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:
What's new in 0.11?
The main change in this release is support for compiling the plugin with
a C++ compiler. Recent versions of GCC 4.7 are now built with C++ rather
than C, meaning that plugins must also be built with C++ (since all of
GCC’s internal symbols are name-mangled). This release fixes the
plugin’s Makefile so that it autodetects whether the plugin needs to be
built with a C or C++ compiler and (I hope) does the right thing
automatically. I've also made the necessary changes to the C source code
of the plugin so that it is compilable as either language.
This should enable the plugin to now be usable with recent builds of gcc
4.7.* (along with gcc 4.6).
The plugin doesn't yet support gcc 4.8 prereleases (help would be
For a description of the other improvements in 0.11, detailed release
notes can be seen at:
Tarball releases are available at:
Prebuilt-documentation can be seen at:
The project's homepage is:
The plugin and checker are Free Software, licensed under the GPLv3 or
eGenix.com mx Base Distribution
Version 3.2.5 for Python 2.4 - 2.7
Open Source Python extensions providing
important and useful services
for Python programmers.
This announcement is also available on our web-site for online reading:
The eGenix.com mx Base Distribution for Python is a collection of
professional quality software tools which enhance Python's usability
in many important areas such as fast text searching, date/time
processing and high speed data types.
The tools have a proven record of being portable across many Unix and
Windows platforms. You can write applications which use the tools on
Windows and then run them on Unix platforms without change due to the
consistent platform independent interfaces.
Contents of the distribution:
* mxDateTime - Easy to use Date/Time Library for Python
* mxTextTools - Fast Text Parsing and Processing Tools for Python
* mxProxy - Object Access Control for Python
* mxBeeBase - On-disk B+Tree Based Database Kit for Python
* mxURL - Flexible URL Data-Type for Python
* mxUID - Fast Universal Identifiers for Python
* mxStack - Fast and Memory-Efficient Stack Type for Python
* mxQueue - Fast and Memory-Efficient Queue Type for Python
* mxTools - Fast Everyday Helpers for Python
The package also include a number of helpful smaller modules in the
mx.Misc subpackage, such as mx.Misc.ConfigFile for config file parsing
or mx.Misc.CommandLine to quickly write command line applications in
All available packages have proven their stability and usefulness in
many mission critical applications and various commercial settings all
around the world.
For more information, please see the distribution page:
The 3.2.5 release of the eGenix mx Base Distribution is the latest
release of our open-source Python extensions.
The new patch-level version includes a few important fixes:
* Fixed a compatibility problem with Python 2.7.3 on Mac OS X 10.6
and later: Removed mx_customize_compiler() in favor of the standard
distutils customize_compiler(). It now installs fine again with pip
on more recent Mac OS X versions. Thanks to Leonardo Santagada for
bringing this problem to our attention.
* mxDateTime: Fixed a possible segfault in mxDateTime that was caused
by the lazy datetime module import mechanism not catching all cases
where the C API was used in mxDateTime. Thanks to Joel Rosdahl for
bringing this to our attention.
* Fixed a bug in the mx.Misc.CSV.Reader.objects() method, which
triggered a TypeError.
If you are upgrading from eGenix mx Base 3.1.x, please also see the
eGenix mx Base Distribution 3.2.0 release notes for details on what
has changed and which new features are available:
As always, we are providing pre-built binaries for all common
platforms: Windows 32/64-bit, Linux 32/64-bit, FreeBSD 32/64-bit, Mac
OS X 32/64-bit. Source code archives are available for installation on
all other Python platforms, such as Solaris, AIX, HP-UX, etc.
To simplify installation in Zope/Plone and other egg-based systems, we
have also precompiled egg distributions for all platforms. These are
available on our own PyPI-style index server for easy and automatic
Whether you are using a pre-built package or the source distribution,
installation is a simple "python setup.py install" command in all
cases. The only difference is that the pre-built packages do not
require a compiler or the Python development packages to be installed.
For a full list of changes, please refer to the eGenix mx Base Distribution
change log at
and the change logs of the various included Python packages.
The download archives and instructions for installing the packages can
be found on the eGenix mx Base Distribution page:
The eGenix mx Base package is distributed under the eGenix.com Public
License 1.1.0 which is an Open Source license similar to the Python
license. You can use the packages in both commercial and non-commercial
settings without fee or charge.
The package comes with full source code
Commercial support for this product is available from eGenix.com.
for details about our support offerings.
-- Marc-Andre Lemburg
Professional Python Services directly from the Source (#1, Nov 28 2012)
>>> Python Projects, Consulting and Support ... http://www.egenix.com/
>>> mxODBC.Zope/Plone.Database.Adapter ... http://zope.egenix.com/
>>> mxODBC, mxDateTime, mxTextTools ... http://python.egenix.com/
::: Try our new mxODBC.Connect Python Database Interface for free ! ::::
eGenix.com Software, Skills and Services GmbH Pastor-Loeh-Str.48
D-40764 Langenfeld, Germany. CEO Dipl.-Math. Marc-Andre Lemburg
Registered at Amtsgericht Duesseldorf: HRB 46611
This is a bugfix release fixing problems of installing with pip and
of initializing objects.
pyPEG 2 for Python 2.7 and 3.x
Python is a nice scripting language. It even gives you access to its own
parser and compiler. It also gives you access to different other parsers
for special purposes like XML and string templates.
But sometimes you may want to have your own parser. This is what's pyPEG
for. And pyPEG supports Unicode.
The source code for all you can find on bitbucket:
To build the documentation, you'll need YML 2. You can download YML
Homepage: http://fdik.org/yml/ Toolchain: http://fdik.org/yml2.tar.bz2
pyPEG 2 depends on lxml, see http://lxml.de/
Wenn Steinbrück „Urwahl“ hört, ruft der „Rolex!“
WSME-Soap 0.4.1 was released today.
It is a bugfix release.
* Fix date/time and binary input types handling
Christophe de Vienne
unicode is a simple python command line utility that displays
properties for a given unicode character, or searches
unicode database for a given name.
It was written with Linux in mind, but should work almost everywhere
(including MS Windows and MacOSX), UTF-8 console is recommended.
˙pɹɐpuɐʇs əpoɔı̣uՈ əɥʇ ɟo əsn pəɔuɐʌpɐ
puɐ səldı̣ɔuı̣ɹd əɥʇ ɓuı̣ʇɐɹʇsuoɯəp looʇ ɔı̣ʇɔɐpı̣p ʇuəlləɔxə uɐ sı̣ ʇI
˙sʇuı̣odəpoɔ ʇuəɹəɟɟı̣p ʎləʇəldɯoɔ ɓuı̣sn əlı̣ɥʍ 'sɥdʎlɓ ɟo ɯɐəɹʇs ɹɐlı̣ɯı̣s
ʎllɐnsı̣ʌ oʇuı̣ ʇxəʇ əɥʇ ʇɹəʌuoɔ oʇ pɹɐpuɐʇs əpoɔı̣uՈ əɥʇ ɟo ɹəʍod llnɟ
əɥʇ sʇı̣oldxə ʇɐɥʇ 'ʎʇı̣lı̣ʇn ,əpoɔɐɹɐd, oslɐ suı̣ɐʇuoɔ əɓɐʞɔɐd əɥ⊥
Changes since previous versions:
* add option to recognise binary input numerical codes
* do not throw an exception when run under an undefined locale
* on error, exit with nonzero existatus
* preliminary python3 support
* other minor tweaks and improvements
| Radovan Garabík http://kassiopeia.juls.savba.sk/~garabik/ |
| __..--^^^--..__ garabik @ kassiopeia.juls.savba.sk |
Antivirus alert: file .signature infected by signature virus.
Hi! I'm a signature virus! Copy me into your signature file to help me spread!
I'm pleased to announce the release of circuits 2.0.0 [cheetah]
This is a major release which includes breaking API changes from the
previous release 1.6.
Some of the highlights of this release include:
* Enhanced internal Event Generation for I/O components.
* Re-Implementation of call/wait synchronous primitives.
* Simplified API for Eventing and Channel targeting.
* Many more bug fixes and test coverage.
For more information see the PyPi page:
James Mills / prologic
What is cx_Freeze?
cx_Freeze is a set of scripts and modules for freezing Python scripts
into executables, in much the same way that py2exe and py2app do.
Unlike these two tools, cx_Freeze is cross platform and should work on
any platform that Python itself works on. It supports Python 2.3 or
higher, including Python 3.
Where do I get it?
The release notes can be read here as well:
1) Added support for the final release of Python 3.3.
2) Added support for copying the MSVC runtime DLLs and manifest if desired
by using the --include-msvcr switch. Thanks to Almar Klein for the initial p
3) Clarified the documentation on the --replace-paths option. Thanks to
Thomas Kluyver for the patch.
1) Producing a Mac distribution failed with a variable reference.
2) Freezing a script using PyQt on a Mac failed with a type error.
3) Version number reported was incorrect. (Issue #7)
4) Correct paths during installation on Windows. (Issue #11)
I am pleased to announce the first official
release of occmodel (v0.1.0) and the releated
occmodel is a small library which gives a high level access
to the OpenCASCADE modelling kernel.
For most users a direct use of the OpenCASCADE modelling
kernel can be quite a hurdle as it is a huge library.
The geometry can be visualized with the included viewer.
This viewer is utilizing modern OpenGL methods like GLSL
shaders and vertex buffers to ensure visual quality and
maximum speed. To use the viewer OpenGL version 2.1 is
Home page : http://github.com/tenko/occmodel
Documentation : http://tenko.github.com/occmodel/index.html
In addition the following related libraries are released:
geotools (required) : http://github.com/tenko/geotools
Documentation : http://tenko.github.com/geotools/index.html
gltools (optional) : http://github.com/tenko/gltools
Documentation : http://tenko.github.com/gltools/index.html
As this is the first official release some hurdles are expected
Binary installers are available for the Windows platform.
We're pleased to announce the 2.0 beta 1 release of PyPy. This release is
not a typical beta, in a sense the stability is the same or better than 1.9
and can be used in production. It does however include a few performance
regressions documented below that don't allow us to label is as 2.0 final.
(It also contains many performance improvements.)
The main features of this release are support for ARM processor and
compatibility with CFFI. It also includes
numerous improvements to the numpy in pypy effort, cpyext and performance.
You can download the PyPy 2.0 beta 1 release here:
What is PyPy?
PyPy is a very compliant Python interpreter, almost a drop-in replacement for
CPython 2.7.3. It's fast (`pypy 2.0 beta 1 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. It also supports ARM machines running Linux.
Windows 64 work is still stalling, we would welcome a volunteer
to handle that.
.. _`pypy 2.0 beta 1 and cpython 2.7.3`: http://bit.ly/USXqpP
How to use PyPy?
We suggest using PyPy from a `virtualenv`_. Once you have a virtualenv
installed, you can follow instructions from `pypy documentation`_ on how
to proceed. This document also covers other `installation schemes`_.
.. _`pypy documentation`:
.. _`virtualenv`: http://www.virtualenv.org/en/latest/
.. _`installation schemes`:
.. _`PyPy and pip`:
Reasons why this is not PyPy 2.0:
* the ``ctypes`` fast path is now slower than it used to be. In PyPy
1.9 ``ctypes`` was either incredibly faster or slower than CPython
you hit the fast path or not. Right now it's usually simply slower. We're
probably going to rewrite ``ctypes`` using ``cffi``, which will make it
* ``cffi`` (an alternative to interfacing with C code) is very fast, but
it is missing one optimization that will make it as fast as a native
call from C.
* ``numpypy`` lazy computation was disabled for the sake of simplicity.
We should reenable this for the final 2.0 release.
* ``cffi`` is officially supported by PyPy. You can install it normally by
using ``pip install cffi`` once you have installed `PyPy and pip`_.
The corresponding ``0.4`` version of ``cffi`` has been released.
* ARM is now an officially supported processor architecture.
PyPy now work on soft-float ARM/Linux builds. Currently ARM processors
supporting the ARMv7 and later ISA that include a floating-point unit are
* This release contains the latest Python standard library 2.7.3 and is fully
compatible with Python 2.7.3.
* It does not however contain hash randomization, since the solution present
in CPython is not solving the problem anyway. The reason can be
found on the `CPython issue tracker`_.
* ``gc.get_referrers()`` is now faster.
* Various numpy improvements. The list includes:
* axis argument support in many places
* full support for fancy indexing
* ``complex128`` and ``complex64`` dtypes
* `JIT hooks`_ are now a powerful tool to introspect the JITting process that
* ``**kwds`` usage is much faster in the typical scenario
* operations on ``long`` objects are now as fast as in CPython (from
roughly 2x slower)
* We now have special strategies for ``dict``/``set``/``list`` which contain
unicode strings, which means that now such collections will be both faster
and more compact.
.. _`cpython issue tracker`: http://bugs.python.org/issue14621
.. _`jit hooks`: http://doc.pypy.org/en/latest/jit-hooks.html
Things we're working on
There are a few things that did not make it to the 2.0 beta 1, which
are being actively worked on. Greenlets support in the JIT is one
that we would like to have before 2.0 final. Two important items that
will not make it to 2.0, but are being actively worked on, are:
* Faster JIT warmup time.
* Software Transactional Memory.
Maciej Fijalkowski, Armin Rigo and the PyPy team