Mailman 3 January 2022 - Python-announce-list

[RELEASE] Black formatter 22.1.0
by Felix Hildén Jan. 29, 2022

Jan. 29, 2022

I'm pleased to announce that Black, The uncompromising code formatter, is finally non-beta software! Here's the full changelog: https://black.readthedocs.io/en/stable/change_log.html Going forward we'll follow our stability policy. Work continues as usual with bugfixes and enhancements, but style changes are now introduced under our new `--preview` CLI switch. This allows us to evolve Black's style without too much disruption to users that want consistency. The default style is updated yearly. Thanks to our maintainers for orchestrating the efforts, especially to our most recent reinforcement Batuhan (@isidentical) who was responsible for our match statement support! A hearty thank you to all of our contributors for pushing Black forward, and to our users for being the reason we do it! You can reach us on our issue tracker: https://github.com/psf/black <P><A HREF="https://black.readthedocs.io"> Black - 22.1.0</A> - the uncompromising code formatter (29-Jan-22)

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ANN: Austin -- CPython frame stack sampler v3.3.0 is now available
by Gabriele Tornetta Jan. 28, 2022

Jan. 28, 2022

I am delighted to announce the release 3.3.0 of Austin. If you haven't heard of Austin before, it is an open-source frame stack sampler for CPython, distributed under the GPLv3 license. It can be used to obtain statistical profiling data out of a running Python application without a single line of instrumentation. This means that you can start profiling a Python application straight away, even while it's running in a production environment, with minimal impact on performance. https://github.com/P403n1x87/austin The best way to leverage Austin is to use the new extension for VS Code, which brings interactive flame graphs straight into the text editor to allow you to quickly jump to the source code with a simple click. You can find the extension on the Visual Studio Marketplace and install it directly from VS Code: https://marketplace.visualstudio.com/items?itemName=p403n1x87.austin-vscode To see how to make the best of Austin with VS Code to find and fix performance issues, check out this blog post, which shows you the editor extension in action on a real Python project: https://p403n1x87.github.io/how-to-bust-python-performance-issues.html The latest release comes with the new -w\--where option that allows extracting the current frame stack from a running Python application https://github.com/P403n1x87/austin#where This new mode is also available for the austinp variant and works with the `-k` switch to also provide the Linux kernel stacks https://github.com/P403n1x87/austin#native-frame-stack And speaking of which, the `austinp` variant has reached a good level of stability and it is now being built as part of the normal Austin `autotools` build process. This means that it is made available through the Snap Store as part of the main Austin package. For those that have not heard of the `austinp` variant before, it is a `ptrace`-based variant of Austin that allows sampling native and kernel frame stacks on Linux, which are then interleaved with the ordinary Python frame stacks for sensible in-depth observability into the performance of Python applications. The new release also comes with a substantial performance improvement thanks to frame caching, which dramatically reduces the number of calls to system calls for inspecting the Python VM address space. This translates in higher achievable sampling rates and accuracy. Support for the various supported platform has also been improved. Worth mentioning is the support for the `py.exe` launcher on Windows. Austin is a pure C application that has no dependencies other than the C standard library. Its source code is hosted on GitHub at https://github.com/P403n1x87/austin The README contains installation and usage details, as well as some examples of Austin in action. Details on how to contribute to Austin's development can be found at the bottom of the page. Austin can be installed easily on the following platforms and from the following sources: Linux: - Snap Store - AUR - Conda Forge macOS: - Homebrew - Conda Forge Windows: - Chocolatey - Scoop An Austin docker image, based on Ubuntu 20.04, is also available from Docker Hub: https://hub.docker.com/r/p403n1x87/austin Austin is also simple to compile from sources as it only depends on the standard C library, if you don't have access to the above-listed sources. You can stay up-to-date with the project's development by following Austin on Twitter (https://twitter.com/AustinSampler). Austin is a free and open-source project. A lot of effort goes into its development to ensure the best performance and that it stays up-to-date with the latest Python releases. If you find it useful, consider sponsoring this project on GitHub at https://github.com/sponsors/P403n1x87. All the best, Gabriele <phoenix1987 (at) gmail.com> <p><a href="https://github.com/P403n1x87/austin">Austin 3.2.0</a> - frame stack sampler for CPython. (28-Jan-22)</p>

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[ANN] Numba 0.55.1
by Valentin Haenel Jan. 28, 2022

Jan. 28, 2022

Dear *, on behalf of the Numba team, I am happy to announce that Numba 0.55.1 has become available! This is a bugfix release that closes all the remaining issues from the accelerated release of 0.55.0 and also any release critical regressions discovered since then. For more information, please point your browsers at: https://numba.discourse.group/t/ann-numba-0-55-1/1161 Best, V-

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pymssql 2.2.4 released
by Mikhail Jan. 24, 2022

Jan. 24, 2022

Hello, I’m happy to announce the release of pymssql 2.2.4, available to download via pip and GitHub. Pymssql is a simple database interface for Python that builds on top of FreeTDS to provide a Python DB-API (PEP-249) interface to Microsoft SQL Server. The official documentation is available at: https://pymssql.readthedocs.io The sources, discussions and bug tracker: https://github.com/pymssql/pymssql. Below please see the changes since last announcement. Enjoy, Mikhail Version 2.2.4 - 2022-01-23 - Mikhail Terekhov ============================================= General ------- - Build wheels for Python-3.10 on Linux. - Fix include paths in setup.py.

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Numba 0.55.0 and llvmlite 0.38.0 are out!
by Valentin Haenel Jan. 17, 2022

Jan. 17, 2022

Dear all, 0.55.0 and llvmlite 0.38.0 have been released. Please point your browsers at our discourse for more information: https://numba.discourse.group/t/numba-0-55-0-and-llvmlite-0-38-0-final-rele… Best, V-

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[RELEASE] Python 3.10.2, 3.9.10, and 3.11.0a4 are now available
by Łukasz Langa Jan. 14, 2022

Jan. 14, 2022

Hi there, before we begin the usual round of release notes, please do note that the three new versions of Python released today do not contain Windows installers yet. This is temporary, due to a more complex than expected code signing certificate renewal. We’ve held the releases all week while the situation is getting resolved but the urgency of 3.10.2 in particular made us release without the Windows installers after all. We apologize for the inconvenience and are doing everything we can to put the Windows installer in place as soon as possible. We’re rooting for both Ee Durbin and Steve Dower who are helping us resolve this. Thanks for your hard work! Hopefully, by this time next week, this will only be a footnote in release management history. The releases you’re looking at were all cursed in some way. What a way to start 2022! Besides the certificate hold up, Python 3.10.2 is an expedited release (you’ll want to upgrade, read below!), Python 3.11.0a4 had almost 20 (sic, twenty!) release blockers before being finally green, and Python 3.9.10 was made from a new M1 Mac on macOS Monterey which made the usually boring process quite a ride. We’re hoping 2022 won’t be this intense all year! <https://discuss.python.org/t/python-3-10-2-3-9-10-and-3-11-0a4-are-now-avai…>Python 3.10.2 Get it here: https://www.python.org/downloads/release/python-3102/ <https://www.python.org/downloads/release/python-3102/> <https://www.blogger.com/#> This is a special bugfix release ahead of schedule to address a memory leak that was happening on certain function calls when using Cython <https://github.com/cython/cython>. The memory leak consisted of a small constant amount of bytes in certain function calls from Cython code. Although in most cases this was not very noticeable, it was very impactful for long-running applications and certain usage patterns. Check bpo-46347 <https://bugs.python.org/issue46347> for more information. Upgrading existing Python 3.10 installations is highly recommended. Even though this is an expedited release, it still contains over 100 other bug fixes. See the change log <https://docs.python.org/release/3.10.2/whatsnew/changelog.html> for details. The next Python 3.10 maintenance release will be 3.10.3, currently scheduled for 2022-04-04. <https://discuss.python.org/t/python-3-10-2-3-9-10-and-3-11-0a4-are-now-avai…>Python 3.9.10 Get it here: https://www.python.org/downloads/release/python-3910/ <https://www.blogger.com/#> Python 3.9.10 is the ninth maintenance release of the legacy 3.9 series. Note: Python 3.10 is now the latest feature release series of Python 3. Python 3.9 micro-releases enter double digits! There’s been 130 commits since 3.9.9 which is a higher number of fixes for this stage of the life cycle compared to 3.8. See the changelog <https://docs.python.org/release/3.9.10/whatsnew/changelog.html> for details on what changed. As a reminder, on macOS, the default installer is now the new universal2 variant. It’s compatible with Mac OS X 10.9 and newer, including macOS 11 Big Sur and macOS 12 Monterey. Python installed with this variant will work natively on Apple Silicon processors. The next Python 3.9 maintenance release will be 3.9.11, currently scheduled for Pi Day '22 (2022-03-14). <https://discuss.python.org/t/python-3-10-2-3-9-10-and-3-11-0a4-are-now-avai…>Python 3.11.0a4 Get it here: https://www.python.org/downloads/release/python-3110a4/ <https://www.blogger.com/#> Python 3.11 is still in development. This release, 3.11.0a4, is the fourth of seven planned alpha releases. Alpha releases are intended to make it easier to test the current state of new features and bug fixes by the community, as well as to test the release process. During the alpha phase, features may be added up until the start of the beta phase (2022-05-06) and, if necessary, may be modified or deleted up until the release candidate phase (2022-08-01). Please keep in mind that this is a preview release and its use is not recommended for production environments. Many new features for Python 3.11 are still being planned and written. Among the new major new features and changes so far: PEP 657 <https://www.python.org/dev/peps/pep-0657/> – Include Fine-Grained Error Locations in Tracebacks PEP 654 <https://www.python.org/dev/peps/pep-0654/> – Exception Groups and except* The Faster CPython Project <https://github.com/faster-cpython> is already yielding some exciting results: this version of CPython 3.11 is ~ 19% faster on the geometric mean of the PyPerformance benchmarks <>, compared to 3.10.0. (Hey, fellow core developer, if a feature you find important is missing from this list, let Pablo know <mailto:pablogsal@python.org>.) The next pre-release of Python 3.11 will be 3.11.0a5, currently scheduled for Wednesday, 2022-02-02. <https://discuss.python.org/t/python-3-10-2-3-9-10-and-3-11-0a4-are-now-avai…>Python 3.6 is pining for the fjords Python 3.6 is no more. It’s an ex-Python. It has ceased to be. On December 23rd 2021 is has reached its end-of-life phase <https://www.python.org/dev/peps/pep-0494/> after five successful years. It’s been the first truly popular Python 3 release, introducing f-strings to the world and making big improvements to both asyncio (async generators!) and typing (variable annotations!). We’d like to congratulate Ned Deily @nad <https://discuss.python.org/u/nad> on successfully driving the 3.6 series to completion as Release Manager. He’s not fully retired yet, as 3.7, which he is also managing, is still receiving security patches until June 2023. <https://discuss.python.org/t/python-3-10-2-3-9-10-and-3-11-0a4-are-now-avai…>We hope you enjoy the new releases Your friendly release team, Pablo Galindo Salgado @pablogsal <https://discuss.python.org/u/pablogsal> Łukasz Langa @ambv <https://discuss.python.org/u/ambv>

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NumPy 1.22.1 has been released.
by Charles R Harris Jan. 14, 2022

Jan. 14, 2022

Hi All, On behalf of the NumPy team, I'm pleased to announce the release of NumPy 1.22.1. NumPy 1.22.1 fixes several bugs discovered after the 1.22.0 release. Notable fixes are: - Fix for f2PY docstring problems (SciPy) - Fix for reduction type problems (AstroPy) - Fixes for various typing bugs. The Python versions supported in this release are 3.8-3.10. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/1.22.1>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v1.22.1>. Linux users will need pip >= 0.19.3 in order to install the manylinux2014 wheels. A recent version of pip is needed to install the universal2 macos wheels. *Contributors* A total of 14 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Arryan Singh - Bas van Beek - Charles Harris - Denis Laxalde - Isuru Fernando - Kevin Sheppard - Matthew Barber - Matti Picus - Melissa Weber Mendonça - Mukulika Pahari - Omid Rajaei + - Pearu Peterson - Ralf Gommers - Sebastian Berg *Pull requests merged* A total of 20 pull requests were merged for this release. - #20702: MAINT, DOC: Post 1.22.0 release fixes. - #20703: DOC, BUG: Use pngs instead of svgs. - #20704: DOC: Fixed the link on user-guide landing page - #20714: BUG: Restore vc141 support - #20724: BUG: Fix array dimensions solver for multidimensional arguments... - #20725: TYP: change type annotation for ``__array_namespace__`` to ModuleType - #20726: TYP, MAINT: Allow ``ndindex`` to accept integer tuples - #20757: BUG: Relax dtype identity check in reductions - #20763: TYP: Allow time manipulation functions to accept ``date`` and ``timedelta``... - #20768: TYP: Relax the type of ``ndarray.__array_finalize__`` - #20795: MAINT: Raise RuntimeError if setuptools version is too recent. - #20796: BUG, DOC: Fixes SciPy docs build warnings - #20797: DOC: fix OpenBLAS version in release note - #20798: PERF: Optimize array check for bounded 0,1 values - #20805: BUG: Fix that reduce-likes honor out always (and live in the... - #20806: BUG: ``array_api.argsort(descending=True)`` respects relative... - #20807: BUG: Allow integer inputs for pow-related functions in ``array_api`` - #20814: DOC: Refer to NumPy, not pandas, in main page - #20815: DOC: Update Copyright to 2022 [License] - #20819: BUG: Return correctly shaped inverse indices in array_api set... Cheers, Charles Harris

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NumPy 1.22.0 has been released
by Charles R Harris Jan. 1, 2022

Jan. 1, 2022

Hi All, On behalf of the NumPy team, I'm pleased to announce the release of NumPy 1.22.0. NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are: - Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release. - A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across applications such as CuPy and JAX. - NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data. - New methods for `quantile`, `percentile`, and related functions. The new methods provide a complete set of the methods commonly found in the literature. - A new configurable allocator for use by downstream projects. These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation. The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/1.22.0/>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v1.22.0>. Linux users will need pip >= 0.19.3 in order to install the manylinux2014 wheels. A recent version of pip is needed to install the universal2 macos wheels. *Contributors* A total of 153 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - @DWesl - @Illviljan - @h-vetinari - @yan-wyb + - Aaron Meurer - Abel Aoun + - Adrian Gao + - Ahmet Can Solak + - Ajay DS + - Alban Colley + - Alberto Rubiales + - Alessia Marcolini + - Amit Kumar + - Andrei Batomunkuev + - Andrew Watson + - Anirudh Dagar + - Ankit Dwivedi + - Antony Lee - Arfy Slowy + - Arryan Singh + - Arun Palaniappen + - Arushi Sharma + - Bas van Beek - Brent Brewington + - Carl Johnsen + - Carl Michal + - Charles Harris - Chiara Marmo - Chris Fu (傅立业) + - Christoph Buchner + - Christoph Reiter + - Chunlin Fang - Clément Robert + - Constanza Fierro - Damien Caliste - Daniel Ching - David Badnar + - David Cortes + - David Okpare + - Derek Huang + - Developer-Ecosystem-Engineering + - Dima Pasechnik - Dimitri Papadopoulos + - Dmitriy Fishman + - Eero Vaher + - Elias Koromilas + - Eliaz Bobadilla + - Elisha Hollander + - Eric Wieser - Eskild Eriksen + - Evan Miller + - Fayas Noushad + - Gagandeep Singh + - Ganesh Kathiresan - Ghiles Meddour + - Greg Lucas - Gregory R. Lee - Guo Shuai + - Gwyn Ciesla + - Hameer Abbasi - Hector Martin + - Henry Schreiner + - Himanshu + - Hood Chatham + - Hugo Defois + - Hugo van Kemenade - I-Shen Leong + - Imen Rajhi + - Irina Maria Mocan + - Irit Katriel + - Isuru Fernando - Jakob Jakobson - Jerry Morrison + - Jessi J Zhao + - Joe Marshall + - Johan von Forstner + - Jonas I. Liechti + - Jonathan Reichelt Gjertsen + - Joshua Himmens + - Jérome Eertmans - Jérôme Kieffer + - KIU Shueng Chuan + - Kazuki Sakamoto + - Kenichi Maehashi - Kenny Huynh + - Kent R. Spillner + - Kevin Granados + - Kevin Modzelewski + - Kevin Sheppard - Lalit Musmade + - Malik Idrees Hasan Khan + - Marco Aurelio da Costa + - Margret Pax + - Mars Lee + - Marten van Kerkwijk - Matthew Barber + - Matthew Brett - Matthias Bussonnier - Matthieu Dartiailh - Matti Picus - Melissa Weber Mendonça - Michael McCann + - Mike Jarvis + - Mike McCann + - Mike Toews - Mukulika Pahari - Nick Pope + - Nick Wogan + - Niels Dunnewind + - Niko Savola + - Nikola Forró - Niyas Sait + - Pamphile ROY - Paul Ganssle + - Pauli Virtanen - Pearu Peterson - Peter Hawkins + - Peter Tillema + - Prathmesh Shirsat + - Raghuveer Devulapalli - Ralf Gommers - Robert Kern - Rohit Goswami + - Ronan Lamy - Ross Barnowski - Roy Jacobson + - Samyak S Sarnayak + - Sayantika Banik + - Sayed Adel - Sebastian Berg - Sebastian Schleehauf + - Serge Guelton - Shriraj Hegde + - Shubham Gupta + - Sista Seetaram + - Stefan van der Walt - Stephannie Jimenez Gacha + - Tania Allard - Theodoros Nikolaou + - Thomas Green + - Thomas J. Fan - Thomas Li + - Tim Hoffmann - Tom Tan + - Tyler Reddy - Vijay Arora + - Vinith Kishore + - Warren Weckesser - Yang Hau - Yashasvi Misra - Yuval Ofek + - Zac Hatfield-Dodds - Zhang Na + Cheers, Charles Harris

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