Mailman 3 May 2015 - Python-announce-list

Crochet 1.4.0: use Twisted anywhere!
by Itamar Turner-Trauring 07 May '15

07 May '15

Crochet is an MIT-licensed library that makes it easier to use Twisted from regular blocking code: from __future__ import print_function from twisted.names import client from crochet import setup, wait_for setup() @wait_for(timeout=5.0) def gethostbyname(name): """Use the Twisted DNS library.""" d = client.lookupAddress(name) d.addCallback(lambda result: result[0][0].payload.dottedQuad()) return d if __name__ == '__main__': # Application code using the public API - notice it works in a normal # blocking manner, with no event loop visible: import sys name = sys.argv[1] ip = gethostbyname(name) print(name, "->", ip) New in 1.4.0 is Python 3.4 support as well as support for using Crochet with uWSGI, and additional documentation on workarounds for various limitations of Crochet. https://pypi.python.org/pypi/crochet for downloads. https://crochet.readthedocs.org/ for documentation. --Itamar Turner-Trauring

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ANN: gcc-python-plugin 0.14
by David Malcolm 06 May '15

06 May '15

gcc-python-plugin is a plugin for GCC 4.6 onwards which embeds the CPython interpreter within GCC, allowing you to write new compiler warnings in Python, generate code visualizations, etc. It ships with "gcc-with-cpychecker", which implements static analysis passes for GCC aimed at finding bugs in CPython extensions. In particular, it can automatically detect reference-counting errors: http://gcc-python-plugin.readthedocs.org/en/latest/cpychecker.html This release adds support for GCC 5. Tarball releases are available at: https://fedorahosted.org/releases/g/c/gcc-python-plugin/ Prebuilt-documentation can be seen at: http://gcc-python-plugin.readthedocs.org/en/latest/index.html The project's homepage is: https://fedorahosted.org/gcc-python-plugin/ The plugin and checker are Free Software, licensed under the GPLv3 or later. Enjoy! Dave Malcolm

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ANN: PyTables 3.2.0 (final) released!
by Francesc Alted 06 May '15

06 May '15

=========================== Announcing PyTables 3.2.0 =========================== We are happy to announce PyTables 3.2.0. ******************************* IMPORTANT NOTICE: If you are a user of PyTables, it needs your help to keep going. Please read the next thread as it contains important information about the future (or the lack of it) of the project: https://groups.google.com/forum/#!topic/pytables-users/yY2aUa4H7W4 Thanks! ******************************* What's new ========== This is a major release of PyTables and it is the result of more than a year of accumulated patches, but most specially it fixes a couple of nasty problem with indexed queries not returning the correct results in some scenarios. There are many usablity and performance improvements too. In case you want to know more in detail what has changed in this version, please refer to: http://www.pytables.org/release_notes.html You can install it via pip or download a source package with generated PDF and HTML docs from: http://sourceforge.net/projects/pytables/files/pytables/3.2.0 For an online version of the manual, visit: http://www.pytables.org/usersguide/index.html What it is? =========== PyTables is a library for managing hierarchical datasets and designed to efficiently cope with extremely large amounts of data with support for full 64-bit file addressing. PyTables runs on top of the HDF5 library and NumPy package for achieving maximum throughput and convenient use. PyTables includes OPSI, a new indexing technology, allowing to perform data lookups in tables exceeding 10 gigarows (10**10 rows) in less than a tenth of a second. Resources ========= About PyTables: http://www.pytables.org About the HDF5 library: http://hdfgroup.org/HDF5/ About NumPy: http://numpy.scipy.org/ Acknowledgments =============== Thanks to many users who provided feature improvements, patches, bug reports, support and suggestions. See the ``THANKS`` file in the distribution package for a (incomplete) list of contributors. Most specially, a lot of kudos go to the HDF5 and NumPy makers. Without them, PyTables simply would not exist. Share your experience ===================== Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. ---- **Enjoy data!** -- The PyTables Developers

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ANN: python-blosc 1.2.7 released
by Francesc Alted 06 May '15

06 May '15

============================= Announcing python-blosc 1.2.7 ============================= What is new? ============ Updated to use c-blosc v1.6.1. Although that this supports AVX2, it is not enabled in python-blosc because we still need a way to devise how to detect AVX2 in the underlying platform. At any rate, c-blosc 1.6.1 fixed an important bug in the blosclz codec that a release was deemed important. For more info, you can have a look at the release notes in: https://github.com/Blosc/python-blosc/wiki/Release-notes More docs and examples are available in the documentation site: http://python-blosc.blosc.org What is it? =========== Blosc (http://www.blosc.org) is a high performance compressor optimized for binary data. It has been designed to transmit data to the processor cache faster than the traditional, non-compressed, direct memory fetch approach via a memcpy() OS call. Blosc is the first compressor that is meant not only to reduce the size of large datasets on-disk or in-memory, but also to accelerate object manipulations that are memory-bound (http://www.blosc.org/docs/StarvingCPUs.pdf). See http://www.blosc.org/synthetic-benchmarks.html for some benchmarks on how much speed it can achieve in some datasets. Blosc works well for compressing numerical arrays that contains data with relatively low entropy, like sparse data, time series, grids with regular-spaced values, etc. python-blosc (http://python-blosc.blosc.org/) is the Python wrapper for the Blosc compression library. There is also a handy tool built on Blosc called Bloscpack (https://github.com/Blosc/bloscpack). It features a commmand line interface that allows you to compress large binary datafiles on-disk. It also comes with a Python API that has built-in support for serializing and deserializing Numpy arrays both on-disk and in-memory at speeds that are competitive with regular Pickle/cPickle machinery. Installing ========== python-blosc is in PyPI repository, so installing it is easy: $ pip install -U blosc # yes, you should omit the python- prefix Download sources ================ The sources are managed through github services at: http://github.com/Blosc/python-blosc Documentation ============= There is Sphinx-based documentation site at: http://python-blosc.blosc.org/ Mailing list ============ There is an official mailing list for Blosc at: blosc(a)googlegroups.com http://groups.google.es/group/blosc Licenses ======== Both Blosc and its Python wrapper are distributed using the MIT license. See: https://github.com/Blosc/python-blosc/blob/master/LICENSES for more details. ---- **Enjoy data!** -- Francesc Alted

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Wing IDE 5.1.4 released
by Wingware 04 May '15

04 May '15

Hi, Wingware has released version 5.1.4 of Wing IDE, our cross-platform integrated development environment for the Python programming language. Wing IDE features a professional code editor with vi, emacs, visual studio, and other key bindings, auto-completion, call tips, context-sensitive auto-editing, goto-definition, find uses, refactoring, a powerful debugger, version control, unit testing, search, project management, and many other features. This release includes the following improvements: Find Symbol in Project dialog Support Django 1.8 Support debugging Django with auto-reload enabled Basic support for Python 3.5 alpha Change Case operations to Source menu Fix alignment of monospaced characters on OS X and Linux Improve pytest support Fix several code analysis problems About 40 other bug fixes and improvements For details see http://wingware.com/news/2015-05-01 and http://wingware.com/pub/wingide/5.1.4/CHANGELOG.txt What's New in Wing 5.1: Wing IDE 5.1 adds multi-process and child process debugging, syntax highlighting in the shells, support for pytest, Find Symbol in Project, persistent time-stamped unit test results, auto-conversion of indents on paste, an XCode keyboard personality, support for Flask, Django 1.7 and 1.8, Python 3.5 and recent Google App Engine versions, improved auto-completion for PyQt, recursive snippet invocation, and many other minor features and improvements. Free trial: http://wingware.com/wingide/trial Downloads: http://wingware.com/downloads Feature list: http://wingware.com/wingide/features Sales: http://wingware.com/store/purchase Upgrades: https://wingware.com/store/upgrade Questions? Don't hesitate to email us at support(a)wingware.com. Thanks, -- Stephan Deibel Wingware | Python IDE The Intelligent Development Environment for Python Programmers wingware.com

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EuroPython 2015: Vote for the talks you want to see
by M.-A. Lemburg 04 May '15

04 May '15

Having received over 300 great proposals for talks, trainings, helpdesks and posters, we now call out to all attendees to vote for what you want to see on the conference schedule. You can search for topics and communicate your personal priorities by casting your vote for each submission on our talk voting page: *** Attendees: This is your chance to shape the conference ! *** https://ep2015.europython.eu/en/talk-voting/ Talk voting will be open until Friday, May 15. The program workgroup (WG) will then use the talk voting results as basis for their talk selection and announce the schedule late in May. Enjoy, -- EuroPython 2015 Team http://ep2015.europython.eu/ http://www.europython-society.org/

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EuroPython 2015: Financial Aid Program launched
by M.-A. Lemburg 03 May '15

03 May '15

We are happy to announce a program for people in need of financial aid to attend EuroPython. You can find all the details on our financial aid page: *** Financial Aid Program *** https://ep2015.europython.eu/en/financial-aid/ In short, we will be giving out grants in three categories: * Ticket discounts * Free tickets * Travel costs and accommodation Anyone who wants to attend EuroPython 2015 can apply, including people who have already purchased tickets. We want to make the event affordable for as many people as possible. Looking for financial aid sponsors ---------------------------------- We are still looking for sponsors to increase the budget we have available for financial aid. If your company would like to sign up as financial aid sponsor, please contact the sponsors team: https://ep2015.europython.eu/en/sponsor/ Enjoy, -- EuroPython 2015 Team http://ep2015.europython.eu/ http://www.europython-society.org/

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Jython 2.7.0 final released!
by fwierzbicki＠gmail.com 03 May '15

03 May '15

On behalf of the Jython development team, I'm pleased to announce that Jython 2.7.0 is finally here! Thanks to Amobee for sponsoring my work on Jython, and thanks to the many contributors to Jython! Details are here: http://fwierzbicki.blogspot.com/2015/05/jython-270-final-released.html

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ANN Nanpy 0.9.4
by Andrea Stagi 02 May '15

02 May '15

Hi, I'm happy to announce Nanpy 0.9.4 release. https://pypi.python.org/pypi/nanpy/0.9.4 This release includes some bug fixing and rtscts parameter support for SerialManager, if you're experiencing some problems with Nanpy on Raspberry Pi please set it to True (here an example: https://github.com/DjangoBeer/minecraftpi-hack/blob/master/altimeter/altime… ). How to start using Nanpy: http://nanpy.github.io/ With Nanpy you can easily use your Arduino board writing Python code from any device: a = ArduinoApi() a.pinMode(13, a.OUTPUT) a.digitalWrite(13, a.HIGH) We support OneWire, Lcd, Stepper, Servo, DallasTemperature and many more libraries… Let’s try to connect our 16x2 lcd screen on pins 7, 8, 9, 10, 11, 12 and show your first “Hello world”! from nanpy import Lcd lcd = Lcd([7, 8, 9, 10, 11, 12], [16, 2]) lcd.printString('Hello World!') Nanpy is an open source project, you can follow our work on Github https://github.com/nanpy There are several project made with Nanpy, an old RC car now powered by Raspberry Pi and Arduino and controlled via Android ( https://www.youtube.com/watch?v=iepyMyFNtjk https://github.com/chickenfootcar), Smart Gardening ( https://www.youtube.com/watch?v=n6hN1xkelKA), Minecraft Altimeter ( https://www.youtube.com/watch?v=HP8vbUTTDto https://github.com/DjangoBeer/minecraftpi-hack/tree/master/altimeter) -- Andrea Stagi (@4stagi) - DeveLover @Nephila Job profile: http://linkedin.com/in/andreastagi Website: http://4spills.blogspot.it/ Github: http://github.com/astagi

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ANN: AES/Python v1.0, an implementation of AES
by Mok-Kong Shen 01 May '15

01 May '15

AES/Python is an implementation of AES in Python with examples of counter mode operations and encryption (with authentication) with PCBC (block-chaining) The implementation of AES in this software follows the pseudo-code in FIPS-197 very closely and neglects all feasible optimization tricks so as to maximize the readability and hence ease of verification which is obviously very essential for gaining users' trust nowadays in any IT-security software in general. The softwaare also includes a function to generate pseudo-random byte sequences with AES in counter mode and a function to encrypt an arbitrarily long 16-byte block sequence according to PCBC (block-chaining), paired with a function to decrypt. PCBC works analogously to CBC with the difference that, instead of employing the ciphertext of the immediately previous block to xor with the plaintext of the current block, one employs a certain suitable (nonlinear) accumulated value of all previous plaintext and ciphertext blocks. Since at the end of processing the last chaining value can be used as a superior integrity check, PCBC is a one-pass encryption processing with integrity check. The software is available at: http://s13.zetaboards.com/Crypto/topic/7385224/1/ M. K. Shen

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