🌐 Mailman 3 December 2021 - Python-announce-list - python.org

argon2-cffi 21.2.0
by Hynek Schlawack Dec. 8, 2021

Dec. 8, 2021

Hi everyone, I’m happy to announce the release of argon2-cffi 21.2.0! With more than 13 million downloads per month, argon2-cffi is the most popular package for using the competition-winning Argon2 password hash in Python. If you want more details on Argon2 and why it matters, check out my blog post Storing Passwords in a Highly Parallelized World <https://hynek.me/articles/storing-passwords/>. Heartfelt thanks go to my generous GitHub sponsors <https://github.com/sponsors/hynek>, companies subscribing on Tidelift <https://tidelift.com/subscription/pkg/pypi-argon2-cffi> (currently nobody :( – tell your boss!), and people who bought me a coffee on https://ko-fi.com/the_hynek! Support like that makes me work on FOSS on a Sunday afternoon, so please consider supporting me too: <https://hynek.me/say-thanks/>! <3 RELEASE HIGHLIGHTS - Pre-compiled wheels for most relevant platforms (yes, including ARM!) - Full type hints. - Adjusted defaults to RFC 9106 and support to pre-configured profiles. Full release notes: https://github.com/hynek/argon2-cffi/releases/tag/21.2.0

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ANN: poliastro 0.16.0 released 🚀
by Juan Luis Cano Rodríguez Dec. 8, 2021

Dec. 8, 2021

Hi all, It fills us with astronomical joy to announce the release of poliastro 0.16.0! 🚀 poliastro is an open source (MIT) pure Python library for interactive Astrodynamics and Orbital Mechanics, with a focus on ease of use, speed, and quick visualization. It provides a simple and intuitive API, and handles physical quantities with units. It is used in academia and the industry by people from all around the world. You can install it using pip or conda: pip install poliastro conda install poliastro --channel conda-forge This release shipped numerous new APIs and performance improvements. Yash, our Google Summer of Code 2021 student, added a number of event detectors for numerical propagation, and several contributors helped accelerate more parts of the code, which should result in significant speedups for most workflows. In addition, we have new community- contributed scripts for relative orbits and mean elements computations. You can read the full release notes here: https://docs.poliastro.space/en/v0.16.0/changelog.html#poliastro-0-16-0- 2021-12-08 We will present these changes at the Open Source Cubesat Workshop 2021, to be held online on December 9-10 https://events.libre.space/event/5/ If you want to learn more about poliastro, don't miss my talk on the Open Source Cubesat Workshop held at the European Space Operations Centre in 2017: https://youtu.be/KnoYzqAw_vM?t=1h36m14s And feel welcome to join our chat on Matrix to ask any questions you might have: http://chat.poliastro.space Per Python ad astra!

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pytest 7.0.0rc1 released!
by Florian Bruhin Dec. 7, 2021

Dec. 7, 2021

The pytest team is proud to announce the 7.0.0rc1 prerelease! This is a prerelease, not intended for production use, but to test the upcoming features and improvements in order to catch any major problems before the final version is released to the major public. We appreciate your help testing this out before the final release, making sure to report any regressions to our issue tracker: https://github.com/pytest-dev/pytest/issues When doing so, please include the string ``[prerelease]`` in the title. You can upgrade from PyPI via: pip install pytest==7.0.0rc1 Users are encouraged to take a look at the CHANGELOG carefully: https://docs.pytest.org/en/7.0.x/changelog.html Thanks to all the contributors to this release: * Adam J. Stewart * Alexander King * Amin Alaee * Andrew Neitsch * Anthony Sottile * Ben Davies * Bernát Gábor * Brian Okken * Bruno Oliveira * Cristian Vera * David Szotten * Eddie * Emmanuel Arias * Emmanuel Meric de Bellefon * Eric Liu * Florian Bruhin * GergelyKalmar * Graeme Smecher * Harshna * Hugo van Kemenade * Jakub Kulík * James Myatt * Jeff Rasley * Kale Kundert * Miro Hrončok * Naveen-Pratap * Oleg Höfling * Ran Benita * Ronny Pfannschmidt * Simon K * Srip * Sören Wegener * Taneli Hukkinen * Terje Runde * Thomas Grainger * Thomas Hisch * William Jamir Silva * Zac Hatfield-Dodds * andrewdotn * denivyruck * ericluoliu * oleg.hoefling * symonk * ziebam * Éloi Rivard Happy testing, The pytest Development Team -- me(a)the-compiler.org | https://www.qutebrowser.org https://bruhin.software/ | https://github.com/sponsors/The-Compiler/ GPG: 916E B0C8 FD55 A072 | https://the-compiler.org/pubkey.asc I love long mails! | https://email.is-not-s.ms/

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[RELEASE] Python 3.10.1 is available
by Pablo Galindo Salgado Dec. 6, 2021

Dec. 6, 2021

I hope you like bug fixes, because we have a whole shipment of them! Python 3.10.1 is the first maintenance release of Python 3.10 as we have packed more than 330 commits of fixes and general improvements. You can get it here: https://www.python.org/downloads/release/python-3101/ # This is the first maintenance release of Python 3.10 Python 3.10.1 is the newest major release of the Python programming language, and it contains many new features and optimizations. # Major new features of the 3.10 series, compared to 3.9 Among the new major new features and changes so far: * [PEP 623](https://www.python.org/dev/peps/pep-0623/) -- Deprecate and prepare for the removal of the wstr member in PyUnicodeObject. * [PEP 604](https://www.python.org/dev/peps/pep-0604/) -- Allow writing union types as X | Y * [PEP 612](https://www.python.org/dev/peps/pep-0612/) -- Parameter Specification Variables * [PEP 626](https://www.python.org/dev/peps/pep-0626/) -- Precise line numbers for debugging and other tools. * [PEP 618 ](https://www.python.org/dev/peps/pep-0618/) -- Add Optional Length-Checking To zip. * [bpo-12782](https://bugs.python.org/issue12782): Parenthesized context managers are now officially allowed. * [PEP 632 ](https://www.python.org/dev/peps/pep-0632/) -- Deprecate distutils module. * [PEP 613 ](https://www.python.org/dev/peps/pep-0613/) -- Explicit Type Aliases * [PEP 634 ](https://www.python.org/dev/peps/pep-0634/) -- Structural Pattern Matching: Specification * [PEP 635 ](https://www.python.org/dev/peps/pep-0635/) -- Structural Pattern Matching: Motivation and Rationale * [PEP 636 ](https://www.python.org/dev/peps/pep-0636/) -- Structural Pattern Matching: Tutorial * [PEP 644 ](https://www.python.org/dev/peps/pep-0644/) -- Require OpenSSL 1.1.1 or newer * [PEP 624 ](https://www.python.org/dev/peps/pep-0624/) -- Remove Py_UNICODE encoder APIs * [PEP 597 ](https://www.python.org/dev/peps/pep-0597/) -- Add optional EncodingWarning [bpo-38605](https://bugs.python.org/issue38605): `from __future__ import annotations` ([PEP 563](https://www.python.org/dev/peps/pep-0563/)) used to be on this list in previous pre-releases but it has been postponed to Python 3.11 due to some compatibility concerns. You can read the Steering Council communication about it [here]( https://mail.python.org/archives/list/python-dev@python.org/thread/CLVXXPQ2…) to learn more. # More resources * [Changelog](https://docs.python.org/3.10/whatsnew/changelog.html#changelog ) * [Online Documentation](https://docs.python.org/3.10/) * [PEP 619](https://www.python.org/dev/peps/pep-0619/), 3.10 Release Schedule * Report bugs at [https://bugs.python.org](https://bugs.python.org). * [Help fund Python and its community](/psf/donations/). # And now for something completely different The Meissner effect (or Meissner–Ochsenfeld effect) is the expulsion of a magnetic field from a superconductor during its transition to the superconducting state when it is cooled below the critical temperature. This expulsion will repel a nearby magnet. The German physicists Walther Meissner and Robert Ochsenfeld discovered this phenomenon in 1933 by measuring the magnetic field distribution outside superconducting tin and lead samples. The experiment demonstrated for the first time that superconductors were more than just perfect conductors and provided a uniquely defining property of the superconductor state. The ability for the expulsion effect is determined by the nature of equilibrium formed by the neutralization within the unit cell of a superconductor. You can do [ver cool things](https://www.youtube.com/watch?v=HRLvVkkq5GE) with it! # We hope you 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. https://www.python.org/psf/ Your friendly release team, Ned Deily @nad https://discuss.python.org/u/nad Steve Dower @steve.dower https://discuss.python.org/u/steve.dower Pablo Galindo Salgado @pablogsal https://discuss.python.org/u/pablogsal

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TatSu 5.7.0
by Juancarlo Añez Dec. 6, 2021

Dec. 6, 2021

TatSu 5.7.0 is now available. - https://pypi.org/project/TatSu/5.7.0/ - https://tatsu.readthedocs.io/ - https://github.com/neogeny/TatSu 竜 TatSu is a tool that takes grammars in a variation of EBNF as input, and outputs memoizing (Packrat) PEG parsers in Python. 竜 TatSu can compile a grammar stored in a string into a tatsu.grammars.Grammar object that can be used to parse any given input, much like the *re* module does with regular expressions, or it can generate a Python module that implements the parser. 竜 TatSu supports left-recursive rules in PEG grammars using the algorithm by Laurent and Mens. The generated AST has the expected left associativity. CHANGELOG: - Now ``config: ParserConfig`` is used in ``__init__()`` and ``parse()`` methods of ``contexts.ParseContext``, ``grammars.Grammar``, and elsewhere to avoid long parameter lists. ``ParserConfig` also provides clean and clear ways of overriding a group of settings - All names defined in the successful choice in a rule are now defined in the resulting AST. Names within optionals that did not match will have their values set to ``None``, and closures that did not match will be set to ``[]` - Moved build configuration from ``setup.py`` in favor of ``setup.cfg`` and ``pyproject.toml`` (@KOLANICH_) - ``Node.children()`` is now computed only when required, and cached - Classes in generated object models are now ``@dataclass`` - Optimize and get rid of bugs and annoyances while keeping backwards compatibility - Drop support for Python < 3.10

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ANN: Lea 3.4.1 released
by pie.denis＠skynet.be Dec. 6, 2021

Dec. 6, 2021

Lea 3.4.1 is now released! ---> https://pypi.org/project/lea/ What is Lea? ------------ Lea is a Python module for playing with discrete probability distributions in an intuitive way. This ranges from simple dice, coin flipping, random sampling . to Bayesian networks, Probabilistic Programming (PP), machine learning and symbolic computation. One salient feature of Lea is the ability to change the probability representation, viz. float, fractions, decimals, and symbols. Lea can be used for education, AI, PP, etc. Comprehensive tutorials are available online (see Wiki pages). For a 5 minutes tour, check out the poster presented at PROBPROG2020 conference: https://probprog.cc/2020/assets/posters/fri/69.pdf What's new in Lea 3.4.1? ------------------------ 1) Reading BIF files (Bayesian Interchange Format): https://bitbucket.org/piedenis/lea/wiki/Lea3_Tutorial_2 2) Misc corrections on Markov chain advanced functions (repair dependencies): https://bitbucket.org/piedenis/lea/issues/63/ 3) Enhance the test suite, especially for information theory To learn more... ---------------- Lea on PyPI -> http://pypi.org/project/lea Lea project page -> http://bitbucket.org/piedenis/lea Documentation -> http://bitbucket.org/piedenis/lea/wiki/Home With the hope that Lea can make this universe less random (or more?), Pierre Denis

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ANN: A new library for encryption and signing has been released.
by Vinay Sajip Dec. 5, 2021

Dec. 5, 2021

A new library called pagesign (Python-age-sign) has been released on PyPI [1]. It covers similar functionality to python-gnupg, but uses the modern encryption tool age [2] and the modern signing tool minisign [3]. The initial release allows you to: * Create and manage identities (which are containers for the keys used for encryption/decryption and signing/verification). * Encrypt and decrypt files to multiple recipients. * Sign files and verify signatures. This release has been signed with my code signing key: Vinay Sajip (CODE SIGNING KEY) <vinay_sajip at yahoo.co.uk> Fingerprint: CA74 9061 914E AC13 8E66 EADB 9147 B477 339A 9B86 Recent changes to PyPI don't show the GPG signature with the download links. An alternative download source where the signatures are available is at [4]. Documentation is available at [5]. As always, your feedback is most welcome (especially bug reports [6], patches and suggestions for improvement, or any other points). Enjoy! Cheers Vinay Sajip [1] https://pypi.org/project/pagesign/0.1.0/ [2] https://age-encryption.org/ [3] https://jedisct1.github.io/minisign/ [4] https://bitbucket.org/vinay.sajip/pagesign/downloads/ [5] https://docs.red-dove.com/pagesign/ [6] https://github.com/vsajip/pagesign/issues/new/choose

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Announcing NumExpr 2.8.0
by Robert McLeod Dec. 2, 2021

Dec. 2, 2021

Hi everyone, NumExpr 2.8.0 is released. This is mostly a version bump. We now support Python 3.10 and support for 2.7 and 3.5 has been discontinued. Project documentation is available at: http://numexpr.readthedocs.io/ Changes from 2.7.3 to 2.8.0 --------------------------- * Wheels for Python 3.10 are now provided. * Support for Python 2.7 and 3.5 has been discontinued. * All residual support for Python 2.X syntax has been removed, and therefore the setup build no longer makes calls to the `2to3` script. The `setup.py` has been refactored to be more modern. * The examples on how to link into Intel VML/MKL/oneAPI now use the dynamic library. 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! -- Robert McLeod robbmcleod(a)gmail.com robert.mcleod(a)hitachi-hightech.com

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