The Call For Papers for Sun's 2009 CommunityOne conference is now
open. For 2009, there will be an East Coast and West Coast event:
CommunityOne East - March 18-19, 2009 - New York City
CommunityOne West - June 1-2, 2009 - San Francisco
Deadline to submit speaking abstracts: Dec. 11, 2008
For more information on these events: <http://developers.sun.com/events/communityone/
If you are interested in submitting a talk: <http://www.eventreg.com/sun/communityone09/cfp
eGenix.com mxODBC Connect
Python Database Interface
Our new client-server product for connecting Python applications
to relational databases - from all major platforms
This announcement is also available on our web-site for online reading:
The mxODBC Connect Database Interface for Python allows users to
easily connect Python applications to all major databases on the
market today in a highly portable and convenient way.
Unlike our mxODBC Python extension, mxODBC Connect is designed
as client-server application, so you no longer need to find production
quality ODBC drivers for all the platforms you target with your Python
Instead you use an easy to install Python client library which
connects directly to the mxODBC Connect database server over the
This makes mxODBC Connect the ideal basis for writing cross-platform
database programs and utilities in Python, especially if you run
applications that need to communicate with databases such as MS SQL
Server and MS Access, Oracle Database, IBM DB2 and Informix, Sybase
ASE and Sybase Anywhere, MySQL, PostgreSQL, SAP MaxDB and many more,
that run on Windows or Linux machines.
By removing the need to install and configure ODBC drivers on the
client side, mxODBC Connect greatly simplifies setup and
configuration of database driven client applications, while at
the same time making the network communication between client and
database server more efficient and more secure.
For more information, please see the product page:
mxODBC Connect 1.0.0 is the first general availability release of our
new mxODBC Connect product.
With this release we have further improved the performance and
round-trip times of the mxODBC Connect network layer even more.
We are now able to achieve a *more than 10 times better performance*
for a typical multi-tier application that runs on Linux and connects
to a MS SQL Server database running on a Windows host, compared to the
same application using mxODBC and the FreeTDS ODBC driver.
Thanks to everyone who participated in the public beta !
The download archives as well as instructions for installation and
configuration of the product can be found on the product page:
Evaluation licenses for the server part are available free of
The client part of mxODBC Connect is always free of charge.
Commercial support for this product is available from eGenix.com.
for details about our support offerings.
Professional Python Services directly from the Source (#1, Dec 02 2008)
>>> Python/Zope Consulting and Support ... http://www.egenix.com/
>>> mxODBC.Zope.Database.Adapter ... http://zope.egenix.com/
>>> mxODBC, mxDateTime, mxTextTools ... http://python.egenix.com/
2008-12-02: Released mxODBC.Connect 1.0.0 http://python.egenix.com/
:::: Try mxODBC.Zope.DA for Windows,Linux,Solaris,MacOSX 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
We are proud to announce the release of LDTP 1.4.0. This release features
number of important breakthroughs in LDTP as well as in the field of Test
Automation. This release note covers a brief introduction on LDTP followed
by the list of new features and major bug fixes which makes this new version
of LDTP the best of the breed. Useful references have been included at the
end of this article for those who wish to hack / use LDTP.
Linux Desktop Testing Project is aimed at producing high quality test
automation framework (C / Python) and cutting-edge tools that can be used to
test Linux Desktop and improve it. It uses the Accessibility libraries to
poke through the application's user interface. The framework also has tools
to record test-cases based on user events in the interface of the
application which is under testing. We strive to help in building a quality
Whats new in this release:
Added new APIs for VMware Workstation automation
Initial work for LDTPv2 - LDTP engine in python
Added code block specific to Access Company related environment
Improved LDTP performance, by reducing the number of window information
Access company has contributed significant code to perform on multiple
window without title
* Guofu Xu <Guofu.Xu(a)access-company.com> fixed couple of crash, handled new
scenarios where the window title is empty and many other performance
Fixed bug # 343890, 550978
Fixed thread lock, which avoid the crash
Download source tarball -
More news to come later ;-)
For detailed information on LDTP framework and latest updates visit
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
To subscribe to LDTP mailing lists, visit
IRC Channel - #ldtp on irc.freenode.net
Linux Desktop (GUI Application) Testing Project -
Announcing the first public release of Aviate, a cross-platform web
deployment tool written in Python.
Aviate is designed to make deploying your web applications very easy,
while providing you with a rich feature set to make repeated task
performed in a snap, and being extensible so you can extend its
features with your own Python code.
Among its feature is being based on XML, an intuitive GUI to create
deployment files, a large number of built-in commands, multiple
protocol support, extensibility, language constructs, and more.
More details on Aviate:
Call For Papers
The first Open Source in Data Mining workshop (OSDM'09)
Monday 27th April 2009
Workshop Website: http://osdm09.togaware.com
To be held at the 13th
Pacific-Asia Conference on Knowledge Discovery
and Data Mining (PAKDD'09)
Submissions due: Monday 22 December 2008
Open source software is becoming increasingly accepted in public and
private sector organisations in many countries. There is a variety
of open source data mining tools available to both researchers and
practitioners, some being simple research prototypes while others are
fully developed software tools in daily use in industry.
This workshop aims to bring together data mining software developers,
practitioners, researchers and educators, with the objectives to
present open source data mining tools, discuss experiences and lessons
learned developing and using such tools, and exchange ideas on how to
promote the use of open source tools in the field of data mining.
Submission of papers: 22 December 2008
Notification of Authors: 23 January 2009
Camera-ready version: 9 February 2009
OSDM'09 workshop: 27 April 2009
PAKDD'09 conference: 28-30 April 2009
The OSDM'09 workshop is aimed at data mining researchers, educators
and practitioners, and it will include a mix of both peer-reviewed
scientific papers as well as software demonstrations. We plan to have:
* An invited keynote presentation by one of the developers of the
Weka data mining tool.
* A session with peer-reviewed papers on topics such as:
- Open source in data mining research.
- Open source in data mining education.
- Open source for data mining in government.
- Open source for data mining in industry and business.
- Data mining using open source - Experiences.
- Impact of open source in data mining.
- Open source methodologies in data mining.
* A more practically oriented session that will include:
- Demonstrations of open source data mining tools.
- Tutorials and how-to's, for example how to set-up and manage
open source data mining tools; how-to choose an open source
license suitable for data mining, selecting a software
repository suitable for open source data mining tools, etc.
* A panel session with prominent data mining open source
developers. Possible topics:
- Why open source for data mining research and education?
- Why publish your data mining tool as open source software?
Important notice: Submitting a paper to the OSDM'09 workshop means
that if the paper is accepted, at least one author must attend the
workshop to present the paper. For no-show authors, their affiliations
will receive a notification.
All submitted papers must be formatted according to Springer's
manuscript submission guidelines as available at
For the initial submission, paper must NOT include author's names,
affiliations and email addresses (left as a blank) --- the review
process will be double-blind. Do not include any acknowledgements
referring to funding bodies. Self-citing references should be removed
from the submitted papers (they can be added after review).
We encourage submissions of two types of papers:
1) Regular papers, up-to 12 pages long in single-spaced pages
with font size at least 11 points (i.e. following the Springer
LNCS style). These papers will be fully reviewed by at least three
members of the OSDM'09 program committee.
2) Short papers, aimed for the demonstration, tutorial and how-to
session. These papers can be up-to 6 pages long, also in Springer
LNCS style). These papers will be reviewed by at least one member
of the OSDM'09 program committee as well as the OSDM'09
Papers submitted to OSDM'09 must not be published or under
consideration to be published elsewhere.
The electronic submissions must be in PDF and made through the
OSDM'09 Submission Page, accessible from:
- Dr Graham Williams Togaware / The Australian Taxation Office
- Dr Peter Christen The Australian National University
- Dr Rohan Baxter The Australian Taxation Office,
- Prof Michael Berthold University of Konstanz, Germany
- Dr Christian Borgelt European Center for Soft Computing,
- Dr Tim Churches NSW Department of Health, Australia
- Assist Prof Janez Demsar University of Ljubljana, Slovenia
- Assoc Prof Eibe Frank University of Waikato, New Zealand
- Dr Mark Hall Pentaho, New Zealand
- Prof Joshua Huang The University of Hong Kong,
- Assoc Prof Bernhard Pfahringer University of Waikato, New Zealand
- Assoc Prof Blaz Zupan University of Ljubljana, Slovenia
- Dr Yunming Ye Harbin Institute of Technology,
Dr Peter Christen
Senior Lecturer / Graduate Convenor (Computer Science) /
Graduate Advisor DCS
Department of Computer Science
ANU College of Engineering and Computer Science
CSIT Building (108), North Road
The Australian National University
Canberra ACT 0200 Australia
T: +61 2 6125 5690
F: +61 2 6125 0010
AIAPA (Associate of the Institute of Analytics
Professionals of Australia Limited)
CRICOS Provider #00120C
Announcing HDF5 for Python (h5py) 1.0
What is h5py?
HDF5 for Python (h5py) is a general-purpose Python interface to the
Hierarchical Data Format library, version 5. HDF5 is a versatile,
mature scientific software library designed for the fast, flexible
storage of enormous amounts of data.
>From a Python programmer's perspective, HDF5 provides a robust way to
store data, organized by name in a tree-like fashion. You can create
datasets (arrays on disk) hundreds of gigabytes in size, and perform
random-access I/O on desired sections. Datasets are organized in a
filesystem-like hierarchy using containers called "groups", and
accesed using the tradional POSIX /path/to/resource syntax.
This is the fourth major release of h5py, and represents the end
of the "unstable" (0.X.X) design phase.
Why should I use it?
H5py provides a simple, robust read/write interface to HDF5 data
from Python. Existing Python and NumPy concepts are used for the
interface; for example, datasets on disk are represented by a proxy
class that supports slicing, and has dtype and shape attributes.
HDF5 groups are are presented using a dictionary metaphor, indexed
A major design goal of h5py is interoperability; you can read your
existing data in HDF5 format, and create new files that any HDF5-
aware program can understand. No Python-specific extensions are
used; you're free to implement whatever file structure your application
Almost all HDF5 features are available from Python, including things
like compound datatypes (as used with NumPy recarray types), HDF5
attributes, hyperslab and point-based I/O, and more recent features
in HDF 1.8 like resizable datasets and recursive iteration over entire
The foundation of h5py is a near-complete wrapping of the HDF5 C API.
HDF5 identifiers are first-class objects which participate in Python
reference counting, and expose the C API via methods. This low-level
interface is also made available to Python programmers, and is
See the Quick-Start Guide for a longer introduction with code examples:
Where to get it
* Main website, documentation: http://h5py.alfven.org
* Downloads, bug tracker: http://h5py.googlecode.com
* The HDF group website also contains a good introduction:
* UNIX-like platform (Linux or Mac OS-X); Windows version is in
* Python 2.5 or 2.6
* NumPy 1.0.3 or later (1.1.0 or later recommended)
* HDF5 1.6.5 or later, including 1.8. Some features only available
when compiled against HDF5 1.8.
* Optionally, Cython (see cython.org) if you want to use custom install
options. You'll need version 0.9.8.1.1 or later.
About this version
Version 1.0 follows version 0.3.1 as the latest public release. The
major design phase (which began in May of 2008) is now over; the design
of the high-level API will be supported as-is for the rest of the 1.X
series, with minor enhancements.
This is the first version to support Python 2.6, and the first to use
Cython for the low-level interface. The license remains 3-clause BSD.
** This project is NOT affiliated with The HDF Group. **
Thanks to D. Dale, E. Lawrence and other for their continued support
and comments. Also thanks to the PyTables project, for inspiration
and generously providing their code to the community, and to everyone
at the HDF Group for creating such a useful piece of software.
Dear Python users,
The Elisa team is happy to announce the release of Elisa Media Center
0.5.20, code-named "Paranoid Android".
Elisa is a cross-platform and open-source Media Center written in Python.
It uses GStreamer  for media playback and pigment  to create an
appealing and intuitive user interface.
New features include a mechanism to trust external plugins' integrity
when distributed through the plugin repository, and a better integration
As usual, a bunch of bugs were fixed, a complete list can be found at:
Installers and sources can be downloaded from
Bug reports and feature requests are welcome at
Have a media-centered evening,
The Elisa team
Elisa 0.5.20 "Paranoid Android"
This is Elisa 0.5.20, twentieth release of the 0.5 branch.
New features since 0.5.19:
- A mechanism to trust external plugins' integrity when distributed through the
- Elisa by default in the "Open With" contextual menu of windows for supported
Bugs fixed since 0.5.19:
- 296796: "add to favourites" action mouse support broken
- 301769: Elisa doesn't load resources that are inside of eggs
- 302877: FirstRunMessage sent too early in Application startup sequence
- 290221: The 'Add' label looks borked sometimes
- 302334: [linux] 'Add folders' doesn't work if HAL resource provider is not loaded
- 302780: DVD is broken even with the correct gstreamer stuff installed
- 303441: [win32] Non playable media leads to black screen
- 296308: update_checker reports wrong distribution name in some cases
You can find source releases of Elisa on the download page:
More details can be found on the project's website: http://elisa.fluendo.com
Support and Bugs
We use Launchpad for bug reports and feature requests:
All code is in a Bazaar branch and can be checked out from there.
It is hosted on Launchpad: https://code.launchpad.net/elisa
Contributors to this release:
- Benjamin Kampmann
- David McLeod
- Florian Boucault
- Guido Amoruso
- Guillaume Emont
- Jesús Corrius
- Lionel Martin
- Olivier Tilloy
- Philippe Normand