Mailman 3 May 2013 - Python-announce-list

Pint 0.2 released. Python units library
by Hernan Grecco 12 May '13

12 May '13

Hi, We are happy to announce Pint 0.2. Pint is a Python package to define, operate and manipulate physical quantities: the product of a numerical value and a unit of measurement. This release brings a lot of new exciting features including extended NumPy support, temperature conversion, implementation of the Buckingham Pi Theorem and support for values with uncertainties. Check out the blog post for more details: http://python-in-the-lab.blogspot.com.ar/2013/05/a-pint-day.html You can get pint using pip: $ pip install pint or get the source code: https://github.com/hgrecco/pint and check the docs: http://pint.readthedocs.org/ What is Pint? --- Pint is Python package to define, operate and manipulate physical quantities: the product of a numerical value and a unit of measurement. It allows arithmetic operations between them and conversions from and to different units. It is distributed with a comprehensive list of physical units, prefixes and constants. Due to it’s modular design, you can extend (or even rewrite!) the complete list without changing the source code. It has a complete test coverage. It runs in Python 2.7 and 3.X with no other dependency. It licensed under BSD. Highlights --- * Unit parsing: prefixed and pluralized forms of units are recognized without explicitly defining them. In other words: as the prefix kilo and the unit meter are defined, Pint understands kilometers. This results in a much shorter and maintainable unit definition list as compared to other packages. * Standalone unit definitions: units definitions are loaded from a text file which is simple and easy to edit. Adding and changing units and their definitions does not involve changing the code. * Advanced string formatting: a quantity can be formatted into string using PEP 3101 syntax. Extended conversion flags are given to provide symbolic, latex and pretty formatting. * Free to choose the numerical type: You can use any numerical type (fraction, float, decimal, numpy.ndarray, etc). NumPy is not required but supported. * NumPy integration: When you choose to use a NumPy ndarray, its methods and ufuncs are supported including automatic conversion of units. For example numpy.arccos(q) will require a dimensionless q and the units of the output quantity will be radian. * Handle temperature: conversion between units with different reference points, like positions on a map or absolute temperature scales. * Small codebase: easy to maintain codebase with a flat hierarchy. * Dependency free: it depends only on Python and it’s standard library. * Python 2 and 3: a single codebase that runs unchanged in Python 2.7+ and Python 3.0+. Thanks to the people that contributed bug reports, suggestions and patches. In particular to: Richard Barnes, Alexander Böhn, Dave Brooks, Giel van Schijndel, Brend Wanders Enjoy! Hernán

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Template Data Interface (tdi) 0.9.9.7
by André Malo 12 May '13

12 May '13

Hello World! I'm pleased to announce version 0.9.9.7 of TDI. About TDI ========= TDI is a markup templating system written in python with (optional but recommended) speedup code written in C. It features strict markup / logic separation, is very fast and provides powerful tools for template manipulation. About Release 0.9.9.7 ===================== The following features have been added: * Support for plain text templates * More C code, speeding up the parsing and filtering process * Support for more python implementations Supported Python Versions ========================= * Python 2.4 - 2.7 * PyPy 1.9, 2.0 (Python only) * Jython 2.5, 2.7 (Python only) License ======= TDI is available under the terms and conditions of the "Apache License, Version 2.0." TODO ==== * better framework integration * python 3 support Links ===== * Homepage + Documentation: http://opensource.perlig.de/tdi/ * PyPI: https://pypi.python.org/pypi/tdi * License: http://www.apache.org/licenses/LICENSE-2.0 André "nd" Malo

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Announce : LDTP 3.5.0 - Linux GUI test automation tool
by Nagappan Alagappan 11 May '13

11 May '13

Hello, New API: * inserttext, objtimeout, guitimeout, getcellsize, getcellvalue, getobjectnameatcoords, getcombovalue, getaccesskey in Python client * doubleClick, doubleClickRow, onWindowCreate, getCellSize, getComboValue, appUnderTest, getAccessKey in Java client * getcellsize, getcellvalue in Ruby client * GetCellSize, GetComboValue, AppUnderTest, GetAccessKey, MouseRightClick, DoubleClick, DoubleClickRow, RightClick in C# client New control type: * POPUP MENU for Ubuntu environment Bugs fixed: Ruby client: * Fixed optional arguments to imagecapture * Check window_name parameter, if empty then use @window_name passed in constructor Python client: * Fixed optional argument APIs to work on both Windows and Linux * imagecapture x, y offset, height and width parameters are disregarded if window parameter is provided - Bug#685548 * Return unicode string all the time on gettextvalue * Fix partial match argument in selectrow, compatible with Windows * Patch by ebass to support Python 2.6 * Added Errno 101 as we see in ebass Ubuntu 10.04 environment Core LDTP2 * Include label type on gettextvalue * Don't include separators in the list Perl client: * Added perl client Credit: * Sawyer X for the Perl interface * ebass (IRC nick name) * Marek Rosa <marek.j.rosa(a)gmail.com> * Thanks to all others who have reported bugs through forum / email / in-person / IRC About LDTP: Cross Platform GUI Automation tool Linux version is LDTP, Windows version is Cobra and Mac version is PyATOM. * Linux version is known to work on GNOME / KDE (QT >= 4.8) / Java Swing / LibreOffice / Mozilla application on all major Linux distribution. * Windows version is known to work on application written in .NET / C++ / Java / QT on Windows XP SP3 / Windows 7 / Windows 8 development version. * Mac GUI testing is known to work on OS X Snow Leopard/Lion/Mountain Lion. Where ever PyATOM runs, LDTP should work on it. Download source: https://github.com/ldtp/ldtp2 Download binary (RPM / DEB): http://download.opensuse.org/repositories/home:/anagappan:/ldtp2:/ Documentation references: For detailed information on LDTP framework and latest updates visit http://ldtp.freedesktop.org For information on various APIs in LDTP including those added for this release can be got from http://ldtp.freedesktop.org/user-doc/index.html Java doc - http://ldtp.freedesktop.org/javadoc/ Report bugs - http://ldtp.freedesktop.org/wiki/Bugs To subscribe to LDTP mailing lists, visit http://ldtp.freedesktop.org/wiki/Mailing_20list IRC Channel - #ldtp on irc.freenode.net How can you help: Spread the news and send back your feedback to us Thanks Nagappan -- Cross platform GUI testing Linux Desktop (GUI Application) Testing Project - http://ldtp.freedesktop.org Cobra - Windows GUI Automation tool - https://github.com/ldtp/cobra ATOMac - Mac GUI Automation tool - https://github.com/pyatom/pyatom http://nagappanal.blogspot.com

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Karlsruhe (Germany) Python User Group, May 17th 2013, 7pm
by Jürgen A. Erhard 09 May '13

09 May '13

The Karlsruhe Python User Group (KaPy) meets again. Friday, 2013-05-17 (May 17th) at 19:00 (7pm) in the rooms of Entropia eV (the local affiliate of the CCC). See http://entropia.de/wiki/Anfahrt on how to get there. For your calendars: meetings are held monthly, on the 3rd Friday. There's also a mailing list at https://lists.bl0rg.net/cgi-bin/mailman/listinfo/kapy.

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Kiwi PyCon 2013 Call for Proposals is now open! (closes 01 June)
by Danny Adair 09 May '13

09 May '13

Dear fellow Pythonistas, We're pleased to announce that Kiwi PyCon 2013's Call for Proposals is now open! This year the conference will be held Saturday 06 and Sunday 07 September in Auckland, New Zealand. Friday 05 September will see tutorials and workshops run during the day - a Kiwi PyCon first! The deadline for proposal submission is Saturday 01 June 2013. For more information please visit http://nz.pycon.org/call-for-proposals/ Looking forward to seeing you in Auckland in September! -- Danny W. Adair Event Director Kiwi PyCon 2013

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PyPy 2.0 - Einstein Sandwich
by Maciej Fijalkowski 09 May '13

09 May '13

We're pleased to announce PyPy 2.0. This is a stable release that brings a swath of bugfixes, small performance improvements and compatibility fixes. PyPy 2.0 is a big step for us and we hope in the future we'll be able to provide stable releases more often. You can download the PyPy 2.0 release here: http://pypy.org/download.html The two biggest changes since PyPy 1.9 are: * stackless is now supported including greenlets, which means eventlet and gevent should work (but read below about gevent) * PyPy now contains release 0.6 of `cffi`_ as a builtin module, which is preferred way of calling C from Python that works well on PyPy .. _`cffi`: http://cffi.readthedocs.org If you're using PyPy for anything, it would help us immensely if you fill out the following survey: http://bit.ly/pypysurvey This is for the developers eyes and we will not make any information public without your agreement. What is PyPy? ============= PyPy is a very compliant Python interpreter, almost a drop-in replacement for CPython 2.7. It's fast (`pypy 2.0 and cpython 2.7.3`_ performance comparison) due to its integrated tracing JIT compiler. This release supports x86 machines running Linux 32/64, Mac OS X 64 or Windows 32. Windows 64 work is still stalling, we would welcome a volunteer to handle that. ARM support is on the way, as you can see from the recently released alpha for ARM. .. _`pypy 2.0 and cpython 2.7.3`: http://speed.pypy.org Highlights ========== * Stackless including greenlets should work. For gevent, you need to check out `pypycore`_ and use the `pypy-hacks`_ branch of gevent. * cffi is now a module included with PyPy. (`cffi`_ also exists for CPython; the two versions should be fully compatible.) It is the preferred way of calling C from Python that works on PyPy. * Callbacks from C are now JITted, which means XML parsing is much faster. * A lot of speed improvements in various language corners, most of them small, but speeding up some particular corners a lot. * The JIT was refactored to emit machine code which manipulates a "frame" that lives on the heap rather than on the stack. This is what makes Stackless work, and it could bring another future speed-up (not done yet). * A lot of stability issues fixed. * Refactoring much of the numpypy array classes, which resulted in removal of lazy expression evaluation. On the other hand, we now have more complete dtype support and support more array attributes. .. _`pypycore`: https://github.com/gevent-on-pypy/pypycore/ .. _`pypy-hacks`: https://github.com/schmir/gevent/tree/pypy-hacks Cheers, fijal, arigo and the PyPy team

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MacroPy 0.1.2: Macros for Pythoon. Quasiquotes, Case Classes, Pattern Matching, LINQ and more!
by Haoyi Li 08 May '13

08 May '13

Hey All, MacroPy is an implementation of Macros in the Python Programming, providing a mechanism for user-defined functions (macros) to perform transformations on the abstract syntax tree(AST) of Python code at module import time. This is an easy way to modify the semantics of a python program in ways which are otherwise impossible, for example providing an extremely concise way of declaring classes: @case class Point(x, y) p = Point(1, 2) print p.x # 1 print p # Point(1, 2) Apart from this, we've used MacroPy's macros to implement a pretty impressive list of features: - Quasiquotes - String Interpolation - Pyxl, integrating XML markup into a Python program - Tracing and Smart Asserts - Case Classes, easy Algebraic Data Types from Scala - Pattern Matching from the Functional Programming world - LINQ to SQL from C# - Quick Lambdas from Scala and Groovy, - Parser Combinators, inspired by Scala's. The full documentation is over on github (https://github.com/lihaoyi/macropy) if anyone wants to check it out. It runs fine on both CPython 2.7 and PyPy 1.9, and I've just pushed the last up-to-date version of MacroPy to PyPI: https://pypi.python.org/pypi/MacroPy Hope someone finds this useful! Thanks! -Haoyi

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ANN: Scopt - Python small ERP
by gallas.robert＠gmail.com 08 May '13

08 May '13

Hello, I would like to introduce Scopt - Python ERP like project. Project URL: http://code.google.com/p/scopt/ Project version: 0.0.005 - POC Project license: Apache License 2.0 (License matrix is not finished yet.) Project was started out as search for Java alternative in area of business software development. Project is divided into: - Scopt - business Core(engine), - Magua - referential GUI implementation - TinyESB - mediation like engine and framework. Architecture of solution is built on asynchronous message passing (mediation). We try to make Scopt easy testable, client and transport layer agnostic with flexible deployment model. Technologies used: Language - Python 2.7.3 DB abstraction - SQLAlchemy - core DB - SQLite, (Oracle and PostgreSql will be supported) HTTP connector - Tornado async web server. GUI referential implementation is developed in Dojo. Android client is planned. For now, main design is outlined and most of implementation details and API are stabilized. We learn Python as we code the project. Any comments on programming style, or following python standards and idioms are welcomed. Robert Gallas gallas.robert(a)gmail.com <p> <a href="http://code.google.com/p/scopt/">Scopt 0.0.005</a> Python ERP like project (09-May-2013) </p>

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gui2py 2nd alpha (0.9b): "pythoncard spin-off" with python 3 + wx phoenix support, released
by Mariano Reingart 08 May '13

08 May '13

I'm glad to announce the second alpha release of gui2py, a simple & powerful GUI framework (derivated from PythonCard) for agile development of modern cross-platform "visual" desktop applications on Windows, Mac OS X, and Linux, using the Python language and the wxPython toolkit. https://code.google.com/p/gui2py/ The focus of this release was to add support for Python 3 and the Phoenix project (the upcoming wxPython version 3.0), but it also looks for compatibility between multiple python and wxPython versions, from py2.5 to py3.3, and wx2.8 (stable) to wx2.9 (classic & phoenix). Changelog 0.9a -> 0.9b: * fixed support for py2.5 wx2.8 ("stable") * added support for py3k & wx2.9.5.81 phoenix * minor fixes * conversion / setup / build scripts Installers and source archive can be downloaded from: https://code.google.com/p/gui2py/downloads/list Installation guide and screenshots were also updated (including py3k and phoenix): https://code.google.com/p/gui2py/wiki/QuickStart https://code.google.com/p/gui2py/wiki/SampleScreenshots Best regards, Mariano Reingart http://www.sistemasagiles.com.ar http://reingart.blogspot.com

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ANN: Spyder v2.2
by Pierre Raybaut 08 May '13

08 May '13

Hi all, On the behalf of Spyder's development team ( http://code.google.com/p/spyderlib/people/list), I'm pleased to announce that Spyder v2.2 has been released and is available for Windows XP/Vista/7/8, GNU/Linux and MacOS X: http://code.google.com/p/spyderlib/. This release represents 18 months of development since v2.1 and introduces major enhancements and new features: * Full support for IPython v0.13, including the ability to attach to existing kernels * New MacOS X application * Much improved debugging experience * Various editor improvements for code completion, zooming, auto insertion, and syntax highlighting * Better looking and faster Object Inspector * Single instance mode * Spanish tranlation of the interface * And many other changes: http://code.google.com/p/spyderlib/wiki/ChangeLog This is the last release to support Python 2.5: * Spyder 2.2 supports Python 2.5 to 2.7 * Spyder 2.3 will support Python 2.7 and Python 3 * (Spyder 2.1.14dev4 is a development release which already supports Python 3) See also https://code.google.com/p/spyderlib/downloads/list. Spyder is a free, open-source (MIT license) interactive development environment for the Python language with advanced editing, interactive testing, debugging and introspection features. Originally designed to provide MATLAB-like features (integrated help, interactive console, variable explorer with GUI-based editors for dictionaries, NumPy arrays, ...), it is strongly oriented towards scientific computing and software development. Thanks to the `spyderlib` library, Spyder also provides powerful ready-to-use widgets: embedded Python console (example: http://packages.python.org/guiqwt/_images/sift3.png), NumPy array editor (example: http://packages.python.org/guiqwt/_images/sift2.png), dictionary editor, source code editor, etc. Description of key features with tasty screenshots can be found at: http://code.google.com/p/spyderlib/wiki/Features Don't forget to follow Spyder updates/news: * on the project website: http://code.google.com/p/spyderlib/ * and on our official blog: http://spyder-ide.blogspot.com/ Last, but not least, we welcome any contribution that helps making Spyder an efficient scientific development/computing environment. Join us to help creating your favourite environment! (http://code.google.com/p/spyderlib/wiki/NoteForContributors) Enjoy! -Pierre

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Python-announce-list May 2013