Mailman 3 December 2019 - Python-announce-list

[baseline 0.2.1] Easy String Baseline
by Dan Gass 29 Mar '20

29 Mar '20

I am please to announce the availability of the "baseline" package. This tool streamlines creation and maintenance of tests which compare string output against a baseline. It offers a mechanism to compare a string against a baselined copy and update the baselined copy to match the new value when a mismatch occurs. The update process includes a manual step to facilitate a review of the change before acceptance. The tool uses multi-line string format for string baselines to improve readability for human review. Docs: https://baseline.readthedocs.io/en/latest/ PyPi: https://pypi.org/project/baseline/ Repo: https://github.com/dmgass/baseline License: MIT With Regards, Dan Gass (dan.gass at gmail) *********** Quick Start *********** Create an empty baseline with a triple quoted multi-line string. Place the ending triple quote on a separate line and indent it to the level you wish the string baseline update to be indented to. Add a compare of the string being tested to the baseline string. Then save the file as ``fox.py``: .. code-block:: python from baseline import Baseline expected = Baseline(""" """) test_string = "THE QUICK BROWN FOX\n JUMPS\nOVER THE LAZY DOG." assert test_string == expected Run ``fox.py`` and observe that the ``assert`` raises an exception since the strings are not equal. Because the comparison failed, the tool located the triple quoted baseline string in the source file and updated it with the miscompared value. When the interpretter exited, the tool saved the updated source file but changed the file name to ``fox.update.py``: .. code-block:: python from baseline import Baseline expected = Baseline(""" THE QUICK BROWN FOX JUMPS OVER THE LAZY DOG. """) test_string = "THE QUICK BROWN FOX\n JUMPS\nOVER THE LAZY DOG." assert test_string == expected After reviewing the change with your favorite file differencing tool, accept the change by either manually overwriting the original file or use the ``baseline`` command line tool to scan the directory for updated scripts and accept them: .. code-block:: shell $ python -m baseline * Found updates for: fox.py Hit [ENTER] to update, [Ctrl-C] to cancel fox.update.py -> fox.py Run ``fox.py`` again and observe the ``assert`` does not raise an exception nor is a source file update generated. If in the future the test value changes, the ``assert`` will raise an exception and cause a new source file update to be generated. Simply repeat the review and acceptance step and you are back in business! <P><A HREF="https://baseline.readthedocs.io/en/latest/"> baseline 0.2.1</A> - Easy String Baseline (07-Jun-18)

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The Real-Time Use of Python in Data Science World!
by Anita Goyal 06 Mar '20

06 Mar '20

This course will help you to expertise the usage of Python in Data Science world. Carter your Python Knowledge so that it can be utilized to get the Insights of Data using Methodologies and Techniques of Data Science... Objective: Understand the concepts of Data science and Python You will be able to use Python in Discovering Data. You will have an idea of Statistical and Analytical methods to deal with huge data sets. You will gain an expertise on Regular Expressions, looping functions and concepts of Object Oriented Programming. You will be able to create business algorithms and data models using Python and it's techniques. Work on Real-life Projects will help you to get a practical experience of real scenarios of IT Industry. Start learning Python for Data Science from basics to advance levels here... https://goo.gl/070wXw

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[ANN] python-javaobj 0.4.0
by Thomas Calmant 30 Dec '19

30 Dec '19

Hi, I am pleased to announce the release 0.4.0 of python-javaobj. What is python-javaobj? ======================= python-javaobj is a python library that provides functions for reading Java objects serialized with ObjectOutputStream. This form of object representation is a standard data interchange format in the Java world. The javaobj package exposes an API familiar to users of the standard library marshal, pickle and json modules. This library works with Python 2.7 and Python 3.4+. It is released under the terms of the Apache Software License 2.0. The source code is available at: https://github.com/tcalmant/python-javaobj/ What's new in 0.4.0 =================== * New implementation of the parser, based on the code of jdeserialize. It is provided by the javaobj.v2 package. It can parse more cases than the previous implementation and provides a new API for the object transformers. This implementation doesn't support writing serialized objects. * Moved the old implementation to the javaobj.v1 package. The import from javaobj redirect to the v1 package. Happy holidays, Thomas

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NumPy 1.16.6 release.
by Charles R Harris 29 Dec '19

29 Dec '19

Hi All, On behalf of the NumPy team I am pleased to announce that NumPy 1.16.6 has been released. This release fixes bugs reported against the 1.16.5 release and backports several enhancements from master that seem appropriate for an LTS series. The supported Python versions are 2.7, 3.5-3.7. This is the last release planned that supports Python 2.7. Wheels for this release can be downloaded from PyPI <https://pypi.org/project/numpy/1.16.6>, source archives and release notes are available from Github <https://github.com/numpy/numpy/releases/tag/v1.16.6>. Downstream developers building this release should use Cython >= 0.29.2 and, if using OpenBLAS, OpenBLAS >= v0.3.7. *Highlights* - The ``np.testing.utils`` functions have been updated from 1.19.0-dev0. This improves the function documentation and error messages as well extending the ``assert_array_compare`` function to additional types. *Contributors* A total of 10 people contributed to this release. - CakeWithSteak - Charles Harris - Chris Burr - Eric Wieser - Fernando Saravia - Lars Grueter - Matti Picus - Maxwell Aladago - Qiming Sun - Warren Weckesser *Pull requests merged* A total of 14 pull requests were merged for this release. - `#14211 <https://github.com/numpy/numpy/pull/14211>`__: BUG: Fix uint-overflow if padding with linear_ramp and negative... - `#14275 <https://github.com/numpy/numpy/pull/14275>`__: BUG: fixing to allow unpickling of PY3 pickles from PY2 - `#14340 <https://github.com/numpy/numpy/pull/14340>`__: BUG: Fix misuse of .names and .fields in various places (backport... - `#14423 <https://github.com/numpy/numpy/pull/14423>`__: BUG: test, fix regression in converting to ctypes. - `#14434 <https://github.com/numpy/numpy/pull/14434>`__: BUG: Fixed maximum relative error reporting in assert_allclose - `#14509 <https://github.com/numpy/numpy/pull/14509>`__: BUG: Fix regression in boolean matmul. - `#14686 <https://github.com/numpy/numpy/pull/14686>`__: BUG: properly define PyArray_DescrCheck - `#14853 <https://github.com/numpy/numpy/pull/14853>`__: BLD: add 'apt update' to shippable - `#14854 <https://github.com/numpy/numpy/pull/14854>`__: BUG: Fix _ctypes class circular reference. (#13808) - `#14856 <https://github.com/numpy/numpy/pull/14856>`__: BUG: Fix `np.einsum` errors on Power9 Linux and z/Linux - `#14863 <https://github.com/numpy/numpy/pull/14863>`__: BLD: Prevent -flto from optimising long double representation... - `#14864 <https://github.com/numpy/numpy/pull/14864>`__: BUG: lib: Fix histogram problem with signed integer arrays. - `#15172 <https://github.com/numpy/numpy/pull/15172>`__: ENH: Backport improvements to testing functions. - `#15191 <https://github.com/numpy/numpy/pull/15191>`__: REL: Prepare for 1.16.6 release. Cheers, Charles Harris

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[ANN] get-reader 1.0.0 stable release
by Shawn Brown 28 Dec '19

28 Dec '19

Happy Holidays! The first stable release of get-reader, version 1.0.0 is now available. * https://pypi.org/project/get-reader/ * https://github.com/shawnbrown/get_reader This module provides a `get_reader()` function that returns reader objects similar to those returned by `csv.reader()`. This package: * reduces common boilerplate code for handling files and reading records * reads data from CSV, pandas, SQL connections, MS Excel, DBF, and squint * provides a single interface across Python versions (including seamless Unicode-aware CSV support for Python 2) * is easy to incorporate into your own projects: * has no hard dependencies * runs on Python 2.6, 2.7, 3.2 through 3.8, PyPy, PyPy3, and Jython * is freely available under the Apache License, version 2 * can be easily vendored directly into your codebase if you don't want to include it as a dependency Some examples: >>> from get_reader import get_reader >>> >>> # CSV file. >>> reader = get_reader('myfile.csv') >>> >>> # Database connection. >>> connection = ... >>> reader = get_reader(connection, 'SELECT col1, col2 FROM mytable;') >>> >>> # Pandas DataFrame. >>> df = pd.DataFrame([...]) >>> reader = get_reader(df) >>> >>> # Excel file. >>> reader = get_reader('myfile.xlsx', worksheet='Sheet2') The internal file object is automatically closed when the iterator is exhausted, when the object is deleted, or when it is explicitly closed. An example using a context manager: >>> with get_reader('myfile.csv') as reader: >>> for row in reader: >>> print(', '.join(row)) The internal file object is also closed when exiting a with block even if the for-loop doesn't finish exhausting the reader. Install: The get-reader module has no hard dependencies; is tested on Python 2.6, 2.7, 3.2 through 3.8, PyPy, PyPy3, and Jython; and is freely available under the Apache License, version 2. You can install get_reader using pip: pip install get-reader To install optional support for MS Excel and DBF files (dBase, Foxpro, etc.), use the following: pip install get-reader[excel,dbf] Python 2 Support Statement: While official support for Python 2 ends on January 1, 2020, this project will continue to support older versions as long as the existing ecosystem provides the ability to run automated tests on those older versions.

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[ANN] Retrospective of Python compilation efforts
by Paul Sokolovsky 24 Dec '19

24 Dec '19

Hello, Over the years, the Python community produced many compiler projects for the language, second to probably only C and LISP. Majority are of course of research and proof of concept quality, but there're a number of quite advanced projects. For some time, I was trying to compile a retrospective of these efforts, formatted as a github "awesome" list: https://github.com/pfalcon/awesome-python-compilers Happy holidays, Paul

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ANN: SfePy 2019.4
by Robert Cimrman 23 Dec '19

23 Dec '19

I am pleased to announce release 2019.4 of SfePy. Description ----------- SfePy (simple finite elements in Python) is a software for solving systems of coupled partial differential equations by the finite element method or by the isogeometric analysis (limited support). It is distributed under the new BSD license. Home page: http://sfepy.org Mailing list: https://mail.python.org/mm3/mailman3/lists/sfepy.python.org/ Git (source) repository, issue tracker: https://github.com/sfepy/sfepy Highlights of this release -------------------------- - support surface terms in 1D problems - improved Gmsh mesh format support (write .msh files) - new updating procedure in nonlinear homogenization - improved/faster log plotter For full release notes see [1]. Cheers, Robert Cimrman [1] http://docs.sfepy.org/doc/release_notes.html#id1 --- Contributors to this release in alphabetical order: Robert Cimrman Vladimir Lukes Matyas Novak Tomáš Zítka

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NumPy 1.18.0 release
by Charles R Harris 22 Dec '19

22 Dec '19

Hi All, On behalf of the NumPy team I am pleased to announce that NumPy 1.18.0 has been released. In addition to the usual bug fixes, this NumPy release cleans up and documents the new random C-API, expires a large number of old deprecations, and improves the appearance and organization of the documentation. The Python versions supported are 3.5-3.8. This is the last NumPy release series that will support Python 3.5. The highlights of this release are: - the C-API for ``numpy.random`` has been defined and documented, - basic infrastructure for linking with 64 bit BLAS and LAPACK libraries, - many documentation improvements. Downstream developers should use Cython >= 0.29.14 for Python 3.8 support and OpenBLAS >= 3.7 to avoid wrong results on the Skylake architecture. The NumPy Wheels for this release can be downloaded from PyPI <https://pypi.org/project/numpy/1.18.0/>, source archives and release notes are available from Github <https://github.com/numpy/numpy/releases/tag/v1.18.0>. *Highlights* - The C-API for ``numpy.random`` has been defined and documented. - Basic infrastructure for linking with 64 bit BLAS and LAPACK libraries. - Many documentation improvements. *Contributors* A total of 114 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Abhinav Sagar - Alex Henrie + - Alexander Jung + - Allan Haldane - Andrea Pattori - Andrew Liu + - Anis Ladram + - Anne Bonner + - Antoine Dechaume + - Aryan Naraghi + - Bastian Eichenberger + - Brian Wignall + - Brigitta Sipocz - CakeWithSteak + - Charles Harris - Chris Barker - Chris Burr + - Chris Markiewicz + - Christoph Gohlke - Christopher Whelan - Colin Snyder - Dan Allan - Daniel Ching - David Stansby + - David Zwicker + - Dieter Werthmüller - Disconnect3d + - Dmytro + - Doug Davis + - Eric Larson - Eric Wieser - Esben Haabendal + - Eugene Prilepin + - Felix Divo + - Gary Gurlaskie - Gina + - Giuseppe Cuccu + - Grzegorz Bokota + - Guanqun Lu + - Guilherme Leobas + - Guillaume Horel - Géraud Le Falher + - Hameer Abbasi - Harmon - Hiroyuki V. Yamazaki - Huang, Guangtai + - Hugo + - Hyeonguk Ryu + - Ilhan Polat + - Isaac Virshup - Jack J. Woehr + - Jack Woehr + - Jackie Leng - Jaime Fernandez - Jeff Hale + - Johann Faouzi + - Jon Dufresne + - Joseph Fox-Rabinovitz - Joseph R. Fox-Rabinovitz + - João Marcos Gris + - Justus Magin + - Jérémie du Boisberranger - Kai Striega - Kevin Sheppard - Kexuan Sun - Kmol Yuan + - Kriti Singh - Larry Bradley + - Lars Grueter - Luis Pedro Coelho - MSeifert04 - Magdalena Proszewska + - Manny + - Mark Harfouche - Martin Reinecke - Martin Thoma - Matt Haberland + - Matt McCormick + - Matthias Bussonnier - Matti Picus - Max Bolingbroke + - Maxwell Aladago + - Michael Hudson-Doyle + - Oleksandr Pavlyk - Omar Merghany + - Pauli Virtanen - Peter Andreas Entschev - Peter Bell - Peter Cock + - Pradeep Reddy Raamana + - Qiming Sun + - Raghuveer Devulapalli - Ralf Gommers - Samesh + - Samesh Lakhotia + - Sebastian Berg - Sergei Lebedev - Seth Troisi + - Siddhesh Poyarekar + - Simon + - Simon Notley + - Stefan van der Walt - Stephan Hoyer - Steve Stagg - Thomas A Caswell - Thomas Kluyver - Tim Hoffmann + - Tirth Patel + - Tyler Reddy - Vladimir Pershin + - Warren Weckesser - Yadong Zhang + - Zieji Pohz + - Zolisa Bleki + Cheers, Charles Harris

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ANN: poliastro 0.13.1 released 🚀
by Juan Luis Cano 20 Dec '19

20 Dec '19

Hi all, It fills us with astronomical joy to announce the release of poliastro 0.13.0! 🚀 poliastro is a pure Python library that allows you to simulate and analyze interplanetary orbits in a Jupyter notebook in an interactive and easy way, used in academia and the industry by people from all around the world. You can install it using pip or conda: conda install poliastro --channel conda-forge pip install poliastro This release brought some bug fixes that we accumulated while preparing the next major version. You can read the full release notes in the documentation: https://docs.poliastro.space/en/v0.13.1/changelog.html#poliastro-0-13-1-201… If you want to know more, don't miss my talk on the Open Source Cubesat Worshop held at the European Space Operations Centre in 2017: https://youtu.be/KnoYzqAw_vM?t=1h36m14s Please join our chat on Matrix/Riot and feel free to ask any questions you might have: https://riot.im/app/#/room/#poliastro:matrix.org Per Python ad astra! -- Juan Luis Cano

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pytest 4.6.8 released!
by Anthony Sottile 19 Dec '19

19 Dec '19

pytest 4.6.8 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: * Anthony Sottile * Bruno Oliveira * Ryan Mast Happy testing, The pytest Development Team

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