Mailman 3 November 2018 - Python-announce-list

[baseline 0.2.1] Easy String Baseline
by Dan Gass March 30, 2020

March 30, 2020

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 March 7, 2020

March 7, 2020

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] PySPH-1.0a6: Smoothed Particle Hydrodynamics with Python
by Prabhu Ramachandran Nov. 27, 2018

Nov. 27, 2018

Hi, I am pleased to release PySPH version 1.0a6. PySPH is an open source (BSD licensed) framework for Smoothed Particle Hydrodynamics (SPH) simulations. It is implemented in Python and the performance critical parts are implemented in Cython/OpenCL. A wide variety of SPH formulations are available and new ones can be easily added. PySPH allows users to write their high-level code in pure Python. This Python code is automatically converted to high-performance Cython or OpenCL which is compiled and executed. PySPH can be configured to work seamlessly with OpenMP, OpenCL, and MPI. Documentation: http://pysph.readthedocs.org Download: http://pypi.python.org/pypi/PySPH/ Development: http://github.com/pypr/pysph Changelog: http://pysph.readthedocs.io/en/latest/overview.html#a6 Quick changelog --------------- - Initial support for transparent execution on a GPU via OpenCL. - Many feature enhancements to support various particle methods. - Allow particle array properties to have strides. - Improved documentation. - Generalized code generation tools. - Several new examples. - Several new SPH schemes have been added. - Many bugs have been fixed. For more details see the detailed changelog here: http://pysph.readthedocs.io/en/latest/overview.html#a6 90 pull requests were merged for this release. Thanks to the following who contributed to this release (in alphabetical order): A Dinesh, Abhinav Muta, Aditya Bhosale, Ananyo Sen, Deep Tavker, Prabhu Ramachandran, Vikas Kurapati, nilsmeyerkit, Rahul Govind, Sanka Suraj. cheers, Prabhu Ramachandran Department of Aerospace Engineering, IIT Bombay

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[ANN] automan-0.4: automation framework for numerical computing
by Prabhu Ramachandran Nov. 26, 2018

Nov. 26, 2018

Hi, I'm pleased to announce the availability of automan version 0.4. automan is a simple Pythonic automation framework that aims to automate the drudgery of managing many numerical simulations. As an automation framework it does the following: - helps you organize your simulations. - helps you orchestrate running simulations and then post-processing the results from these. - helps you reuse code for the post processing of your simulation data. - execute all your simulations and post-processing with one command. - optionally distribute your simulations among other computers on your network. This greatly facilitates reproducibility. Automan is written in pure Python and is easy to install. It has been used to automate complete research papers. Learn more at: https://automan.rtfd.io and https://github.com/pypr/automan This release adds support for defining inter task/problem dependencies and fixes some subtle bugs. cheers, Prabhu Ramachandran

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Pygments 2.3 released
by Matthäus G. Chajdas Nov. 25, 2018

Nov. 25, 2018

I'm happy to announce the release of Pygments 2.3. Pygments is a generic syntax highlighter written in Python. The main changes over 2.2 are Python 3.7 support, new lexers, and various small fix accumulated over the last two years. Please have a look at the changelog <http://pygments.org/docs/changelog>. Report bugs and feature requests in the issue tracker: <http://bitbucket.org/birkenfeld/pygments-main/issues>. Thanks go to all the contributors of these lexers, and to all those who reported bugs and waited very patiently for this release. Download it from <http://pypi.python.org/pypi/Pygments>, or look at the demonstration at <http://pygments.org/demo>. Enjoy, Matthäus

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pytest 4.0.1
by Bruno Oliveira Nov. 24, 2018

Nov. 24, 2018

pytest 4.0.1 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: * Anthony Sottile * Bruno Oliveira * Daniel Hahler * Michael D. Hoyle * Ronny Pfannschmidt * Slam Happy testing, The pytest Development Team

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PyCA cryptography 2.4.2 released
by Paul Kehrer Nov. 21, 2018

Nov. 21, 2018

PyCA cryptography 2.4.2 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, X509, key derivation functions, and much more. We support Python 2.7, Python 3.4+, and PyPy. Changelog (https://cryptography.io/en/latest/changelog/#v2-4-2): * Updated Windows, macOS, and manylinux1 wheels to be compiled with OpenSSL 1.1.0j. -Paul Kehrer (reaperhulk)

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[ANN] iPOPO 0.8.1
by Thomas Calmant Nov. 17, 2018

Nov. 17, 2018

Hello, I'm happy to announce that iPOPO v0.8.1 has just been released! What is iPOPO ============= iPOPO is a Service-Oriented Component Model (SOCM) based on Pelix, a dynamic service platform. Both are inspired on two popular Java technologies for the development of long-lived applications: the iPOJO component model and the OSGi Service Platform. iPOPO enables to conceive long-running and modular IT services. It is based on the concepts specified by OSGi: - Bundle: a Python module imported using Pelix and associated to a context. A bundle has a life-cycle (install, start, updated, stop, uninstall) - Service: a Python object registered in a service registry, associated to a specification and to properties. - Component: the instance of a class described/manipulated by iPOPO decorators Components are bound together by the specification(s) of the service(s) they provide. The required services are injected into components by iPOPO. For more information about those concepts, see https://ipopo.readthedocs.io/en/latest/refcards/index.html#refcards iPOPO provides many services out-of-the-box, like an HTTP server, local and remote shell, remote services... iPOPO is released under the terms of Apache Software License 2.0 What's new in 0.8.1 =================== This is bug fix release, for both the ThreadPool, used in Remote Services, and the RSA implementation: * Fixed a memory leak in the thread pool implementation. The patch comes from issue 35 of the jsonrpclib-pelix project. * Fixed a deadlock in the Py4J provider (issue #100), contributed by Scott Lewis. See pull request #101 for more details. You can take a look at the documentation at https://ipopo.readthedocs.io/ iPOPO is available on PyPI: https://pypi.python.org/pypi/iPOPO Source is available on GitHub: https://github.com/tcalmant/ipopo Feel free to send feedback on your experience of Pelix/iPOPO, via the mailing lists: User list : http://groups.google.com/group/ipopo-users Development list : http://groups.google.com/group/ipopo-dev Have fun!

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TatSu 4.3.0 released
by Juancarlo Añez Nov. 17, 2018

Nov. 17, 2018

TatSu 4.3.0 has been released with this changelog: - #66 <https://github.com/neogeny/TatSu/issues/66> Fix multiline ( (?x) ) patterns not properly supported in grammar (@pdw-mb <https://github.com/pdw-mb>) - #70 <https://github.com/neogeny/TatSu/issues/70> Important upgrade to ModelBuilder and grammar specification of classes for generated nodes. See pull request #78 <https://github.com/neogeny/TatSu/pull/78> for details ( @Victorious3 <https://github.com/Victorious3>) https://pypi.org/project/tatsu/ https://github.com/neogeny/TatSu https://tatsu.readthedocs.io/ 竜 TatSu (the successor to Grako <https://bitbucket.org/neogeny/grako/>) is a tool that takes grammars in a variation of EBNF <http://en.wikipedia.org/wiki/Ebnf> as input, and outputs memoizing <http://en.wikipedia.org/wiki/Memoization> (Packrat <http://bford.info/packrat/>) PEG <http://en.wikipedia.org/wiki/Parsing_expression_grammar> parsers in Python <http://python.org/>. 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 <https://docs.python.org/3.7/library/re.html> module does with regular expressions, or it can generate a Python <http://python.org/> module that implements the parser. -- Juancarlo *Añez*

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TatSu 4.3.0 released
by Juancarlo Añez Nov. 17, 2018

Nov. 17, 2018

TatSu 4.3.0 has been released with this changelog: -- Juancarlo *Añez* tel:+58(414)901-2021 skype:juancarloanez

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