Mailman 3 July 2020 - Python-announce-list

PyCon ZA 2020 - Call for Submissions
by Neil Muller 12 Nov '20

12 Nov '20

PyCon ZA 2020 will take place on the 8th & 9th of October, 2020. This year, due to the ongoing uncertainty of when conference facilities will be allowed to open, we will be running PyCon ZA as an online event. We are looking for the following presentations: - Keynotes (45 minute long talks on a subject of general interest) - Talks (30 minute long talks on more specific topics) If you would like to give a presentation, please register at https://za.pycon.org/ and submit your proposal, following the instructions at https://za.pycon.org/talks/submit-talk/ . We have a number of tracks available, including: Data Science, Teaching and Learning with Python, Web, Scientific Computing, Testing and Other (which includes all talks that don't fall under the mentioned tracks). We hope to notify accepted presenters by no later than the 31st of August 2020. Speakers will be expected to be available after the presentation for a short Q&A session. Shared sessions are also possible. The presentations will be in English. PyCon ZA offers a mentorship program for inexperienced speakers. If you would like assistance preparing your submission, email team(a)za.pycon.org with a rough draft of your talk proposal and we'll find a suitable experienced speaker to act as a mentor. If you want to present something else at PyCon ZA, please contact the organising committee at team(a)za.pycon.org . We’re researching which software platforms will be most suitable for running PyCon ZA. As soon as we have finalised this decision, we’ll make it public and update potential presenters. If you have experience with presenting on particular platforms, we'd love to hear from you at team(a)za.pycon.org . -- Neil Muller On behalf of the PyCon ZA organising committee

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pip 20.2 release, plus changes coming in 20.3
by Sumana Harihareswara 01 Oct '20

01 Oct '20

On behalf of the Python Packaging Authority, I am pleased to announce that we have just released pip 20.2, a new version of pip. You can install it by running python -m pip install --upgrade pip. The highlights for this release are: - The beta of the next-generation dependency resolver is available - Faster installations from wheel files - Improved handling of wheels containing non-ASCII file contents - Faster `pip list` using parallelized network operations - Installed packages now contain metadata about whether they were directly requested by the user (PEP 376’s REQUESTED file) The new dependency resolver is *off by default* because it is *not yet ready for everyday use*. The new dependency resolver is significantly stricter and more consistent when it receives incompatible instructions, and reduces support for certain kinds of constraints files, so some workarounds and workflows may break. Please test it with the `--use-feature=2020-resolver` flag. Please see our guide on how to test and migrate, and how to report issues <https://pip.pypa.io/en/latest/user_guide/#changes-to-the-pip-dependency-res…>. We are preparing to change the default dependency resolution behavior and make the new resolver the default in pip 20.3 (in October 2020). This release also partially optimizes pip’s network usage during installation (as part of a Google Summer of Code project by McSinyx <https://summerofcode.withgoogle.com/projects/#5428041779511296>). Please test it with `pip install --use-feature=2020-resolver --use-feature=fast-deps` and report bugs to the issue tracker <https://github.com/pypa/pip/issues/new?template=bug-report.md>. This functionality is *still experimental* and *not ready for everyday use*. You can find more details (including deprecations and removals) in the changelog <https://pip.pypa.io/en/stable/news/>. As with all pip releases, a significant amount of the work was contributed by pip’s user community. Huge thanks to all who have contributed, whether through code, documentation, issue reports and/or discussion. Your help keeps pip improving, and is hugely appreciated. Specific thanks go to Mozilla (through its Mozilla Open Source Support <https://www.mozilla.org/en-US/moss/> Awards) and to the Chan Zuckerberg Initiative <https://chanzuckerberg.com/eoss/> DAF, an advised fund of Silicon Valley Community Foundation, for their funding that enabled substantial work on the new resolver. -- Sumana Harihareswara pip project manager via contract with PSF Changeset Consulting https://changeset.nyc

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pytest 6.0.1
by Bruno Oliveira 30 Jul '20

30 Jul '20

pytest 6.0.1 has just been released to PyPI. This is a bug-fix release, being a drop-in replacement. To upgrade:: pip install --upgrade pytest The full changelog is available at https://docs.pytest.org/en/latest/changelog.html. Thanks to all who contributed to this release, among them: * Bruno Oliveira * Mattreex * Ran Benita * hp310780 Happy testing, The pytest Development Team

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pytest 6.0.0 released!
by Bruno Oliveira 28 Jul '20

28 Jul '20

The pytest team is proud to announce the 6.0.0 release! pytest is a mature Python testing tool with more than 2000 tests against itself, passing on many different interpreters and platforms. This release contains a bunch of new goodies such as typing annotations, pyproject.toml, new hooks, and new command-line flags. CHANGELOG: https://docs.pytest.org/en/stable/changelog.html For complete documentation, please visit: https://docs.pytest.org/en/stable/ As usual, you can upgrade from PyPI via: pip install -U pytest Thanks to all users who have tested the 6.0.0rc1 release, it really helped us out nail down a few problems before the final release. Also many thanks to all contributors, among them: * Alfredo Deza * Andreas Maier * Andrew * Anthony Sottile * ArtyomKaltovich * Arvin Firouzi * Bruno Oliveira * Claire Cecil * Curt J. Sampson * Daniel * Daniel Hahler * Danny Sepler * David Diaz Barquero * Debi Mishra * earonesty * Fabio Zadrozny * Felix Nieuwenhuizen * Florian Bruhin * Florian Dahlitz * Garrett Thomas * gaurav dhameeja * gdhameeja * Gleb Nikonorov * Hugo van Kemenade * Hunter Richards * ibriquem * Katarzyna Król * Katrin Leinweber * Kelton Bassingthwaite * Keri Volans * Kostis Anagnostopoulos * Lewis Belcher * Lewis Cowles * Lukas Geiger * Martin Michlmayr * Mattwmaster58 * Maximilian Cosmo Sitter * mcsitter * Miro Hrončok * Nikolay Kondratyev * Pavel Karateev * Paweł Wilczyński * piotrhm * Prashant Anand * Ram Rachum * Ran Benita * Ronny Pfannschmidt * Ruaridh Williamson * Simon K * smarie * symonk * Tim Hoffmann * Tor Colvin * Vlad-Radz * Xinbin Huang * xuiqzy * Zac Hatfield-Dodds Happy testing, The pytest Development Team

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Corrected: leoAst.py creates two-way links between tokens and ast nodes
by Edward K. Ream 25 Jul '20

25 Jul '20

In the initial announcement, the link to leoAst.py was incorrect. The correct link is to leoAst.py in Leo's "devel" branch: https://github.com/leo-editor/leo-editor/blob/devel/leo/core/leoAst.py Alas, the link did not generate a 404, but instead linked to way obsolete code. My apologies for the confusion this has already caused. Edward ------------------------------------------------------------------------------------------ Edward K. Ream: edreamleo(a)gmail.com Leo: http://leoeditor.com/ ------------------------------------------------------------------------------------------

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ANN: leoAst.py creates two-way links between tokens and ast nodes
by Edward K. Ream 25 Jul '20

25 Jul '20

*Overview* leoAst.py <https://github.com/leo-editor/leo-editor/blob/fstrings/leo/core/leoAst.py> unifies python's token-oriented and ast-oriented worlds. leoAst.py defines classes that create two-way links between *tokens* created by python's tokenize module <https://docs.python.org/3/library/tokenize.html> and *parse tree nodes* created by python's ast module <https://docs.python.org/3/library/ast.html>: The *Token Order Generator* (TOG) class *quickly* creates the following links: - An *ordered* *children* array from each ast node to its children. Order matters! - A *parent* link from each ast.node to its parent. - Two-way links between tokens in the *token list*, a list of Token objects, and the ast nodes in the parse tree: - For each token, *token.node* contains the ast.node "responsible" for the token. - For each ast node, *node.first_i* and *node.last_i* are indices into the token list. These indices give the range of tokens that can be said to be "generated" by the ast node. Once the TOG class has inserted parent/child links, the *Token Order Traverser* (TOT) class traverses trees annotated with parent/child links extremely quickly. *Contents of leoAst.py* leoAst.py is completely independent of Leo <http://leoeditor.com/>. leoAst.py contains: - The TOG and TOT classes. - An *AstDumper* class that shows these links in various formats. - Unit tests that completely cover the TOG and TOT classes. - All necessary support code - An entirely new implementation of *fstringify* <https://pypi.org/project/fstringify/>. - *Orange*, an entirely new implementation of *black* <https://pypi.org/project/black/>. *Usage* usage: leoAst.py (--help | --pytest | --unittest) OR leoAst.py (--fstringify | --fstringify-diff | --orange | --orange-diff) PATHS positional arguments: PATHS directory or list of files optional arguments: -h, --help show this help message and exit --fstringify leonine fstringify --fstringify-diff show fstringify diff --orange leonine Black --orange-diff show orange diff --pytest run pytest --unittest run unittest.main() *Applicability and importance* Many python developers will find asttokens <https://github.com/gristlabs/asttokens> meets all their needs. asttokens is well documented and easy to use. Nevertheless, two-way links are significant additions to python's tokenize <https://docs.python.org/3/library/tokenize.html> and ast <https://docs.python.org/3/library/ast.html> modules: - Links from tokens to nodes are assigned to the nearest possible ast node, not the nearest statement, as in asttokens. Links can easily be reassigned, if desired. - The TOG and TOT classes are intended to be the foundation of tools such as *fstringify* <https://pypi.org/project/fstringify/> and *black* <https://pypi.org/project/black/>. - The TOG class solves real problems, such as: how-to-get-source-corresponding-to-a-python-ast-node <https://stackoverflow.com/questions/16748029/>. *Figures of merit* *Simplicity*: The code consists primarily of a set of generators, one for every kind of ast node. *Speed*: The TOG creates two-way links between tokens and ast nodes in roughly the time taken by python's tokenize.tokenize and ast.parse library methods. This is substantially faster than the asttokens <https://pypi.org/project/asttokens/>, fstringify <https://pypi.org/project/fstringify/>, and black <https://pypi.org/project/black/> tools. The TOT class traverses trees annotated with parent/child links even more quickly. *Memory*: The TOG class makes no significant demands on python's resources. Generators add nothing to python's call stack. TOG.node_stack is the only variable-length data. This stack resides in python's heap, so its length is unimportant. In the worst case, it might contain a few thousand entries. The TOT class uses no variable-length data at all. *Links* - Theory of operation <http://leoeditor.com/appendices.html#tokenorder-classes-theory-of-operation> . - Project history <https://github.com/leo-editor/leo-editor/issues/1440#issuecomment-574145510> . - A stack overflow discussion that mentions Leo's deprecated TokenSync class <https://stackoverflow.com/questions/7456933/>, an earlier attempt at plugging the holes in python's api. Edward ------------------------------------------------------------------------------------------ Edward K. Ream: edreamleo(a)gmail.com Leo: http://leoeditor.com/ ------------------------------------------------------------------------------------------

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ANN: SciPy 1.5.2
by Tyler Reddy 24 Jul '20

24 Jul '20

Hi all, On behalf of the SciPy development team I'm pleased to announce the release of SciPy 1.5.2, which is a bug fix release. Sources and binary wheels can be found at: https://pypi.org/project/scipy/ and at: https://github.com/scipy/scipy/releases/tag/v1.5.2 One of a few ways to install this release with pip: pip install scipy==1.5.2 ========================== SciPy 1.5.2 Release Notes ========================== SciPy 1.5.2 is a bug-fix release with no new features compared to 1.5.1. Authors ====== * Peter Bell * Tobias Biester + * Evgeni Burovski * Thomas A Caswell * Ralf Gommers * Sturla Molden * Andrew Nelson * ofirr + * Sambit Panda * Ilhan Polat * Tyler Reddy * Atsushi Sakai * Pauli Virtanen A total of 13 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. Issues closed for 1.5.2 ------------------------------ * `#3847 <https://github.com/scipy/scipy/issues/3847>`__: Crash of interpolate.splprep(task=-1) * `#7395 <https://github.com/scipy/scipy/issues/7395>`__: splprep segfaults if fixed knots are specified * `#10761 <https://github.com/scipy/scipy/issues/10761>`__: scipy.signal.convolve2d produces incorrect values for large arrays * `#11971 <https://github.com/scipy/scipy/issues/11971>`__: DOC: search in devdocs returns wrong link * `#12155 <https://github.com/scipy/scipy/issues/12155>`__: BUG: Fix permutation of distance matrices in scipy.stats.multiscale_graphcorr * `#12203 <https://github.com/scipy/scipy/issues/12203>`__: Unable to install on PyPy 7.3.1 (Python 3.6.9) * `#12316 <https://github.com/scipy/scipy/issues/12316>`__: negative scipy.spatial.distance.correlation * `#12422 <https://github.com/scipy/scipy/issues/12422>`__: BUG: slsqp: ValueError: failed to initialize intent(inout) array... * `#12428 <https://github.com/scipy/scipy/issues/12428>`__: stats.truncnorm.rvs() never returns a scalar in 1.5 * `#12441 <https://github.com/scipy/scipy/issues/12441>`__: eigvalsh inconsistent eigvals= subset_by_index= * `#12445 <https://github.com/scipy/scipy/issues/12445>`__: DOC: scipy.linalg.eigh * `#12449 <https://github.com/scipy/scipy/issues/12449>`__: Warnings are not filtered in csr_matrix.sum() * `#12469 <https://github.com/scipy/scipy/issues/12469>`__: SciPy 1.9 exception in LSQSphereBivariateSpline * `#12487 <https://github.com/scipy/scipy/issues/12487>`__: BUG: optimize: incorrect result from approx_fprime * `#12493 <https://github.com/scipy/scipy/issues/12493>`__: CI: GitHub Actions for maintenance branches * `#12533 <https://github.com/scipy/scipy/issues/12533>`__: eigh gives incorrect results * `#12579 <https://github.com/scipy/scipy/issues/12579>`__: BLD, MAINT: distutils issues in wheels repo Pull requests for 1.5.2 ------------------------------- * `#12156 <https://github.com/scipy/scipy/pull/12156>`__: BUG: Fix permutation of distance matrices in scipy.stats.multiscale_graphcorr * `#12238 <https://github.com/scipy/scipy/pull/12238>`__: BUG: Use 64-bit indexing in convolve2d to avoid overflow * `#12256 <https://github.com/scipy/scipy/pull/12256>`__: BLD: Build lsap as a single extension instead of extension +... * `#12320 <https://github.com/scipy/scipy/pull/12320>`__: BUG: spatial: avoid returning negative correlation distance * `#12383 <https://github.com/scipy/scipy/pull/12383>`__: ENH: Make cKDTree.tree more efficient * `#12392 <https://github.com/scipy/scipy/pull/12392>`__: DOC: update scipy-sphinx-theme * `#12430 <https://github.com/scipy/scipy/pull/12430>`__: BUG: truncnorm and geninvgauss never return scalars from rvs * `#12437 <https://github.com/scipy/scipy/pull/12437>`__: BUG: optimize: cast bounds to floats in new_bounds_to_old/old_bounds_to_new * `#12442 <https://github.com/scipy/scipy/pull/12442>`__: MAINT:linalg: Fix for input args of eigvalsh * `#12461 <https://github.com/scipy/scipy/pull/12461>`__: MAINT: sparse: write matrix/asmatrix wrappers without warning... * `#12478 <https://github.com/scipy/scipy/pull/12478>`__: BUG: fix array_like input defects and add tests for all functions... * `#12488 <https://github.com/scipy/scipy/pull/12488>`__: BUG: fix approx_derivative step size. Closes #12487 * `#12500 <https://github.com/scipy/scipy/pull/12500>`__: CI: actions branch trigger fix * `#12501 <https://github.com/scipy/scipy/pull/12501>`__: CI: actions branch trigger fix * `#12504 <https://github.com/scipy/scipy/pull/12504>`__: BUG: cKDTreeNode use after free * `#12529 <https://github.com/scipy/scipy/pull/12529>`__: MAINT: allow graceful docs re-upload * `#12538 <https://github.com/scipy/scipy/pull/12538>`__: BUG:linalg: eigh type parameter handling corrected * `#12560 <https://github.com/scipy/scipy/pull/12560>`__: MAINT: truncnorm.rvs compatibility for \`Generator\` * `#12562 <https://github.com/scipy/scipy/pull/12562>`__: redo gh-12188: fix segfaults in splprep with fixed knots * `#12586 <https://github.com/scipy/scipy/pull/12586>`__: BLD: Add -std=c99 to sigtools to compile with C99 * `#12590 <https://github.com/scipy/scipy/pull/12590>`__: CI: Add GCC 4.8 entry to travis build matrix * `#12591 <https://github.com/scipy/scipy/pull/12591>`__: BLD: fix cython error on master-branch cython Checksums ========= MD5 ~~~ 2e046d26cdc4241a6a5b2907d57528df scipy-1.5.2-cp36-cp36m-macosx_10_9_x86_64.whl 902dea66453e2fa0616e9479970986f5 scipy-1.5.2-cp36-cp36m-manylinux1_i686.whl e130db080706d9f4ce22d8493c8e1ce2 scipy-1.5.2-cp36-cp36m-manylinux1_x86_64.whl 721f16bae600731e479a5b4e98ce9a97 scipy-1.5.2-cp36-cp36m-win32.whl a3171cfe38618d51acbfb8d1b39ac612 scipy-1.5.2-cp36-cp36m-win_amd64.whl c9f733d4d2e82c098c08760963dafaf8 scipy-1.5.2-cp37-cp37m-macosx_10_9_x86_64.whl 53ba6c502d09145b38e0e857b2d4a273 scipy-1.5.2-cp37-cp37m-manylinux1_i686.whl b9db33944ac4147936a7f42df8e95ad2 scipy-1.5.2-cp37-cp37m-manylinux1_x86_64.whl be9e8bfdf0e5e0914d1e1605be26d9c0 scipy-1.5.2-cp37-cp37m-win32.whl 848fa7b82a25d0ce36710ccc47ebc2ca scipy-1.5.2-cp37-cp37m-win_amd64.whl 590cd3b70a2dc8664896d6b9e2e5fc6d scipy-1.5.2-cp38-cp38-macosx_10_9_x86_64.whl 7fdbb19c15702b98319ea4ea32df8458 scipy-1.5.2-cp38-cp38-manylinux1_i686.whl 301f3a873e1bfef70d6f594c489fafe8 scipy-1.5.2-cp38-cp38-manylinux1_x86_64.whl 8c08ac0f55810e89e336eb3bf5a7b337 scipy-1.5.2-cp38-cp38-win32.whl 711f5c47c801dc79bead7d40669fd8c9 scipy-1.5.2-cp38-cp38-win_amd64.whl 620fc39f371e04a76af5d0290f8d3753 scipy-1.5.2.tar.gz 5bc188f21054a2ecff74fae40dd298da scipy-1.5.2.tar.xz 17bc80802955d100f6c1335594eda29a scipy-1.5.2.zip SHA256 ~~~~~~ cca9fce15109a36a0a9f9cfc64f870f1c140cb235ddf27fe0328e6afb44dfed0 scipy-1.5.2-cp36-cp36m-macosx_10_9_x86_64.whl 1c7564a4810c1cd77fcdee7fa726d7d39d4e2695ad252d7c86c3ea9d85b7fb8f scipy-1.5.2-cp36-cp36m-manylinux1_i686.whl 07e52b316b40a4f001667d1ad4eb5f2318738de34597bd91537851365b6c61f1 scipy-1.5.2-cp36-cp36m-manylinux1_x86_64.whl d56b10d8ed72ec1be76bf10508446df60954f08a41c2d40778bc29a3a9ad9bce scipy-1.5.2-cp36-cp36m-win32.whl 8e28e74b97fc8d6aa0454989db3b5d36fc27e69cef39a7ee5eaf8174ca1123cb scipy-1.5.2-cp36-cp36m-win_amd64.whl 6e86c873fe1335d88b7a4bfa09d021f27a9e753758fd75f3f92d714aa4093768 scipy-1.5.2-cp37-cp37m-macosx_10_9_x86_64.whl a0afbb967fd2c98efad5f4c24439a640d39463282040a88e8e928db647d8ac3d scipy-1.5.2-cp37-cp37m-manylinux1_i686.whl eecf40fa87eeda53e8e11d265ff2254729d04000cd40bae648e76ff268885d66 scipy-1.5.2-cp37-cp37m-manylinux1_x86_64.whl 315aa2165aca31375f4e26c230188db192ed901761390be908c9b21d8b07df62 scipy-1.5.2-cp37-cp37m-win32.whl ec5fe57e46828d034775b00cd625c4a7b5c7d2e354c3b258d820c6c72212a6ec scipy-1.5.2-cp37-cp37m-win_amd64.whl fc98f3eac993b9bfdd392e675dfe19850cc8c7246a8fd2b42443e506344be7d9 scipy-1.5.2-cp38-cp38-macosx_10_9_x86_64.whl a785409c0fa51764766840185a34f96a0a93527a0ff0230484d33a8ed085c8f8 scipy-1.5.2-cp38-cp38-manylinux1_i686.whl 0a0e9a4e58a4734c2eba917f834b25b7e3b6dc333901ce7784fd31aefbd37b2f scipy-1.5.2-cp38-cp38-manylinux1_x86_64.whl dac09281a0eacd59974e24525a3bc90fa39b4e95177e638a31b14db60d3fa806 scipy-1.5.2-cp38-cp38-win32.whl 92eb04041d371fea828858e4fff182453c25ae3eaa8782d9b6c32b25857d23bc scipy-1.5.2-cp38-cp38-win_amd64.whl 066c513d90eb3fd7567a9e150828d39111ebd88d3e924cdfc9f8ce19ab6f90c9 scipy-1.5.2.tar.gz 28d5d2e9af6ca5c0352cd83fb64191f2d8e883ab5287a221ba7a175c8cc2ccbe scipy-1.5.2.tar.xz a9054595a370f24d68f7a694037316b69ae80f5837323d567f76cde055189c08 scipy-1.5.2.zip

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ANN: Lea 3.3.0 released
by pie.denis＠skynet.be 22 Jul '20

22 Jul '20

Lea 3.3.0 is now released! ---> http://pypi.org/project/lea/3.3.0 What is Lea? ------------ Lea is a Python module aiming at working with discrete probability distributions in an intuitive way. It allows you modeling a broad range of random phenomena: gambling, weather, finance, etc. More generally, Lea may be used for any finite set of discrete values having known probability: numbers, booleans, date/times, symbols, ... Each probability distribution is modeled as a plain object, which can be named, displayed, queried or processed to produce new probability distributions. Lea also provides advanced functions, machine learning and Probabilistic Programming (PP) features; these include conditional probabilities, Bayesian networks, joint probability distributions, Markov chains, EM algorithm and symbolic computation. Lea can be used for AI, PP, gambling, education, etc. LGPL - Python 2.6+ / Python 3 supported What's new in Lea 3.3.0? ------------------------ The version 3.3.0 extends Lea with advanced Monte-Carlo algorithms, for dealing with problems intractable for exact resolution. These are described in a dedicated page of the wiki: http://bitbucket.org/piedenis/lea/wiki/Lea3_Tutorial_3#markdown-header-appro ximate-inference-by-monte-carlo-approaches This version contains also a couple of improvements on usability. To learn more... ---------------- Lea 3 on PyPI -> http://pypi.org/project/lea Lea project page -> http://bitbucket.org/piedenis/lea Documentation -> http://bitbucket.org/piedenis/lea/wiki/Home Statues algorithm -> http://link.springer.com/chapter/10.1007/978-3-030-52246-9_10 With the hope that Lea can make this Universe less infectious, Pierre Denis

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EuroPython 2020: Data Science Track
by M.-A. Lemburg 22 Jul '20

22 Jul '20

We are excited to announce a complete two day data science track at EuroPython 2020 Online, happening on Thursday and Friday (July 23 - 24). Yes, that’s starting tomorrow. Sorry for the short notice :-) * Data Science @ EuroPython 2020 * https://ep2020.europython.eu/events/data-science/ The data science track is part of EuroPython 2020, so you won’t need to buy an extra ticket to attend. We will have a two day track featuring more than 20 keynotes, full-length talks and posters: - Keynotes in the Microsoft Room - Talks in the Parrot Room - Posters in the Poster Rooms The full program is available on our data science page: https://ep2020.europython.eu/events/data-science/ If you’d like to attend the data science track at EuroPython 2020, please register for EuroPython 2020 soon. Dates and Registration ---------------------- EuroPython 2020 will be held online from July 23-26 2020. You can register on our website: https://ep2020.europython.eu/registration/buy-tickets/ If you want to learn more about the online setup, please check the Setup section on our website: https://ep2020.europython.eu/setup/online-conference/ After buying a ticket, please register on our Discord server, following the instructions in the order confirmation email. You will even be able to buy tickets on the days themselves, however, please be aware that this may cause delays in your Discord signup. Please see our website for more information. Help spread the word -------------------- Please help us spread this message by sharing it on your social networks as widely as possible. Thank you ! Link to the blog post: https://blog.europython.eu/post/624331411913146368/europython-2020-data-sci… Tweet: https://twitter.com/europython/status/1285864453511294976 Thanks, -- EuroPython 2020 Team https://ep2020.europython.eu/ https://www.europython-society.org/

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NumPy 1.19.1 released.
by Charles R Harris 21 Jul '20

21 Jul '20

Hi All, On behalf of the NumPy team I am pleased to announce that NumPy 1.19.1 has been released. This release supports Python 3.6-3.8 and may be built with the latest Python 3.9 beta. It fixes several bugs found in the 1.19.0 release, replaces several functions deprecated in the upcoming Python-3.9 release, has improved support for AIX, and has a number of development related updates to keep CI working with recent upstream changes. Downstream developers should use Cython >= 0.29.21 when building for Python 3.9 and Cython >= 0.29.16 when building for Python 3.8. OpenBLAS >= 3.7 is needed to avoid wrong results on the Skylake architecture. The NumPy Wheels for this release can be downloaded from PyPI <https://pypi.org/project/numpy/1.19.1/>, source archives, release notes, and wheel hashes are available from Github <https://github.com/numpy/numpy/releases/tag/v1.19.1>. Linux users will need pip >= 0.19.3 in order to install manylinux2010 and manylinux2014 wheels. *Contributors* A total of 15 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Abhinav Reddy + - Anirudh Subramanian - Antonio Larrosa + - Charles Harris - Chunlin Fang - Eric Wieser - Etienne Guesnet + - Kevin Sheppard - Matti Picus - Raghuveer Devulapalli - Roman Yurchak - Ross Barnowski - Sayed Adel - Sebastian Berg - Tyler Reddy *Pull requests merged* A total of 25 pull requests were merged for this release. - #16649: MAINT, CI: disable Shippable cache - #16652: MAINT: Replace PyUString_GET_SIZE with PyUnicode_GetLength. - #16654: REL: Fix outdated docs link - #16656: BUG: raise IEEE exception on AIX - #16672: BUG: Fix bug in AVX complex absolute while processing array of... - #16693: TST: Add extra debugging information to CPU features detection - #16703: BLD: Add CPU entry for Emscripten / WebAssembly - #16705: TST: Disable Python 3.9-dev testing. - #16714: MAINT: Disable use_hugepages in case of ValueError - #16724: BUG: Fix PyArray_SearchSorted signature. - #16768: MAINT: Fixes for deprecated functions in scalartypes.c.src - #16772: MAINT: Remove unneeded call to PyUnicode_READY - #16776: MAINT: Fix deprecated functions in scalarapi.c - #16779: BLD, ENH: Add RPATH support for AIX - #16780: BUG: Fix default fallback in genfromtxt - #16784: BUG: Added missing return after raising error in methods.c - #16795: BLD: update cython to 0.29.21 - #16832: MAINT: setuptools 49.2.0 emits a warning, avoid it - #16872: BUG: Validate output size in bin- and multinomial - #16875: BLD, MAINT: Pin setuptools - #16904: DOC: Reconstruct Testing Guideline. - #16905: TST, BUG: Re-raise MemoryError exception in test_large_zip's... - #16906: BUG, DOC: Fix bad MPL kwarg. - #16916: BUG: Fix string/bytes to complex assignment - #16922: REL: Prepare for NumPy 1.19.1 release Cheers, Charles Harris

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