Mailman 3 October 2020 - Python-announce-list

logassert v6
by Facundo Batista 25 Oct '20

25 Oct '20

logassert is a simple log assertion mechanism for Python unittests. Why? As is vox populi, you must also test the logging calls in your programs. With logassert this is now very easy. In this version: - Simple way to check that nothing was logged (on any level or a specific one): assert NOTHING in logs.debug - Helper to check that several lines were logged one after the other: assert Sequence( "Got 1 error and \d+ warnings:", Exact(" error: bar"), ) in logs.debug - Show proper message when "not in" assertion is used (thanks Diego Mascialino) Regards, -- . Facundo Blog: http://www.taniquetil.com.ar/plog/ PyAr: http://www.python.org.ar/ Twitter: @facundobatista

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ANN: psutil 5.7.3 released
by Giampaolo Rodola' 24 Oct '20

24 Oct '20

Hello all, I'm glad to announce the release of psutil 5.7.3: https://github.com/giampaolo/psutilHere's a blog post explaining the highlights in detail: https://gmpy.dev/blog/2020/freebsd-process-environ-and-resource-limits 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, both 32-bit and 64-bit architectures. Supported Python versions are 2.6, 2.7 and 3.4+. PyPy is also known to work. What's new ========== 2020-10-23 **Enhancements** - 809: [FreeBSD] add support for `Process.rlimit()`. - 893: [BSD] add support for `Process.environ()` (patch by Armin Gruner) - 1830: [UNIX] `net_if_stats()`'s `isup` also checks whether the NIC is running (meaning Wi-Fi or ethernet cable is connected). (patch by Chris Burger) - 1837: [Linux] improved battery detection and charge "secsleft" calculation (patch by aristocratos) **Bug fixes** - 1620: [Linux] physical cpu_count() result is incorrect on systems with more than one CPU socket. (patch by Vincent A. Arcila) - 1738: [macOS] Process.exe() may raise FileNotFoundError if process is still alive but the exe file which launched it got deleted. - 1791: [macOS] fix missing include for getpagesize(). - 1823: [Windows] Process.open_files() may cause a segfault due to a NULL pointer. - 1838: [Linux] sensors_battery(): if `percent` can be determined but not the remaining values, still return a result instead of None. (patch by aristocratos) 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 -- Giampaolo - https://gmpy.dev/

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EuroPython 2020: Edited videos are online
by M.-A. Lemburg 18 Oct '20

18 Oct '20

We’re happy to announce that all edited videos of this year’s conference are now available on our YouTube channel: * EuroPython 2020 Playlist * https://www.youtube.com/watch?v=CvbQArKEFes&list=PL8uoeex94UhHgMD9GOCbEHWku… We have 131 videos available in total, covering a very broad set of Python topics, so there’s going to be something interesting for everyone. We hope to see you all again next year and perhaps even have a few more people attending EuroPython 2021 Online, now that the format has proven successful. Stay safe. 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/632313693115416577/europython-2020-edited-v… Tweet: https://twitter.com/europython/status/1317793661061615616 Thanks, -- EuroPython 2020 Team https://ep2020.europython.eu/ https://www.europython-society.org/

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ANN: SciPy 1.5.3
by Tyler Reddy 17 Oct '20

17 Oct '20

Hi all, On behalf of the SciPy development team I'm pleased to announce the release of SciPy 1.5.3, which is a bug fix release that includes Linux ARM64 wheels for the first time. Sources and binary wheels can be found at: https://pypi.org/project/scipy/ and at: https://github.com/scipy/scipy/releases/tag/v1.5.3 One of a few ways to install this release with pip: pip install scipy==1.5.3 ========================== SciPy 1.5.3 Release Notes ========================== SciPy 1.5.3 is a bug-fix release with no new features compared to 1.5.2. In particular, Linux ARM64 wheels are now available and a compatibility issue with XCode 12 has been fixed. Authors ====== * Peter Bell * CJ Carey * Thomas Duvernay + * Gregory Lee * Eric Moore * odidev * Dima Pasechnik * Tyler Reddy * Simon Segerblom Rex + * Daniel B. Smith * Will Tirone + * Warren Weckesser A total of 12 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 1.5.3 ------------------------------ * `#9611 <https://github.com/scipy/scipy/issues/9611>`__: Overflow error with new way of p-value calculation in kendall... * `#10069 <https://github.com/scipy/scipy/issues/10069>`__: scipy.ndimage.watershed_ift regression in 1.0.0 * `#11260 <https://github.com/scipy/scipy/issues/11260>`__: BUG: DOP853 with complex data computes complex error norm, causing... * `#11479 <https://github.com/scipy/scipy/issues/11479>`__: RuntimeError: dictionary changed size during iteration on loading... * `#11972 <https://github.com/scipy/scipy/issues/11972>`__: BUG (solved): Error estimation in DOP853 ODE solver fails for... * `#12543 <https://github.com/scipy/scipy/issues/12543>`__: BUG: Picture rotated 180 degrees and rotated -180 degrees should... * `#12613 <https://github.com/scipy/scipy/issues/12613>`__: Travis X.4 and X.7 failures in master * `#12654 <https://github.com/scipy/scipy/issues/12654>`__: scipy.stats.combine_pvalues produces wrong results with method='mudholkar_george' * `#12819 <https://github.com/scipy/scipy/issues/12819>`__: BUG: Scipy Sparse slice indexing assignment Bug with zeros * `#12834 <https://github.com/scipy/scipy/issues/12834>`__: BUG: ValueError upon calling Scipy Interpolator objects * `#12836 <https://github.com/scipy/scipy/issues/12836>`__: ndimage.median can return incorrect values for integer inputs * `#12860 <https://github.com/scipy/scipy/issues/12860>`__: Build failure with Xcode 12 Pull requests for 1.5.3 ----------------------------- * `#12611 <https://github.com/scipy/scipy/pull/12611>`__: MAINT: prepare for SciPy 1.5.3 * `#12614 <https://github.com/scipy/scipy/pull/12614>`__: MAINT: prevent reverse broadcasting * `#12617 <https://github.com/scipy/scipy/pull/12617>`__: MAINT: optimize: Handle nonscalar size 1 arrays in fmin_slsqp... * `#12623 <https://github.com/scipy/scipy/pull/12623>`__: MAINT: stats: Loosen some test tolerances. * `#12638 <https://github.com/scipy/scipy/pull/12638>`__: CI, MAINT: pin pytest for Azure win * `#12668 <https://github.com/scipy/scipy/pull/12668>`__: BUG: Ensure factorial is not too large in mstats.kendalltau * `#12705 <https://github.com/scipy/scipy/pull/12705>`__: MAINT: \`openblas_support\` added sha256 hash * `#12706 <https://github.com/scipy/scipy/pull/12706>`__: BUG: fix incorrect 1d case of the fourier_ellipsoid filter * `#12721 <https://github.com/scipy/scipy/pull/12721>`__: BUG: use special.sindg in ndimage.rotate * `#12724 <https://github.com/scipy/scipy/pull/12724>`__: BUG: per #12654 adjusted mudholkar_george method to combine p... * `#12726 <https://github.com/scipy/scipy/pull/12726>`__: BUG: Fix DOP853 error norm for complex problems * `#12730 <https://github.com/scipy/scipy/pull/12730>`__: CI: pin xdist for Azure windows * `#12786 <https://github.com/scipy/scipy/pull/12786>`__: BUG: stats: Fix formula in the \`stats\` method of the ARGUS... * `#12795 <https://github.com/scipy/scipy/pull/12795>`__: CI: Pin setuptools on windows CI * `#12830 <https://github.com/scipy/scipy/pull/12830>`__: [BUG] sparse: Avoid using size attribute in LIL __setitem__ * `#12833 <https://github.com/scipy/scipy/pull/12833>`__: BUG: change list of globals items to list of a copy * `#12842 <https://github.com/scipy/scipy/pull/12842>`__: BUG: Use uint16 for cost in NI_WatershedElement * `#12845 <https://github.com/scipy/scipy/pull/12845>`__: BUG: avoid boolean or integer addition error in ndimage.measurements.median * `#12864 <https://github.com/scipy/scipy/pull/12864>`__: BLD: replace the #include of libqull_r.h with with this of qhull_ra.h... * `#12867 <https://github.com/scipy/scipy/pull/12867>`__: BUG: Fixes a ValueError yielded upon calling Scipy Interpolator... * `#12902 <https://github.com/scipy/scipy/pull/12902>`__: CI: Remove 'env' from pytest.ini * `#12913 <https://github.com/scipy/scipy/pull/12913>`__: MAINT: Ignore pytest's PytestConfigWarning 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Webware for Python 3
by cito＠online.de 17 Oct '20

17 Oct '20

After a nearly year-long alpha and beta phase, Webware for Python 3.0.0 has been released today. Here are all the important links: GitHub: https://github.com/WebwareForPython/w4py3 PyPI: https://pypi.org/project/Webware-for-Python/ Documentation: https://webwareforpython.github.io/w4py3/ List of changes: https://webwareforpython.github.io/w4py3/changes.html Mirgration guide: https://webwareforpython.github.io/w4py3/migrate.html The main improvements and changes in Webware for Python 3 are: - Python 3.6 or newer instead of Python 2 - Standard packaging and installation - Entry points for Webware plug-ins - WSGI instead of app server and adapters - Sphinx/ReadTheDocs for documentation - GitHub Actions to run improved test suite The WebKit plug-in has been promoted to the top level and does not exist anymore as a separate plug-in. PSP is still supported. MiddleKit has become an external plug-in now, available at: https://github.com/WebwareForPython/w4py3-middlekit Let me know if there are any pain points, bugs or other problems. You can use GitHub issues, pull requests or the webware mailing list for feedback and sending bug reports or improvements. -- Christoph

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EuroPython 2021 will be run online
by M.-A. Lemburg 15 Oct '20

15 Oct '20

In the last few weeks, we had a close look at the how the situation around COVID-19 is panning out. Unfortunately, things are not moving in a direction where we’d feel confident to hold next year’s conference as an in-person event in Dublin. EuroPython 2022 in Dublin ------------------------- After discussion with the venue, we decided to postpone the in-person conference for another year, to July 11-17 2022 in Dublin, Ireland. We are currently finalizing the details. Since going online has proven to work well, we also want to keep the momentum for EuroPython 2022 and are planning to run the event in a hybrid version, where both speakers and attendees can optionally join online. EuroPython 2021 Online ---------------------- Given the experience with running EuroPython 2020 online this year, we are sure that EuroPython 2021 will be a success as well. We will take the experience we’ve gained from this year’s event to improve the online version next year, simplify some aspects, reactivate finaid and enable joining it in smaller groups to create a distributed experience. We’re still collecting ideas, so if you have any suggestions, we’d love to hear them. Please write to helpdesk(a)europython.eu. 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/632055258029473792/europython-2021-will-be-… Tweet: https://twitter.com/europython/status/1316759678118961152 Thanks, -- EuroPython Society https://www.europython-society.org/

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[ANN] Austin -- CPython frame stack sampler v2.0.0 is now available
by Gabriele 13 Oct '20

13 Oct '20

I am delighted to announce the release 2.0.0 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 straightaway, even while it's running on a production environment, with minimal impact on performance. The simplest way of using Austin is by piping its output to FlameGraph for a quick and detailed representation of the collected samples. The latest release introduces a memory profiling mode which allows you to profile memory usage. Austin is a pure C application that has no other 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 - Debian repositories macOS: - Homebrew Windows: - Chocolatey - Scoop 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. Besides support for Python 3.9, this new release of Austin brings a considerable performance enhancement that allows it to sample up to 8 times faster than previous versions. But please do read on until the end to find out about some new tools that take advantage of all the key features of Austin. Due to increasing popularity, the sample Python applications that were included in the main repository have been moved to dedicated projects on GitHub. The TUI can now be found at https://github.com/P403n1x87/austin-tui while Austin Web is now available from https://github.com/P403n1x87/austin-web They can both be installed easily from PyPI, but in order to use them the Austin binary needs to be on the PATH environment variable. These projects now rely on the austin-python Python package that provides a Python wrapper around Austin. If you are considering making your own profiling tool based on Austin, this package can spare you from writing boilerplate code, so it's worth having a look at it at https://github.com/P403n1x87/austin-python The documentation is hosted on RTD at https://austin-python.readthedocs.io/en/latest/ Finally, I am happy to announce the release of pytest-austin, a plugin for pytest that allows you to set up performance regression testing by simply decorating your existing pytest test suite. The plugin launches Austin to profile your test runs, meaning that no further instrumentation is required. For more details, check out the project on GitHub https://github.com/P403n1x87/pytest-austin Like the other Austin tools, pytest-austin can be installed easily from PyPI. You can stay up-to-date with the project's development by following Austin on Twitter (https://twitter.com/AustinSampler). All the best, Gabriele <phoenix1987(a)gmail.com> <p><a href="https://github.com/P403n1x87/austin">Austin 2.0.0</a> - frame stack sampler for CPython. (13-Oct-20)</p>

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aiosnow
by Robert Wikman 10 Oct '20

10 Oct '20

Happy to announce a project I've been working on for some time that's finally in beta: aiosnow, a MIT licensed Python 3 client library for interacting with an ITSM cloud service, providing something not too dissimilar to a database ORM. I'm sharing this here as the library makes use of Python asyncio, and other cool features like: - Asynchronous generators, context managers - Query condition chaining using Python bitwise operators - Model Schema system implemented using Marshmallow - The aiohttp library for working with remote HTTP APIs It was built with modularity in mind, and is meant to be forked, hacked and consumed in other projects - commercial or otherwise. What's in it for me? I do this for fun, to learn, and to support the asyncio backend of another project I'm working on, which uses this library at its core. GitHub page: https://github.com/rbw/aiosnow Technical documentation: https://aiosnow.readthedocs.io/en/latest Big thanks to the code contributors and donors! -- Robert Wikman 0xf6feb506ae5d3762

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Guppy 3/Heapy 3.1.0
by YiFei Zhu 10 Oct '20

10 Oct '20

I am happy to announce Guppy 3 3.1.0 Guppy 3 is a library and programming environment for Python, currently providing in particular the Heapy subsystem, which supports object and heap memory sizing, profiling and debugging. It also includes a prototypical specification language, the Guppy Specification Language (GSL), which can be used to formally specify aspects of Python programs and generate tests and documentation from a common source. Guppy 3 is a fork of Guppy-PE, created by Sverker Nilsson for Python 2. This is a major feature release. The main news in this release: o Python 3.9 support, without subinterpreter support or inter-interpreter traversal. o Added .byprod classifier via tracemalloc, and .prod to print tracemalloc traceback. o Added .all to print all lines in a MorePrinter buffer. o Added R_INSET relation for being contained by an unordered set. License: MIT The project homepage is on GitHub: https://github.com/zhuyifei1999/guppy3 Enjoy, YiFei Zhu

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Wing Python IDE 7.2.6 has been released
by Wingware 08 Oct '20

08 Oct '20

Wing 7.2.6 improves exception reporting for pytest, implements 2w in vi mode, fixes problems with setting up a new Django project, improves auto-spacing for / and :, reduces CPU use when analyzing and waiting for remote files, and makes a number of usability improvements. Details: https://wingware.com/news/2020-10-07 Downloads: https://wingware.com/downloads == About Wing == Wing is a light-weight but full-featured Python IDE designed specifically for Python, with powerful editing, code inspection, testing, and debugging capabilities. Wing's deep code analysis provides auto-completion, auto-editing, and refactoring that speed up development. Its top notch debugger works with any Python code, locally or on a remote host. Wing also supports test-driven development, version control, UI color and layout customization, and includes extensive documentation and support. Wing is available in three product levels: Wing Pro is the full-featured Python IDE for professional developers, Wing Personal is a free Python IDE for students and hobbyists (omits some features), and Wing 101 is a very simplified free Python IDE for beginners (omits many features). Learn more at https://wingware.com/

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