Mailman 3 June 2025 - Python-announce-list

python-oracledb 3.2.0
by Anthony Tuininga June 27, 2025

June 27, 2025

What is python-oracledb? python-oracledb is a Python extension module that enables access to Oracle Database for Python and conforms to the Python database API 2.0 specifications with a number of enhancements. This module replaces cx_Oracle. Where do I get it? https://pypi.org/project/oracledb/3.2.0/ The easiest method to install/upgrade python-oracledb is via pip as in python -m pip install oracledb --upgrade What's new? This release adds a number of new features and corrects a number of issues. Highlights are as follows: - support for recipient lists in Oracle Advanced Queuing with thin mode - support for fetching VECTOR columns in data frames - support for Instance Principal authentication when using OCI Cloud Native Authentication - support for Oracle Database 23ai multi-pool DRCP See the full release notes for all of the details: https://python-oracledb.readthedocs.io/en/latest/release_notes.html#oracled… Please provide any feedback via GitHub issues: https://github.com/oracle/ python-oracledb/issues or discussions: https://github.com/oracle/python- oracledb/discussions

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ANN: Python-Blosc2 3.5.0 is out!
by Francesc Alted June 24, 2025

June 24, 2025

Announcing Python-Blosc2 3.5.0 ============================== This release adds significant new functionality in the form of ``stack()``. It allows you to stack multiple Blosc2 NDarrays along a new axis, similar to NumPy's ``np.stack()``. This is particularly useful for creating higher-dimensional arrays from lower-dimensional ones. We have blogged about this: https://www.blosc.org/posts/blosc2-new-concatenate/#stacking-arrays You can think of Python-Blosc2 3.x as an extension of NumPy/numexpr that: - Can deal with ndarrays compressed using first-class codecs & filters. - Performs many kind of math expressions, including reductions, indexing... - Supports broadcasting operations. - Supports NumPy ufunc mechanism: mix and match NumPy and Blosc2 computations. - Integrates with Numba and Cython via UDFs (User Defined Functions). - Adheres to modern NumPy casting rules way better than numexpr. - Supports linear algebra operations (like ``blosc2.matmul()``). Install it with:: pip install blosc2 --update # if you prefer wheels conda install -c conda-forge python-blosc2 mkl # if you prefer conda and MKL For more info, you can have a look at the release notes in: https://github.com/Blosc/python-blosc2/releases Code example:: from time import time import blosc2 import numpy as np # Create some data operands N = 20_000 a = blosc2.linspace(0, 1, N * N, dtype="float32", shape=(N, N)) b = blosc2.linspace(1, 2, N * N, shape=(N, N)) c = blosc2.linspace(-10, 10, N) # broadcasting is supported # Expression t0 = time() expr = ((a**3 + blosc2.sin(c * 2)) < b) & (c > 0) print(f"Time to create expression: {time()-t0:.5f}") # Evaluate while reducing (yep, reductions are in) along axis 1 t0 = time() out = blosc2.sum(expr, axis=1) t1 = time() - t0 print(f"Time to compute with Blosc2: {t1:.5f}") # Evaluate using NumPy na, nb, nc = a[:], b[:], c[:] t0 = time() nout = np.sum(((na**3 + np.sin(nc * 2)) < nb) & (nc > 0), axis=1) t2 = time() - t0 print(f"Time to compute with NumPy: {t2:.5f}") print(f"Speedup: {t2/t1:.2f}x") assert np.all(out == nout) print("All results are equal!") This will output something like (using an Intel i9-13900X CPU here):: Time to create expression: 0.00033 Time to compute with Blosc2: 0.46387 Time to compute with NumPy: 2.57469 Speedup: 5.55x All results are equal! See a more in-depth example, explaining why Python-Blosc2 is so fast, at: https://www.blosc.org/python-blosc2/getting_started/overview.html#operating… Sources repository ------------------ The sources and documentation are managed through github services at: https://github.com/Blosc/python-blosc2 Python-Blosc2 is distributed using the BSD license, see https://github.com/Blosc/python-blosc2/blob/main/LICENSE.txt for details. Mastodon feed ------------- Follow https://fosstodon.org/@Blosc2 to get informed about the latest developments. Enjoy! - Blosc Development Team Compress better, compute bigger

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NumPy 2.3.1 released
by Charles R Harris June 21, 2025

June 21, 2025

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 <https://pypi.org/project/numpy/2.3.1>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v2.3.1>. *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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pytest-8.4.1
by Bruno Oliveira June 18, 2025

June 18, 2025

pytest 8.4.1 has just been released to PyPI. This is a bug-fix release, being a drop-in replacement. The full changelog is available at https://docs.pytest.org/en/stable/changelog.html. Thanks to all of the contributors to this release: * Bruno Oliveira * Iwithyou2025 * John Litborn * Martin Fischer * Ran Benita * SarahPythonista Happy testing, The pytest Development Team

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Python 3.14.0 beta 3 is here!
by Hugo van Kemenade June 17, 2025

June 17, 2025

It’s 3.14 beta 3! https://www.python.org/downloads/release/python-3140b3/ This is a beta preview of Python 3.14 Python 3.14 is still in development. This release, 3.14.0b3, is the third of four planned beta releases. Beta release previews are intended to give the wider community the opportunity to test new features and bug fixes and to prepare their projects to support the new feature release. We strongly encourage maintainers of third-party Python projects to test with 3.14 during the beta phase and report issues found to the Python bug tracker as soon as possible. While the release is planned to be feature-complete entering the beta phase, it is possible that features may be modified or, in rare cases, deleted up until the start of the release candidate phase (Tuesday 2025-07-22). Our goal is to have no ABI changes after beta 4 and as few code changes as possible after the first release candidate. To achieve that, it will be extremely important to get as much exposure for 3.14 as possible during the beta phase. This includes creating pre-release wheels for 3.14, as it helps other projects to do their own testing. However, we recommend that your regular production releases wait until 3.14.0rc1, to avoid the risk of ABI breaks. Please keep in mind that this is a preview release and its use is not recommended for production environments. Major new features of the 3.14 series, compared to 3.13 Some of the major new features and changes in Python 3.14 are: New features Note that PEPs 734 and 779 are exceptionally new in beta 3! - PEP 779: Free-threaded Python is officially supported - PEP 649: The evaluation of type annotations is now deferred, improving the semantics of using annotations. - PEP 750: Template string literals (t-strings) for custom string processing, using the familiar syntax of f-strings. - PEP 734: Multiple interpreters in the stdlib. - PEP 784: A new module compression.zstd providing support for the Zstandard compression algorithm. - PEP 758: except and except* expressions may now omit the brackets. - Syntax highlighting in PyREPL, and support for color in unittest, argparse, json and calendar CLIs. - PEP 768: A zero-overhead external debugger interface for CPython. - UUID versions 6-8 are now supported by the uuid module, and generation of versions 3-5 and 8 are up to 40% faster. - PEP 765: Disallow return/break/continue that exit a finally block. - PEP 741: An improved C API for configuring Python. - A new type of interpreter. For certain newer compilers, this interpreter provides significantly better performance. Opt-in for now, requires building from source. - Improved error messages. - Builtin implementation of HMAC with formally verified code from the HACL* project. - A new command-line interface to inspect running Python processes using asynchronous tasks. - The pdb module now supports remote attaching to a running Python process. (Hey, fellow core developer, if a feature you find important is missing from this list, let Hugo know.) For more details on the changes to Python 3.14, see What’s new in Python 3.14. The next pre-release of Python 3.14 will be the final beta, 3.14.0b4, scheduled for 2025-07-08. https://docs.python.org/3.14/whatsnew/3.14.html Build changes - PEP 761: Python 3.14 and onwards no longer provides PGP signatures for release artifacts. Instead, Sigstore is recommended for verifiers. - Official macOS and Windows release binaries include an experimental JIT compiler. Incompatible changes, removals and new deprecations - Incompatible changes - Python removals and deprecations - C API removals and deprecations - Overview of all pending deprecations Python install manager The installer we offer for Windows is being replaced by our new install manager, which can be installed from the Windows Store or our FTP page. See our documentation for more information. The JSON file available for download below contains the list of all the installable packages available as part of this release, including file URLs and hashes, but is not required to install the latest release. The traditional installer will remain available throughout the 3.14 and 3.15 releases. More resources - [Online documentation](https://docs.python.org/3.14/) - [PEP 745](https://peps.python.org/pep-0745/), 3.14 Release Schedule - Report bugs at [ github.com/python/cpython/issues](https://github.com/python/cpython/issues) - [Help fund Python and its community](https://www.python.org/psf/donations/ ) And now for something completely different If you’re heading out to sea, remember the Maritime Approximation: π mph = e knots https://xkcd.com/3023/ Enjoy the new release Thanks to all of the many volunteers who help make Python Development and these releases possible! Please consider supporting our efforts by volunteering yourself or through organisation contributions to the Python Software Foundation. Regards from sunny Helsinki with 19 hours of daylight, Your release team, Hugo van Kemenade Ned Deily Steve Dower Łukasz Langa

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[RELEASE] Python 3.13.5 is now available (yes, really...)
by Thomas Wouters June 11, 2025

June 11, 2025

When I was younger (...hush) we would call this a brown paper bag release, but actually, we shouldn’t hide from our mistakes. We’re only human. So, please enjoy: <https://discuss.python.org/t/python-3-13-5-is-now-available-yes-really/9521…>Python 3.13.5 https://www.python.org/downloads/release/python-3135/ <https://discuss.python.org/t/python-3-13-5-is-now-available-yes-really/9521…>This is the fifth maintenance release of Python 3.13 Python 3.13 is the newest major release of the Python programming language, and it contains many new features and optimizations compared to Python 3.12. 3.13.5 is the fifth maintenance release of 3.13. 3.13.5 is an expedited release to fix a couple of significant issues with the 3.13.4 release: - gh-135151 <https://github.com/python/cpython/issues/135151>: Building extension modules on Windows for the regular (non-free-threaded) build failed. - gh-135171 <https://github.com/python/cpython/issues/135171>: Generator expressions stopped raising TypeError (when iterating over non-iterable objects) at creation time, delaying it to first use. - gh-135326 <https://github.com/python/cpython/issues/135326>: Passing int-like objects (like numpy.int64) to random.getrandbits() failed, when it worked before. Several other bug fixes (which would otherwise have waited until the next release) are also included. Special thanks to everyone who worked hard the last couple of days to fix these issues as quickly as possible. Full Changelog <https://docs.python.org/release/3.13.5/whatsnew/changelog.html#python-3-13-5> <https://discuss.python.org/t/python-3-13-5-is-now-available-yes-really/9521…>More resources - Online Documentation <https://docs.python.org/3.13/> - PEP 719 <https://peps.python.org/pep-0719/>, 3.13 Release Schedule (not that you’ll find this release on there yet.) - Report bugs via GitHub <https://github.com/python/cpython/issues>. - Help fund Python directly <https://www.python.org/psf/donations/python-dev/> (or via GitHub Sponsors <https://github.com/sponsors/python>), and support the Python community <https://www.python.org/psf/donations/>. <https://discuss.python.org/t/python-3-13-5-is-now-available-yes-really/9521…>Stay safe and upgrade! As always, upgrading is highly recommended to all users of 3.13. <https://discuss.python.org/t/python-3-13-5-is-now-available-yes-really/9521…>Enjoy the new releases Thanks to all of the many volunteers who help make Python Development and these releases possible! Please consider supporting our efforts by volunteering yourself or through organization contributions to the Python Software Foundation. Regards from hey, it’s us again, your release team, Thomas Wouters Ned Deily Steve Dower Łukasz Langa

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PyCA cryptography 45.0.4 released
by Alex Gaynor June 10, 2025

June 10, 2025

PyCA cryptography 45.04 has been released to PyPI. cryptography includes both high level recipes and low level interfaces to common cryptographic algorithms such as symmetric ciphers, asymmetric algorithms, message digests, X.509, key derivation functions, and much more. We support Python 3.7+, and PyPy3 7.3.11+. Changelog (https://cryptography.io/en/latest/changelog/#v45-0-4): * Fixed decrypting PKCS#8 files encrypted with SHA1-RC4. (This is not considered secure, and is supported only for backwards compatibility.) Alex -- All that is necessary for evil to succeed is for good people to do nothing.

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ANN: NumExpr 2.11.0, with free-threaded support, is out!
by Francesc Alted June 9, 2025

June 9, 2025

========================= Announcing NumExpr 2.11.0 ========================= Hi everyone, NumExpr 2.11.0 Initial support for free-threaded Python 3.13t has been added. This is still experimental, so please report any issues you find. Finally, Python 3.10 is now the minimum supported version. Project documentation is available at: http://numexpr.readthedocs.io/ Changes from 2.10.2 to 2.11.0 ----------------------------- * Initial support for free-threaded Python 3.13t has been added. This is still experimental, so please report any issues you find. For more info, see discussions PRs #504, #505 and #508. Thanks to @andfoy, @rgommers and @FrancescAlted for the work. * Fix imaginary evaluation in the form of `1.1e1j`. This was previously not supported and would raise an error. Thanks to @27rabbitlt for the fix. * The test suite has been modernized to use `pytest` instead of `unittest`. This should make it easier to run the tests and contribute to the project. * Python 3.10 is now the minimum supported version. What's Numexpr? --------------- Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like "3*a+4*b") are accelerated and use less memory than doing the same calculation in Python. It has multi-threaded capabilities, as well as support for Intel's MKL (Math Kernel Library), which allows an extremely fast evaluation of transcendental functions (sin, cos, tan, exp, log...) while squeezing the last drop of performance out of your multi-core processors. Look here for a some benchmarks of numexpr using MKL: https://github.com/pydata/numexpr/wiki/NumexprMKL Its only dependency is NumPy (MKL is optional), so it works well as an easy-to-deploy, easy-to-use, computational engine for projects that don't want to adopt other solutions requiring more heavy dependencies. Where I can find Numexpr? ------------------------- The project is hosted at GitHub in: https://github.com/pydata/numexpr You can get the packages from PyPI as well (but not for RC releases): http://pypi.python.org/pypi/numexpr Documentation is hosted at: http://numexpr.readthedocs.io/en/latest/ Share your experience --------------------- Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. Enjoy data!

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NumPy 2.3.0 released
by Charles R Harris June 7, 2025

June 7, 2025

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 <https://pypi.org/project/numpy/2.3.0>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v2.3.0>. Cheers, Charles Harris

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ANN: Python Meeting Düsseldorf - 18.06.2025
by eGenix Team June 6, 2025

June 6, 2025

/This announcement is in German since it targets a local user group//meeting in Düsseldorf, Germany/ Ankündigung Python Meeting Düsseldorf - Juni 2025 <https://www.egenix.com/company/news/Python-Meeting-Duesseldorf-2025-06-18> Ein Treffen von Python Enthusiasten und Interessierten in ungezwungener Atmosphäre. *18.06.2025, 18:00 Uhr* Raum 1, 2.OG im Bürgerhaus Stadtteilzentrum Bilk <http://www.duesseldorf.de/jugendamt/fam/famfoe/bueh/ac/index.shtml> Düsseldorfer Arcaden <http://www.duesseldorf-arcaden.de/anfahrt.html>, Bachstr. 145, 40217 Düsseldorf <http://maps.google.com/maps?q=51.209169,6.775339&layer=c&sll=51.209353,6.77…> Programm Bereits angemeldete Vorträge: * Klaus Bremer: *Using Python's argparse * * Jochen Wersdörfer: *MCP Server - Connect LLMs to your data * * Detlef Lannert: *WeasyPrint - Print from HTML/CSS to PDF * * Marc-André Lemburg: *DuckLake - Rethinking Lakehouse architectures* Weitere Vorträge können gerne noch angemeldet werden. Bei Interesse, bitte unter info(a)pyddf.de melden. Startzeit und Ort Wir treffen uns um 18:00 Uhr im Bürgerhaus in den Düsseldorfer Arcaden. Das Bürgerhaus teilt sich den Eingang mit dem Schwimmbad und befindet sich an der Seite der Tiefgarageneinfahrt der Düsseldorfer Arcaden. Über dem Eingang steht ein großes "Schwimm’ in Bilk" Logo. Hinter der Tür direkt links zu den zwei Aufzügen, dann in den 2. Stock hochfahren. Der Eingang zum Raum 1 liegt direkt links, wenn man aus dem Aufzug kommt. >>> Eingang in Google Street View <http://bit.ly/11sCfiw> *⚠️ Wichtig*: Bitte nur dann anmelden, wenn ihr absolut sicher seid, dass ihr auch kommt. Angesichts der begrenzten Anzahl Plätze, haben wir kein Verständnis für kurzfristige Absagen oder No-Shows. Einleitung Das Python Meeting Düsseldorf <http://pyddf.de/> ist eine regelmäßige Veranstaltung in Düsseldorf, die sich an Python Begeisterte aus der Region wendet. Einen guten Überblick über die Vorträge bietet unser PyDDF YouTube-Kanal <http://www.youtube.com/pyddf/>, auf dem wir Videos der Vorträge nach den Meetings veröffentlichen. Veranstaltet wird das Meeting von der eGenix.com GmbH <https://www.egenix.com/>, Langenfeld, in Zusammenarbeit mit Clark Consulting & Research <http://www.clark-consulting.eu/>, Düsseldorf: Format Das Python Meeting Düsseldorf <http://pyddf.de/> nutzt eine Mischung aus (Lightning) Talks und offener Diskussion. Vorträge können vorher angemeldet werden, oder auch spontan während des Treffens eingebracht werden. Ein Beamer mit HDMI und FullHD Auflösung steht zur Verfügung. (Lightning) Talk Anmeldung bitte formlos per EMail an info(a)pyddf.de <mailto:info@pyddf.de?subject=Anmeldung Lightning Talk Python Meeting Düsseldorf> Kostenbeteiligung Das Python Meeting Düsseldorf <http://pyddf.de/> wird von Python Nutzern für Python Nutzer veranstaltet. Da Tagungsraum, Beamer und Getränke Kosten produzieren, bitten wir die Teilnehmer um einen Beitrag in Höhe von EUR 10,00 inkl. 19% Mwst. Schüler und Studenten zahlen EUR 5,00 inkl. 19% Mwst. Wir möchten alle Teilnehmer bitten, den Betrag in bar mitzubringen. Anmeldung Da wir nur 25 Personen in dem angemieteten Raum empfangen können, möchten wir bitten, sich vorher anzumelden. *Meeting Anmeldung* bitte per Meetup <https://www.meetup.com/Python-Meeting-Dusseldorf/> Weitere Informationen Weitere Informationen finden Sie auf der Webseite des Meetings: https://pyddf.de/ Viel Spaß ! -- Marc-Andre Lemburg eGenix.com Professional Python Services directly from the Experts (#1, Jun 06 2025) >>> Python Projects, Coaching and Support ... https://www.egenix.com/ >>> Python Product Development ... https://consulting.egenix.com/ ________________________________________________________________________ ::: We implement business ideas - efficiently in both time and costs ::: eGenix.com Software, Skills and Services GmbH Pastor-Loeh-Str.48 D-40764 Langenfeld, Germany. CEO Dipl.-Math. Marc-Andre Lemburg Registered at Amtsgericht Duesseldorf: HRB 46611 https://www.egenix.com/company/contact/ https://www.malemburg.com/

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