I'm pleased to announce a new release of the mock module, the first in a
while. Konrad Delong has joined me as a maintainer of mock and has been
a great help in getting this release out. As there are several major new
features this is a beta release, with 0.7.0 final coming out in a few
weeks assuming there are no major problems discovered. Please download
it and try it out:
mock is a Python module that provides a core Mock class. It is intended
to reduce the need for creating a host of trivial stubs throughout your
test suite. After performing an action, you can make assertions about
which methods / attributes were used and arguments they were called
with. You can also specify return values and set needed attributes in
the normal way.
mock is tested on Python versions 2.4-2.7 and Python 3.
Full documentation is included in the distribution.
Changes in 0.7.0 (including the much awaited magic method support) are:
* Addition of ``mocksignature``
* Ability to mock magic methods
* Ability to use patch and patch.object as class decorators
* Renamed ``patch_object`` to ``patch.object`` (``patch_object`` is
* Addition of ``MagicMock`` class with all magic methods pre-created for you
* Python 3 compatibility (tested with 3.2 but should work with 3.0 & 3.1 as
* Addition of ``patch.dict(...)`` for changing dictionaries during a test
* Addition of ``mocksignature`` argument to ``patch`` and ``patch_object``
* ``help(mock)`` works now (on the module). Can no longer use ``__bases__``
as a valid sentinel name (thanks to Stephen Emslie for reporting and
* Addition of soft comparisons: call_args, call_args_list and method_calls
return now tuple-like objects which compare equal even when empty args
or kwargs are skipped
* Added some docstrings.
* BUGFIX: ``side_effect`` now works with ``BaseException`` exceptions like
* BUGFIX: patching the same object twice now restores the patches correctly
* The tests now require `unittest2 <http://pypi.python.org/pypi/unittest2>`_
* `Konrad Delong <http://konryd.blogspot.com/>`_ added as co-maintainer
The main tasks before a 0.7.0 final release are finishing the
documentation and docstrings, plus allowing `patch.dict(...)` to act as
a context manager (currently decorator only).
All the best,
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*** Attention Cygwin Python module package maintainers: ***
*** Cygwin has migrated from Python 2.5 to 2.6. ***
*** Please build, test, and release your packages ASAP. ***
I have updated the version of Python to 2.6.5-2. The tarballs should be
available on a Cygwin mirror near you shortly.
The following are the changes since the previous release:
o promote from experimental to current
o build against ncursesw (instead of ncurses)
o export PySignal_SetWakeupFd (used by PyGObject/PyGtk)
o build _ctypes module against Cygwin's libffi
o change /usr/bin/python to be a copy instead of a symlink, so
Cygwin Python is directly executable from Windows
Note if you upgrade to 2.6.5-2, then any Python 2.5 module will no
Python is an interpreted, interactive, object-oriented programming
language. If interested, see the Python web site for more details:
Please read the README file:
since it covers requirements, installation, known issues, etc.
To update your installation, click on the "Install Cygwin now" link on
the http://cygwin.com/ web page. This downloads setup.exe to your
system. Then, run setup and answer all of the questions.
If you have questions or comments, please send them to the Cygwin
mailing list at: cygwin(a)cygwin.com .
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On behalf of the Python development team, I'm tickled pink to announce the
second release candidate of Python 2.7.
Python 2.7 is scheduled (by Guido and Python-dev) to be the last major version
in the 2.x series. However, 2.7 will have an extended period of bugfix
2.7 includes many features that were first released in Python 3.1. The faster io
module, the new nested with statement syntax, improved float repr, set literals,
dictionary views, and the memoryview object have been backported from 3.1. Other
features include an ordered dictionary implementation, unittests improvements, a
new sysconfig module, auto-numbering of fields in the str/unicode format method,
and support for ttk Tile in Tkinter. For a more extensive list of changes in
2.7, see http://doc.python.org/dev/whatsnew/2.7.html or Misc/NEWS in the Python
To download Python 2.7 visit:
While this is a preview release and is thus not suitable for production use, we
strongly encourage Python application and library developers to test the release
with their code and report any bugs they encounter to:
This helps ensure that those upgrading to Python 2.7 will encounter as few bumps
2.7 documentation can be found at:
benjamin at python.org
(on behalf of the entire python-dev team and 2.7's contributors)
I am pleased to announce version 2.21.3 of the Python bindings for GObject.
The new release is available from ftp.gnome.org as and its mirrors as
soon as its synced correctly:
What's new since PyGObject 2.21.2?
- Proper handling of null-ok in virtual methods (Ludovic L'Hours)
- Fall back to use the floating references API in glib if
there isn't a sinkfunc defined. (Tomeu Vizoso)
- Revert "Drop sinkfuncs." (Tomeu Vizoso)
- [giounix] Make it possible to compile on glib 2.20 (Johan Dahlin)
- Release the lock when potentially invoking Python code.
GObject is an object system library used by GTK+ and GStreamer.
PyGObject provides a convenient wrapper for the GObject library for use
in Python programs, and takes care of many of the boring details such as
managing memory and type casting. When combined with PyGTK, and
gnome-python, it can be used to write full featured Gnome applications.
Like the GObject library itself PyGObject is licensed under the
GNU LGPL, so is suitable for use in both free software and proprietary
applications. It is already in use in many applications ranging
from small single purpose scripts up to large full
PyGObject requires glib >= 2.22.4 and Python >= 2.3.5 to build.
GIO bindings require glib >= 2.22.4.
Please remember that this is an unstable release and shouldn't be used
The PyGObject team
PyCon Australia 2010, to be held at the Sydney Masonic Center over the
weekend of June 26 and 27, is only days away.
REGISTRATION WILL CLOSE TOMORROW (JUNE 22) AT 1PM!
You have until 1PM tomorrow to register and pay.
Register here: http://pycon-au.org/reg
We will NOT be accepting registrations at the door. We will NOT be
accepting money at the door. If you're registered and haven't paid by
tomorrow you will not have a seat at the conference dinner.
PyCon Australia 2010
what is it
A Python package to parse and build CSS Cascading Style Sheets. (Not a
about this release
0.9.7b3 is a beta release but quite stable.
+ API CHANGE: Changed parameters of script/utility function
- parameter ``resolveVariables=True`` now (default was
- ``minify = True`` will not parse Comments at all. This is
not really a change as comments were not kept in a minified stylesheet
anyway but this may speed up stylesheet combination a bit
+ **PERFORMANCE/IMPROVEMENT**: Added parameter
``parseComments=True`` to CSSParser. If parsing with ``parser =
cssutils.CSSParser(parseComments=False).parse...`` comments in a given
stylesheet are simple omitted from the resulting stylesheet DOM.
+ **PERFORMANCE**: Compiled productions in cssutils tokenizer are
cached now (to clear it use
``cssutils.tokenize2._TOKENIZER_CACHE.clear()``) which results in a
slight performance improvement. Thanks to moscovich!
cssutils is published under the LGPL version 3 or later, see
If you have other licensing needs please let me know.
For download options see http://cthedot.de/cssutils/
cssutils needs Python 2.4 or higher or Jython 2.5 and higher (tested
with Python 2.6.5(x64), 2.5.4(x32), 2.4.4(x32) and Jython 2.5.1 on Win7
Bug reports (via Google code), comments, etc are very much appreciated!
Hello Python Community.
I'm pleased to announce pyxser-1.4.4r, a python extension which
contains functions to serialize and deserialize Python Objects
into XML. It is a model based serializer. Here is the ChangeLog
entry for this release:
Daniel Molina Wegener <dmw(a)coder.cl>
* src/include/pyxser_collections.h - added set handling
function prototypes. Added support for unicode
key names, which are converted to the user settings
encoding (ie utf-8) inside the XML output.
* src/pyxser_serializer.c - removed memory leak. Addded
support for unicode object names in dictionary/list types.
* src/pyxser_collections.c - added set handling function
prototypes. added name property handling algorithm, so
non string name properties are not serialized. I shall
extend it to other modules.
* src/pyxser_tools.c - added set handling prototypes and
set type checking function.
* test-utf8-leak.py - added serialization of SQL Alchemy
objects, so we can test more complex Python objects
* test-utf8-sqlalchemy.py - added sql alchemy object
* src/pyxser_serializer.c - reduced serialization algorithms,
replacing deep nested if statements by flatten ones.
* src/pyxser_collections.c - reduced serialization algorithms
replacing deep nested if statements by flatten ones.
* src/pyxser_typem.c - reduced serialization algorithms,
replacing deep nested if statements by flatten ones.
Thanks to pyxser users for their feedback.
This release contains some bug fixes, mainly related to type
checking and type handling. I hope this small extension will
help you on your programming tasks.
The project is hosted at:
The web page for the project is located at:
PyPi entry is:
For a sample article on how to integrate
pyxser with ZSI WebServices:
Thanks and best regards,
Daniel Molina Wegener <dmw [at] coder [dot] cl>
Software Architect, System Programmer & Web Developer
Phone: +56 (2) 979-0277 | Blog: http://coder.cl/
IMDbPY 4.6 is available (tgz, rpm, exe) from:
IMDbPY is a Python package useful to retrieve and manage the data of
the IMDb movie database about movies, people, characters and companies.
In this release, a lot of minor fixes and some overall improvements..
Platform-independent and written in pure Python (and few C lines),
IMDbPY can retrieve data from both the IMDb's web server and a local
copy of the whole database.
IMDbPY package can be very easily used by programmers and developers
to provide access to the IMDb's data to their programs.
Some simple example scripts are included in the package; other
IMDbPY-based programs are available from the home page.
Davide Alberani <alberanid(a)libero.it> [GPG KeyID: 0x465BFD47]
stdeb produces Debian source packages from Python packages via a new
distutils command, sdist_dsc. Automatic defaults are provided for the
Debian package, but many aspects of the resulting package can be
customized. An additional command, bdist_deb, creates a Debian binary
package, a .deb file. The new debianize command builds a debian/
directory directly alongside your setup.py.
Two convenience utilities are also provided. pypi-install will query the
Python Package Index (PyPI) for a package, download it, create a .deb
from it, and then install the .deb. py2dsc will convert a
distutils-built source tarball into a Debian source package.
This email announces release 0.6.0.
Highlights for this release (you may also wish to consult the full
- A new ``debianize`` command to build a ``debian/`` directory
alongside your setup.py file.
As always, please check the release notes:
The full changelog is here:
Announcing PyTables 2.2rc2
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.
This is the second (and probably last) release candidate for PyTables
2.2, so please test it as much as you can before I declare the beast
stable. The main new features in 2.2 series are:
* A new compressor called Blosc, designed to read/write data to/from
memory at speeds that can be faster than a system `memcpy()` call.
With it, many internal PyTables operations that are currently
bounded by CPU or I/O bandwith are speed-up. Some benchmarks:
* A new `tables.Expr` module (based on Numexpr) that allows to do
persistent, on-disk computations on many algebraic operations.
For a brief look on its performance, see:
* Support for HDF5 hard links, soft links and automatic external links
(kind of mounting external filesystems). A new tutorial about its
usage has been added to the 'Tutorials' chapter of User's Manual.
* Suport for 'fancy' indexing (i.e., à la NumPy) in all the data
containers in PyTables. Backported from the implementation in the
h5py project. Thanks to Andrew Collette for his fine work on this!
As always, a large amount of bugs have been addressed and squashed too.
In case you want to know more in detail what has changed in this
version, have a look at:
You can download a source package with generated PDF and HTML docs, as
well as binaries for Windows, from:
For an on-line version of the manual, visit:
About the HDF5 library:
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 (and numarray!)
makers. Without them, PyTables simply would not exist.
Share your experience
Let us know of any bugs, suggestions, gripes, kudos, etc. you may
-- The PyTables Team