Mailman 3 February 2026 - Python-announce-list

Announcing delb 0.6, a Python library for XML encoded text
by delb project Feb. 22, 2026

Feb. 22, 2026

I'm happy to announce the release of *delb* 0.6 that marks a significant milestone for the project. It was started as an experimental prototype out of frustration with the available Python tools to process XML encoded textual data, namely those according to the guidelines of the *Text Encooding Initiative*, and was thus named by the abbreviation for *Donde esta la biblioteca?* This newest incarnation is a completely native implementation of its data model with a matured and stable API. The functional extent is kept low-level enough to build further XML related tools and domain specific applications with it. The current main selling points at a glance are: - XML DOM types are represented by distinct classes. - A completely type-annotated API with consistent naming and callables’ signatures. - Loads documents from various source types. - Easy, simply filterable traversing of a document in all directions staring from any node. - Shadows comments and processing instructions by default. - Querying with XPath and CSS expressions. - Serializations that may fulfil the promise of XML’s well-readability to an unwitnessed degree and even don’t mess up whitespace. - Optional whitespace handling per TEI recommendation. - Various customization opportunities (document loaders & representations, XML parser, XPath functions). - It’s well tested. PyPI: https://pypi.org/project/delb Documentation: https://delb.readthedocs.io/0.6/ Also recommended to check out are: - An extension to interact with eXist-db instances: https://pypi.org/project/delb-existdb/ - Danny Pudi's & Donald Glover's performance: https://www.youtube.com/watch?v=j2IDOMuHpWY Feel free to forward this email to interested engineers in the field of Digital Humanities and please excuse redundant deliveries. Best regards, Frank

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[ANN] PyData/Sparse 0.18.0 released
by Hameer Abbasi Feb. 19, 2026

Feb. 19, 2026

PyData/Sparse is a library providing N-dimensional sparse arrays for the PyData ecosystem. This release focuses on expanded array API compatibility, developer experience, and QoL fixes. Repo: https://github.com/pydata/sparse Docs: https://sparse.pydata.org/en/0.18.0/ Issue Tracker: https://github.com/pydata/sparse/issues Changelog What's Changed * Implementing `repeat` function by @prady0t in https://github.com/pydata/sparse/pull/875 * Adding `tile` function by @prady0t in https://github.com/pydata/sparse/pull/880 * Setting `boolean indexing` flag to False by @prady0t in https://github.com/pydata/sparse/pull/884 * Adding `unstack` function by @prady0t in https://github.com/pydata/sparse/pull/883 * Fixing `check_zero_fill_value` by @prady0t in https://github.com/pydata/sparse/pull/886 * Running codecov only when tests pass by @prady0t in https://github.com/pydata/sparse/pull/887 * Adding `diff` function by @prady0t in https://github.com/pydata/sparse/pull/888 * Making benchmarking tests deterministic by @prady0t in https://github.com/pydata/sparse/pull/891 * Migration guide by @hameerabbasi in https://github.com/pydata/sparse/pull/898 * Lock mlir to python <3.14 by @prady0t in https://github.com/pydata/sparse/pull/906 * feat: Add sparse.interp function for numba backend by @peanutfun in https://github.com/pydata/sparse/pull/903 * Update Finch notebook by @mtsokol in https://github.com/pydata/sparse/pull/911 * BUG: asarray: fix default format for `SparseArray` input by @lucascolley in https://github.com/pydata/sparse/pull/918 * [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/pydata/sparse/pull/916 * BLD/DEV/CI: better Pixi setup by @lucascolley in https://github.com/pydata/sparse/pull/920 * ENH: transition to SciPy sparse arrays from matrices by @lucascolley in https://github.com/pydata/sparse/pull/919 * DEV/CI: use Pixi for examples, notebooks, and xp-tests by @lucascolley in https://github.com/pydata/sparse/pull/922 New Contributors * @peanutfun made their first contribution in https://github.com/pydata/sparse/pull/903 * @lucascolley made their first contribution in https://github.com/pydata/sparse/pull/918 Full Changelog: https://github.com/pydata/sparse/compare/0.17.0...0.18.0

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TatSu v5.17.0
by Juancarlo Añez Feb. 16, 2026

Feb. 16, 2026

竜 TatSu is a tool that takes grammars in a superset of EBNF as input, and outputs memoizing (Packrat) PEG parsers in Python. The classic variations of EBNF (Tomassetti, EasyExtend, Wirth) and ISO EBNF are also supported as input grammar format. The Overdue Major Refactoring ------------------------------------------ Maintenance and contributions to TatSu have been more difficult than necessary because of the way the code evolved through its lifetime. - Very long modules and classes that try to do too much - Algorithms difficult to understand or with incorrect semantics - Basic features missing, because the above made them hard to implement This release is a major refactoring of the code in TatSu. - Complex modules were partitioned into sub-modules and classes with well-defined purpose - Several algorithms were rewritten to make their semantics clear and evident, and their implementation more efficient - Many unit tests were added to assert the semantics of complex algorithms - Several user-facing features were added as they became easier to implement For the details about the many changes please take a look at the commit log. - pypi: https://pypi.org/project/TatSu/ - docs: https://tatsu.readthedocs.io/ - repo: https://github.com/neogeny/TatSu Every effort has been made to preserve backwards compatibility by keeping most unit tests intact and testing with projects with large grammars and complex processing. If something escaped those tests, there will be a bugfix release with the fixes soon enough. User-Facing Changes - The TatSu documentation has been improved and expanded, and it has a better look&feel with improved navigation. - TatSu doesn’t care about file names, but the default extension used in unit tests, examples, and documentation for grammars is now .tatsu - EBNF, both ISO and the classic variations, is fully supported as grammar input format - Now tatsu.parse(...., asmodel=True) produces a model that matches the ::Type declarations in their grammar (see the models documentation for a thorough review of the features). - walkers.NodeWalker now handles all known types of input. Also: - DepthFirstWalker was reimplemented to ensure DFS semantics - PostOrderDepthFirstWalker walks children before parents - PreOrderWalker was broken and crazy. It was rewritten as a BreadthFirstWalker with the correct semantics - Constant expressions in a grammar are now evaluated deeply with multiple passes of eval() as to produce results that are intuitively correct: def test_constant_math(): grammar = r""" start = a:`7` b:`2` @:```{a} / {b}``` $ ; """ result = parse(grammar, '', trace=True) assert result == 3.5 - Evaluation of Python expressions by the parsing engine now use safe_eval(), a hardened firewall around most security attacks targeting eval() (see the safeeval module for details) - Because None is a valid initial value for attributes and a frequent return value for callables, the required logic for undefined values was moved to the notnone module, which declares Undefined as an alias for notnone.NotNone In [1]: from tatsu.util.undefined import Undefined In [2]: u = Undefined In [3]: u is None Out[3]: False In [4]: u is Undefined Out[4]: True In [5]: Undefined is None Out[5]: False In [6]: d = u or 'OK' In [7]: d Out[7]: 'OK' - objectmodel.Node was rewritten to give it clear semantics and efficiency - New attributes to Node after initialization generate a warning if the name of a method is being shadowed. This change avoids confusing @dataclass, which is used in generated object models. - Node equality is explicitly defined as object identity. No attempts are made at comparing Node structurally. - Node.children() has the expected semantics, and is much more efficient. - Node.parseinfo is now honored by the parsing engine (previously, only results of type AST could have a parseinfo). Generation of parseinfo is disabled by default, and is enabled by passing pareseinfo=True to the API entry points. def test_node_parseinfo(self): grammar = """ @@grammar :: Test start::Test = true | false ; true = "test" @:`True` $; false = "test" @:`False` $; """ text = 'test' node = tatsu.parse(grammar, text, asmodel=True, parseinfo=True, ) assert type(node).__name__ == 'Test' assert node.ast is True assert node.parseinfo is not None assert node.parseinfo.pos == 0 assert node.parseinfo.endpos == len(text) - Synthetic classes created by synth.synthetize() during parsing with ModelBuilderSemantics behave more consistently, and now have a base class of class SynthNode(BaseNode) - Now ast.AST has consistent semantics of a dict that allows access to contents using the attribute interface - asjson() and friends now cover all known cases with improved consistency and efficiency, so there are less demands over clients of the API - Entry points no longer list a large subset of the configuration options defined in ParserConfig, but still accept them through **settings keyword arguments. Now ParserConfig verifies that the settings passed to are valid, eliminating the frustration of passing an incorrect setting name (a typo) and hoping it has the intended effect. - TatSu still has no library dependencies for its core functionality, but several libraries are used during its development and testing. The TatSu development configuration uses uv and hatch. Several requirements-xyz.txt files are generated in favor of those using pip with pyenv, virtualenvwrapper, or virtualenv - All attempts at recovering comments from parsed input were removed. It never worked, so it had no use. Comment recovery may be attempted in the future. - All pre-existing grammars are compatible with this version of TatSu. - Previously generated Python parsers and models, work with this version of TatSu, yet you should consider generating them anew to take advantage of the improved speed, layout, and features. - CAVEAT: Several functions, methods, and argument names were deprecated. They can still be used, but warnings will be issued at runtime. - CAVEAT: If there are invalid strings or regex patterns in your grammars YOU MUST fix them because now the grammar parser validates strings and patterns. - Many of the functions that TatSu defines for its own use are useful in other contexts. Some examples are: from tatsu.safeeval import is_eval_safe from tatsu.safeeval import hasshable from tatsu.safeeval import make_hashable from tatsu.util import safe_name from tatsu.util.misc import find_from_rematch from tatsu.util.misc import topsort from tatsu.util.undefined import Undefined # ... ----------------------------------------------------------------------------------------------- -- Juancarlo Añez mailto:apalala@gmail.com

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Subject: [ANN] tklr — local, keyboard-first tickler file (0.0.51)
by Daniel Graham Feb. 14, 2026

Feb. 14, 2026

Hello, I'm pleased to announce tklr, a local reminder system inspired by the classic tickler file. You enter reminders in plain text; tklr parses dates, recurrence, and metadata as you type, then ranks tasks by urgency and goals by priority. Highlights: - Form-free entry with live prompts (no forms to fill) - CLI and Textual UI with mouse-free navigation - Multiple reminder types: events, tasks, projects, goals, notes, jots, drafts - Flexible scheduling with fuzzy dates, recurrence, and time zones - Organized views (Agenda, Next/Last, Queries, bins, hashtags) Install: pip install -U tklr-dgraham pipx install tklr-dgraham Example entry: * lunch with Ed @s 12p fri @e 1h30m @a 15m: n Links: PyPI: https://pypi.org/project/tklr-dgraham/ GitHub: https://github.com/dagraham/tklr-dgraham Docs: https://dagraham.github.io/tklr-dgraham/ Demo: https://raw.githubusercontent.com/dagraham/tklr-dgraham/master/screenshots/… License: GPL-3.0-or-later Version: 0.0.51 Contact: Daniel Graham <dnlgrhm(a)gmail.com> Follow-ups: GitHub Discussions or email <P><A HREF="https://dagraham.github.io/tklr-dgraham/">tklr 0.0.51</A> - local, keyboard-first tickler file reminder system with CLI and Textual UI. (14-Feb-26) Daniel Graham

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PyCA cryptography 46.0.5 released
by Paul Kehrer Feb. 10, 2026

Feb. 10, 2026

PyCA cryptography 46.0.0 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 3.8+, and PyPy3 3.11. Changelog (https://cryptography.io/en/latest/changelog/#v46-0-5) * An attacker could create a malicious public key that reveals portions of your private key when using certain uncommon elliptic curves (binary curves). This version now includes additional security checks to prevent this attack. This issue only affects binary elliptic curves, which are rarely used in real-world applications. Credit to **XlabAI Team of Tencent Xuanwu Lab and Atuin Automated Vulnerability Discovery Engine** for reporting the issue. **CVE-2026-26007** * Support for SECT binary elliptic curves is deprecated and will be removed in the next release. -Paul Kehrer (reaperhulk)

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18ᵗʰ Advanced Scientific Programming in Python in Prague, Czechia, 30 August – 06 September 2026
by Tiziano Zito Feb. 8, 2026

Feb. 8, 2026

ASPP2026: 18ᵗʰ Advanced Scientific Programming in Python Summer School ====================================================================== https://aspp.school Scientists spend a significant amount of time writing, maintaining and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. They end up being overwhelmed by the coding challenges they face and keep re-inventing the wheel. In the hope to free more time for research they increasingly rely on generative AI, which may produce runnable code without the need to fully understand it. Such code can neither be reused nor trusted to work correctly and, as a result, scientists are hesitant to share it and publish it. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist. Lectures are interactive and allow participants to acquire direct hands-on experience with the topics. Participants will work in pairs throughout the school and will team up to practice the newly learned skills in a real programming project — an entertaining computer game. We use the Python programming language for the entire course. This school is targeted at PhD students, postdocs and more senior researchers from all fields, who do a lot of programming in their academic life, but were never taught how to do so properly. Competence in programming and basic knowledge of Python and git is assumed. Participants are required to work through the proposed introductory material before. 🌈 We strive for a welcoming and sociable atmosphere for scientists from all walks of life. In particular, we focus on recruiting an international and gender-balanced pool of students. Date & Location =============== 30 August – 06 September, 2026. Prague Czechia Czechia Application =========== You can apply online: https://aspp.school Application deadline: 23:59 UTC, Sunday 03 May 2026. There will be no deadline extension, so be sure to apply on time. Invitations and notifications of rejection will be sent by Sunday 24 May, 2026. Participation is for free, i.e. no fee is charged! Participants however should take care of travel, living, and accommodation expenses by themselves. Program ======= • Large-scale collaborative scientific code development with git and code forges • Testing and debugging scientific code • Organizing, documenting, and distributing scientific code • Data in scientific programming • Scientific programming patterns in Python • What every scientist should know about computer architecture • Writing parallel applications in Python • Programming in teams Faculty ======= • Aitor Morales-Gregorio, Faculty of Mathematics and Physics, Charles University, Prague, Czechia • Anna-Lena Eckert, Translational Computational Psychiatry Group, University College London, UK • Carlos Cernuda, Data Analysis and Cybersecurity, Mondragon Unibertsitatea, Bilbao, Spain • Guillermo Aguilar, Department of Computational Psychology, Technische Universität Berlin, Germany • Jenni Rinker, Department of Wind and Energy Systems, Technical University of Denmark, Lyngby, Denmark • Lisa Schwetlick, Laboratoire des Systèmes Perceptifs, École Normale Supérieure, Paris, France • Pamela Hathway, freelance consultant, Nürnberg, Germany • Pietro Berkes, NAGRA Kudelski, Lausanne, Switzerland • Rike-Benjamin Schuppner, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Germany • Tiziano Zito, Compilers and Programming Languages, Technische Universität Berlin, Germany • Verjinia Metodieva, Charité–Universitätsmedizin and Einstein Center for Neurosciences Berlin, Germany • Zbigniew Jędrzejewski-Szmek, Amutable GmbH, Warsaw, Poland Organizers ========== Head of the organization for ASPP and responsible for the scientific program: • Tiziano Zito, Compilers and Programming Languages, Technische Universität Berlin, Germany Organization team in Prague: • Aitor Morales-Gregorio, Faculty of Mathematics and Physics, Charles University, Prague, Czechia Funding and Sponsors ==================== ASPP2026 is hosted by the Faculty of Mathematics and Physics of the Charles University in Prague, Czechia. Website: https://aspp.school Contact: info(a)aspp.school

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JustHTML 1.6.0 released
by Emil Stenström Feb. 7, 2026

Feb. 7, 2026

Subject: JustHTML 1.6.0 — pure-Python HTML5 parser (CSS selectors + sanitizer) Install: pip install justhtml Repo: https://github.com/EmilStenstrom/justhtml Docs: https://emilstenstrom.github.io/justhtml/ Example (CSS selectors): from justhtml import JustHTML doc = JustHTML("<div><p class='x'>Hi</p><p>Bye</p></div>", fragment=True) print(doc.query_one("div p.x").to_html(pretty=False)) # <p class="x">Hi</p> License: MIT Contact: emil(a)emilstenstrom.se <P><A HREF="https://emilstenstrom.github.io/justhtml/">JustHTML 1.6.0</A> - Pure-Python HTML5 parser with CSS selectors and built-in sanitization. (07-Feb-26) -- Emil Stenström

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ANN: psutil 7.2.2 released
by Giampaolo Rodola' Feb. 2, 2026

Feb. 2, 2026

Hello all, I'm glad to announce the release of psutil 7.2.2: https://github.com/giampaolo/psutil See blog post: https://gmpy.dev/blog/2026/event-driven-process-waiting About ===== psutil (process and system utilities) is a cross-platform library for retrieving information on running processes and system utilization (CPU, memory, disks, network) in Python. It is useful mainly for system monitoring, profiling and limiting process resources and management of running processes. It implements many functionalities offered by command line tools such as: ps, top, lsof, netstat, ifconfig, who, df, kill, free, nice, ionice, iostat, iotop, uptime, pidof, tty, taskset, pmap. It currently supports Linux, Windows, macOS, Sun Solaris, FreeBSD, OpenBSD, NetBSD and AIX. Supported Python versions are cPython 3.6+ and PyPy. What's new ========== 2026-01-28 **Enhancements** - #2705: [Linux]: `Process.wait()`_ now uses ``pidfd_open()`` + ``poll()`` for waiting, resulting in no busy loop and faster response times. Requires Linux >= 5.3 and Python >= 3.9. Falls back to traditional polling if unavailable. - #2705: [macOS], [BSD]: `Process.wait()`_ now uses ``kqueue()`` for waiting, resulting in no busy loop and faster response times. **Bug fixes** - #2701, [macOS]: fix compilation error on macOS < 10.7. (patch by Sergey Fedorov) - #2707, [macOS]: fix potential memory leaks in error paths of `Process.memory_full_info()` and `Process.threads()`. - #2708, [macOS]: Process.cmdline()`_ and `Process.environ()`_ may fail with ``OSError: [Errno 0] Undefined error`` (from ``sysctl(KERN_PROCARGS2)``). They now raise `AccessDenied`_ instead. Links ===== - Home page: https://github.com/giampaolo/psutil - Download: https://pypi.org/project/psutil/#files - Documentation: http://psutil.readthedocs.io - What's new: https://github.com/giampaolo/psutil/blob/master/HISTORY.rst Hashes ====== psutil-7.2.2-cp313-cp313t-macosx_10_13_x86_64.whl md5: 6d6c68458477db71083d3655ec3f18a9 sha256: 2edccc433cbfa046b980b0df0171cd25bcaeb3a68fe9022db0979e7aa74a826b psutil-7.2.2-cp313-cp313t-macosx_11_0_arm64.whl md5: 380d9ace49206f778b6bce3eaca14474 sha256: e78c8603dcd9a04c7364f1a3e670cea95d51ee865e4efb3556a3a63adef958ea psutil-7.2.2-cp313-cp313t-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl md5: a65aff021780d111143fd7354a36b504 sha256: 1a571f2330c966c62aeda00dd24620425d4b0cc86881c89861fbc04549e5dc63 psutil-7.2.2-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl md5: cf8ee1368435bf0b42ce032f3234b45b sha256: 917e891983ca3c1887b4ef36447b1e0873e70c933afc831c6b6da078ba474312 psutil-7.2.2-cp313-cp313t-win_amd64.whl md5: 4bd9479ffaa617c1192bb54876c41189 sha256: ab486563df44c17f5173621c7b198955bd6b613fb87c71c161f827d3fb149a9b psutil-7.2.2-cp313-cp313t-win_arm64.whl md5: 751bf4743c88653d925cbcc5d5c23ebe sha256: ae0aefdd8796a7737eccea863f80f81e468a1e4cf14d926bd9b6f5f2d5f90ca9 psutil-7.2.2-cp314-cp314t-macosx_10_15_x86_64.whl md5: 4bf84e3887dfd38dc959715accba3190 sha256: eed63d3b4d62449571547b60578c5b2c4bcccc5387148db46e0c2313dad0ee00 psutil-7.2.2-cp314-cp314t-macosx_11_0_arm64.whl md5: 4a63f53de0e8952be8e2c7667024cd16 sha256: 7b6d09433a10592ce39b13d7be5a54fbac1d1228ed29abc880fb23df7cb694c9 psutil-7.2.2-cp314-cp314t-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl md5: 7d8abddc896d1c0a5402c33db577a0bd sha256: 1fa4ecf83bcdf6e6c8f4449aff98eefb5d0604bf88cb883d7da3d8d2d909546a psutil-7.2.2-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl md5: c49f0ec609408cf245b16d35557657c0 sha256: e452c464a02e7dc7822a05d25db4cde564444a67e58539a00f929c51eddda0cf psutil-7.2.2-cp314-cp314t-win_amd64.whl md5: 9b36745aefa2ce3a948c713d5cc2034a sha256: c7663d4e37f13e884d13994247449e9f8f574bc4655d509c3b95e9ec9e2b9dc1 psutil-7.2.2-cp314-cp314t-win_arm64.whl md5: 7c92710cb62c39686a58f4b9daae836d sha256: 11fe5a4f613759764e79c65cf11ebdf26e33d6dd34336f8a337aa2996d71c841 psutil-7.2.2-cp36-abi3-macosx_10_9_x86_64.whl md5: 934cb1e9f3104d357f022df9501e18dd sha256: ed0cace939114f62738d808fdcecd4c869222507e266e574799e9c0faa17d486 psutil-7.2.2-cp36-abi3-macosx_11_0_arm64.whl md5: a17b3cbf9718fea225435c88973243c9 sha256: 1a7b04c10f32cc88ab39cbf606e117fd74721c831c98a27dc04578deb0c16979 psutil-7.2.2-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl md5: 440ab2614aa8abfc2e274c27da288929 sha256: 076a2d2f923fd4821644f5ba89f059523da90dc9014e85f8e45a5774ca5bc6f9 psutil-7.2.2-cp36-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl md5: af782b2c9c2e569b22664e340fbc0526 sha256: b0726cecd84f9474419d67252add4ac0cd9811b04d61123054b9fb6f57df6e9e psutil-7.2.2-cp36-abi3-musllinux_1_2_aarch64.whl md5: 69d4a0bfd9e9611ba829b270203c675b sha256: fd04ef36b4a6d599bbdb225dd1d3f51e00105f6d48a28f006da7f9822f2606d8 psutil-7.2.2-cp36-abi3-musllinux_1_2_x86_64.whl md5: 1c1ea237fadf0b93182dbbc12683e991 sha256: b58fabe35e80b264a4e3bb23e6b96f9e45a3df7fb7eed419ac0e5947c61e47cc psutil-7.2.2-cp37-abi3-win_amd64.whl md5: a8df6ec640e62acc69dd49f6fe543ca5 sha256: eb7e81434c8d223ec4a219b5fc1c47d0417b12be7ea866e24fb5ad6e84b3d988 psutil-7.2.2-cp37-abi3-win_arm64.whl md5: a4709c9c8bc7ebfd346382e8ac5d8267 sha256: 8c233660f575a5a89e6d4cb65d9f938126312bca76d8fe087b947b3a1aaac9ee psutil-7.2.2.tar.gz md5: a1c5c30f68a927053be09592d1a4be53 sha256: 0746f5f8d406af344fd547f1c8daa5f5c33dbc293bb8d6a16d80b4bb88f59372 -- Giampaolo - https://gmpy.dev/about

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NumPy 2.4.2 released
by Charles R Harris Feb. 1, 2026

Feb. 1, 2026

Hi All, On behalf of the NumPy team, I'm pleased to announce the release of NumPy 2.4.2. The NumPy 2.4.2 is a patch release that fixes bugs discovered after the 2.4.1 release. Highlights are: - Fixes memory leaks - Updates OpenBLAS to fix hangs This release supports Python versions 3.11-3.14. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/2.4.2>; release notes and the changelog are available on Github <https://github.com/numpy/numpy/releases/tag/v2.4.2>. *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 - Daniel Tang + - Joren Hammudoglu - Kumar Aditya - Matti Picus - Nathan Goldbaum - Ralf Gommers - Sebastian Berg - Vikram Kumar + *Pull requests merged* A total of 12 pull requests were merged for this release. - #30629: MAINT: Prepare 2.4.x for further development - #30636: TYP: ``arange``\ : accept datetime strings - #30657: MAINT: avoid possible race condition by not touching ``os.environ``... - #30700: BUG: validate contraction axes in tensordot (#30521) - #30701: DOC: __array_namespace__info__: set_module not __module__ (#30679) - #30702: BUG: fix free-threaded PyObject layout in replace_scalar_type_names... - #30703: TST: fix limited API example in tests for latest Cython - #30709: BUG: Fix some bugs found via valgrind (#30680) - #30712: MAINT: replace ob_type access with Py_TYPE in PyArray_CheckExact - #30713: BUG: Fixup the quantile promotion fixup - #30736: BUG: fix thread safety of ``array_getbuffer`` (#30667) - #30737: backport scipy-openblas version change Cheers, Charles Harris

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