLD: Update vendor-meson to fix module_feature conflicts
   arguments\...
   - #28852: BUG: fix heap buffer overflow in np.strings.find
   - #28853: TYP: fix `NDArray[floating] + float` return type
   - #28864: BUG: fix stringdtype singleton thread safety
   - #28865: MAINT: use OpenBLAS 0.3.29
   - #28889: MAINT: from_dlpack thread safety fixes
   - #28913: TYP: Fix non-existent `CanIndex` annotation in
   `ndarray.setfield`
   - #28915: MAINT: Avoid dereferencing/strict aliasing warnings
   - #28916: BUG: Fix missing check for PyErr_Occurred() in
   \_pyarray_correlate.
   - #28966: TYP: reject complex scalar types in ndarray.\_\_ifloordiv\_\_


Cheers,

Charles Harris
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[Numpy-discussion] NumPy 2.3.0rc1 Released

[Charles R Harris via NumPy-Discussion]

Hi All,

On behalf of the NumPy team, I'm pleased to announce the release of
NumPy 2.3.0rc1. The NumPy 2.3.0rc1 release continues the work to improve
free threaded Python support and annotations together with the usual set of
bug fixes. It is unusual in the number of expired deprecations and the
number of code modernizations and style cleanups. The latter may not be
visible to users, but is important for code maintenance over the long term.
Note that we have also upgraded from manylinux2014 to manylinux_2_28.

There are known test failures in the rc1 release involving MyPy and PyPy.
The cause of both has been determined and fixes will be applied before the
final
release. The current Windows on ARM wheels also lack OpenBLAS, but they
should suffice for initial downstream testing. OpenBLAS will be
incorporated in those wheels when it becomes available.

Highlights for this release are:

   - Interactive examples in the NumPy documentation.
   - Building NumPy with OpenMP Parallelization.
   - Preliminary support for Windows on ARM.
   - Improved support for free threaded Python.
   - Improved annotations.


This release supports Python 3.10-3.13. Wheels can be downloaded from PyPI
; source archives, release notes,
and wheel hashes are available on Github
.

Cheers,

Charles Harris
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[Numpy-discussion] NumPy 2.3.x has been branched

[Charles R Harris via NumPy-Discussion]

Hi All,

The main branch is now open for NumPy 2.4.0 development.

Chuck
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[Numpy-discussion] Re: we have a NumPy PyPI organization now

[Charles R Harris via NumPy-Discussion]

On Mon, Jun 16, 2025 at 7:24 AM Ralf Gommers via NumPy-Discussion <
numpy-discussion@python.org> wrote:

> Hi all,
>
> Now that PyPI has organizations and they came out of beta and the
> application queue cleared, I applied for a NumPy organization and that just
> came through (https://pypi.org/org/numpy/). We can start moving projects
> under that now, so it'll look more like https://pypi.org/org/scipy/. For
> the main `numpy` project I don't think it does very much, but for the
> smaller packages that are maintained by a NumPy team it may be beneficial
> to mark them as "official" out of the many many packages that contain
> `numpy` in the package name or description (
> https://pypi.org/search/?q=numpy).
>
> See https://blog.pypi.org/posts/2023-04-23-introducing-pypi-organizations/
> and https://docs.pypi.org/organization-accounts/ for more details on PyPI
> organizations.
>
> Cheers,
> Ralf
>
>
Thanks for taking care of that Ralf. The scipy page looks pretty nice.

Chuck
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[Numpy-discussion] NumPy 2.3.1 released

[Charles R Harris via NumPy-Discussion]

Hi All,

On behalf of the NumPy team, I'm pleased to announce the release of
NumPy 2.3.1. The NumPy 2.3.1 release is a patch release with several bug
fixes, annotation improvements, and better support for OpenBSD. Highlights
are:

   - Fix bug in ``matmul`` for non-contiguous out kwarg parameter
   - Fix for Accelerate runtime warnings on M4 hardware
   - Fix new in NumPy 2.3.0 ``np.vectorize`` casting errors
   - Improved support of cpu features for FreeBSD and OpenBSD

This release supports Python 3.11-3.13, Python 3.14 will be supported when
it is released. Wheels can be downloaded from PyPI
; source archives, release notes, and
wheel hashes are available on Github
.


*Contributors*

A total of 9 people contributed to this release.  People with a "+" by
their names contributed a patch for the first time.

   - Brad Smith +
   - Charles Harris
   - Developer-Ecosystem-Engineering
   - François Rozet
   - Joren Hammudoglu
   - Matti Picus
   - Mugundan Selvanayagam
   - Nathan Goldbaum
   - Sebastian Berg



*Pull requests merged*
A total of 12 pull requests were merged for this release.

   - #29140: MAINT: Prepare 2.3.x for further development
   - #29191: BUG: fix matmul with transposed out arg (#29179)
   - #29192: TYP: Backport typing fixes and improvements.
   - #29205: BUG: Revert ``np.vectorize`` casting to legacy behavior
   (#29196)
   - #29222: TYP: Backport typing fixes
   - #29233: BUG: avoid negating unsigned integers in resize
   implementation...
   - #29234: TST: Fix test that uses uninitialized memory (#29232)
   - #29235: BUG: Address interaction between SME and FPSR (#29223)
   - #29237: BUG: Enforce integer limitation in concatenate (#29231)
   - #29238: CI: Add support for building NumPy with LLVM for Win-ARM64
   - #29241: ENH: Detect CPU features on OpenBSD ARM and PowerPC64
   - #29242: ENH: Detect CPU features on FreeBSD / OpenBSD RISC-V64.


Cheers,

Charles Harris
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[Numpy-discussion] Interesting discussion of ``fast-math``

[Charles R Harris via NumPy-Discussion]

Hi All,

Thought some might find this discussion
 interesting.

Chuck
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[Numpy-discussion] NumPy 2.3.0 released

[Charles R Harris via NumPy-Discussion]

Hi All,

On behalf of the NumPy team, I'm pleased to announce the release of
NumPy 2.3.0.  The NumPy 2.3.0 release improves free threaded Python support
and annotations together with the usual set of bug fixes. It is unusual in
the number of expired deprecations, code modernizations, and style
cleanups. The
latter may not be visible to users, but is important for code maintenance
over the long term. Note that we have also upgraded from manylinux2014 to
manylinux_2_28. Highlights are:

   - Interactive examples in the NumPy documentation.
   - Building NumPy with OpenMP Parallelization.
   - Preliminary support for Windows on ARM.
   - Improved support for free threaded Python.
   - Improved annotations.


This release supports Python 3.11-3.13, Python 3.14 will be supported when
it is released. Wheels can be downloaded from PyPI
; source archives, release notes, and
wheel hashes are available on Github
.

Cheers,

Charles Harris
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