Dear Python users,
The Moovida team is happy to announce the release of Moovida Media
Center 1.0.2, code-named "Acid Rain".
Moovida, formerly known as Elisa, is a cross-platform and open-source
Media Center written in Python.
It uses GStreamer [1] for media playback and pigment [2] to create an
appealing and intuitive user interface.
This release is a lightweight release, meaning it is pushed through our
automatic plugin update system. Additionally a windows installer is
available for download on our website.
As usual, for users already running Moovida, the upgrade to 1.0.2 should
be done automatically via the plugin repository.
A complete list of the issues fixed can be found at:
http://launchpad.net/elisa/+milestone/1.0.2
This is also summarised in the (attached) release notes.
Installers and sources can be downloaded from
http://www.moovida.com/download/
Bug reports and feature requests are welcome at
http://bugs.launchpad.net/elisa/+filebug
Have a media-centered week-end,
Olivier, for the Moovida team
[1] http://www.gstreamer.net/
[2] https://code.fluendo.com/pigment/trac
Moovida 1.0.2 "Acid Rain"
=========================
This is Elisa 1.0.2, second release of the 1.0 branch.
Bugs fixed since 1.0.0:
- 308892: [linux] pulseaudio: files containing an audio stream do not play
- 379439: [win32] Moovida cannot play or index files with non-ascii path on Windows XP
- 381307: [win32] Moovida does not start after updates on XP with a non-ascii user name
- 381404: Most of Moovida is unusable after auto update of database plugin (race condition)
- 267959: Default to local cover art for albums
- 375275: Blank screen with no feedback when no last/most watched TV shows in playlist
- 376160: Impossible to type 'K', 'E' or 'Y' in text entry widget
- 379438: [win32] can not access "This Computer" or "Attached Devices"
- 380206: [win32] Cannot do recategorization of videos
- 380520: [linux] DAAP shares not appearing in UI
- 381593: Music album infos: Cover not displayed anymore
- 381702: Cannot access resources in plugins which name contains a dash
- 267772: Traceback when querying the Amazon cover retriever
- 380478: When USB plugged in, OSD player disappears
- 380878: Modal popup is always an error one
- 381019: Playing a TV episode should enqueue the whole season
- 381020: Playing a track should enqueue the whole album
- 381366: The --shell option does nothing
- 354571: fix a bug in poblesec/widgets/player/button.py
- 356178: [win32] Wrong encoding of some characters in the license text control of the installer
- 381177: [linux] Incorrect info on linux packages installation page
Download
You can find source releases of Moovida on the download page:
http://www.moovida.com/download
Moovida Homepage
More details can be found on the project's website: http://www.moovida.com
Support and Bugs
We use Launchpad for bug reports and feature requests:
https://bugs.launchpad.net/elisa/+filebug
Developers
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:
- Anna Wojdel
- David McLeod
- Fernando Casanova Coch
- Florian Boucault
- Guillaume Emont
- Jesús Corrius
- Jutta Mailander
- Lionel Martin
- Loïc Molinari
- Maxwell Young
- Michał Sawicz
- Olivier Tilloy
- Philippe Normand
- Xose Pérez
I've just revved jsonlib2, the C-based json parser used at metaweb for
freebase.com. Compared with simplejson, my initial tests have it
between 21 and 25 times faster for loads() and around 10x faster for
dumps()
http://code.google.com/p/jsonlib2/
For those of you who have never used jsonlib/jsonlib2, all you have to
know is that with this version, jsonlib2 is much more compatible with
simplejson/json. Got a ways to go but for most applications it should
be a drop-in replacement.
This is the first C Python extension I've ever written, and I actually
inherited most of the code when I forked jsonlib because of
differences with the author. This means I'm very interested in patches/
critiques/etc.
For those using jsonlib or jsonlib2:
Version 1.5 is a big API change - loads() and dumps() are now almost
completely compatible with simplejson's loads() and dumps() - so it
really should be a drop-in replacement. Here are a few things that
have been possible with simplejson, but not with jsonlib2:
1) looser enforcement of json spec - allowing stuff like:
>>> jsonlib2.dumps({None: "foo"})
'{"null": "foo"}'
>>> jsonlib2.dumps(None)
'null'
2) full support for Infinity, NaN, in both dumping AND parsing, by
default:
>>> jsonlib2.dumps(1e10000)
'Infinity'
>>> jsonlib2.loads(jsonlib2.dumps(1e10000))
inf
I've actually imported the simplejson unit tests, and this library
passes 26 of 32 tests, and most failures are just due to the fact that
jsonlib2 prefers to output in utf8 rather than unicode, for faster
output from a web server.
Alec
Hello to everyone.
I'm an Italian engineer and I'm approaching to Python, particularly to
Python extension through C++ (because I'm an experienced C++ programmer).
I've seen that Python files are basically managed through the C FILE pointer.
I've recently released on Google Code a very small library which allows to
treat the C FILE* as a C++ stream and I think this should be useful to
Python developers.
The link is this: http://code.google.com/p/mds-utils/
The library uses Boost.Iostreams.
Think to this situation: you have some C++ classes or functions that
take a C++ stream or
fstream as parameter. You want to make a Python extension from this
library but you want
to pass a Python file object to your C++ code. Using my library, you
can wrap the underlying
FILE* into an object that behaves like a C++ stream.
I've not yet built an on-line documentation, but the library comes
with detailed doxygen documentation and useful examples.
I hope my library will be useful to the Python community and I'd like
to see a link to it on the
Python web site.
Best regards to all of you.
Michele
--
Michele De Stefano
http://www.linkedin.com/in/micdestefanohttp://xoomer.virgilio.it/michele_de_stefano
============================================
Announcing HDF5 for Python (h5py) 1.2 *BETA*
============================================
I'm pleased to announce the availability of HDF5 for Python 1.2 beta! This
release represents a significant update to the h5py feature set. Bug
reports, questions and complaints are welcome and needed!
Downloads, bug tracker: http://h5py.googlecode.com
Documentation: h5py.alfven.org
Contact email: h5py at alfven dot org
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.
In addition to providing interoperability with existing HDF5 datasets
and platforms, h5py is a convienient way to store and retrieve
arbitrary NumPy data and metadata.
What's new in 1.2
-----------------
- Variable-length strings are now supported! They are mapped to native
Python strings via the NumPy "object" type. VL strings may be read,
written and created from h5py, and are allowed in all HDF5 contexts,
even as members of compound or array types.
- Enumerated types are now fully supported; they can be used in NumPy
anywhere integer types are allowed, and are stored as native HDF5
enums. Conversion between integers and enums is supported.
- The NumPy "array" dtype is now allowed as a top-level type when
creating a dataset, not just as a member of a compound type.
- Many different low-level HDF5 drivers can now be used when creating
a file, which allows purely in-memory ("core") files, multi-volume
("family") files, and files which use low-level buffered I/O.
- HDF5 exceptions now inherit from common Python built-ins like TypeError
and ValueError (in addition to the current HDF5 error hierarchy), freeing
the user from knowledge of the HDF5 error system.
- Unicode file names are now supported
- Groups and attributes now support the standard Python dictionary
interface methods, including keys(), values() and friends.
Design revisions since 1.1
--------------------------
- The role of the "name" attribute on File objects has changed. "name"
now returns the HDF5 path of the File object ('/'); the file name on
disk is available at File.filename.
- Dictionary-interface methods for Group and AttributeManager objects have
been renamed to follow the standard Python convention (keys(), values(),
etc). The old method names are still available but deprecated. They
will not be removed until h5py 1.4 or equivalent.
- The HDF5 shuffle filter is no longer automatically activated when
GZIP or LZF compression is used; many datasets "in the wild" do not
benefit from shuffling.
Standard features
-----------------
- Supports storage of NumPy data of the following types:
* Integer/Unsigned Integer
* Float/Double
* Complex/Double Complex
* Compound ("recarray")
* Strings
* Boolean
* Array
* Enumeration (integers)
* Void
- Random access to datasets using the standard NumPy slicing syntax,
including a subset of fancy indexing and point-based selection
- Transparent compression of datasets using GZIP, LZF or SZIP,
and error-detection using Fletcher32
- "Pythonic" interface supporting dictionary and NumPy-array metaphors
for the high-level HDF5 abstrations like groups and datasets
- A comprehensive, object-oriented wrapping of the HDF5 low-level C API
via Cython, in addition to the NumPy-like high-level interface.
- Supports many new features of HDF5 1.8, including recursive iteration
over entire files and in-library copy operations on the file tree
- Thread-safe
Where to get it
---------------
* Main website, documentation: http://h5py.alfven.org
* Downloads, bug tracker: http://h5py.googlecode.com
Requires
--------
* Linux, Mac OS-X or Windows
* Python 2.5 (Windows), Python 2.5 or 2.6 (Linux/Mac OS-X)
* NumPy 1.0.3 or later
* HDF5 1.6.5 or later (including 1.8); HDF5 is included with
the Windows version.
Thanks
------
Thanks to D. Dale, E. Lawrence and other for their continued support
and comments. Also thanks to the Francesc Alted and the PyTables project,
for inspiration and generously providing their code to the community. Thanks
to everyone at the HDF Group for creating such a useful piece of software.
Hi all-
Per requests, I've moved the concurrency-sig list to concurrency-sig(a)python.org
from it's present home at Google Groups. I'll be shutting down the
google list in the next few days. Sorry for any inconvenience this
may have caused.
--Pete
Python svn build (http://pyvm.sourceforge.net) is a project to create binary
distributions for the python interpreter: the source used to build them is the
latest svn revision.
The builds are made using the OpenSUSE buildserver https://build.opensuse.org
and the test results can be seen on the website http://pyvm.sourceforge.net.
The final packages in rpm format are available for CentOS/Fedora/Mandriva and
OpenSUSE.
Regards,
Antonio Cavallo
Veusz 1.4
---------
Velvet Ember Under Sky Zenith
-----------------------------
http://home.gna.org/veusz/
Veusz is Copyright (C) 2003-2009 Jeremy Sanders <jeremy(a)jeremysanders.net>
Licenced under the GPL (version 2 or greater).
Veusz is a Qt4 based scientific plotting package. It is written in
Python, using PyQt4 for display and user-interfaces, and numpy for
handling the numeric data. Veusz is designed to produce
publication-ready Postscript/PDF output. The user interface aims to be
simple, consistent and powerful.
Veusz provides a GUI, command line, embedding and scripting interface
(based on Python) to its plotting facilities. It also allows for
manipulation and editing of datasets.
Changes in 1.4:
* Dates can be plotted on axes
* Bar graph component, support bars in groups and stacked bars
with error bars
* Improved import
- text lines can be ignored in imported files
- prefix and suffix can be added to dataset names
- more robust import dialog
* Markers can be "thinned" for large datasets
* Further LaTeX support, including \frac for fractions and \\
for line breaks.
* Keys show error bars on datasets with errors
* Axes can scale plotted data by a factor
More minor changes
* Mathematical expressions can be entered in many places where
numbers are entered (e.g. axis minima)
* Many more latex symbols
* Text labels can also be placed outside graphs directly on pages
* Dataset expressions can be edited
* Data can be copied out of data edit dialog. Rows can be inserted or
deleted.
* Mac format line terminators are allowed in import files
* Preview window resizes properly in import dialog
Features of package:
* X-Y plots (with errorbars)
* Line and function plots
* Contour plots
* Images (with colour mappings and colorbars)
* Stepped plots (for histograms)
* Bar graphs
* Plotting dates
* Fitting functions to data
* Stacked plots and arrays of plots
* Plot keys
* Plot labels
* Shapes and arrows on plots
* LaTeX-like formatting for text
* EPS/PDF/PNG/SVG export
* Scripting interface
* Dataset creation/manipulation
* Embed Veusz within other programs
* Text, CSV and FITS importing
Requirements:
Python (2.4 or greater required)
http://www.python.org/
Qt >= 4.3 (free edition)
http://www.trolltech.com/products/qt/
PyQt >= 4.3 (SIP is required to be installed first)
http://www.riverbankcomputing.co.uk/pyqt/http://www.riverbankcomputing.co.uk/sip/
numpy >= 1.0
http://numpy.scipy.org/
Optional:
Microsoft Core Fonts (recommended for nice output)
http://corefonts.sourceforge.net/
PyFITS >= 1.1 (optional for FITS import)
http://www.stsci.edu/resources/software_hardware/pyfits
For documentation on using Veusz, see the "Documents" directory. The
manual is in pdf, html and text format (generated from docbook).
Issues with the current version:
* Due to Qt, hatched regions sometimes look rather poor when exported
to PostScript or PDF.
* Due to a bug in Qt, some long lines, or using log scales, can lead
to very slow plot times under X11. This problem is seen with
dashed/dotted lines. It is fixed by upgrading to Qt-4.5.1 (the
Veusz binary version includes this Qt version).
* Can be very slow to plot large datasets if antialiasing is enabled.
Right click on graph and disable antialias to speed up output. This
is mostly a problem with older Qt versions, however.
If you enjoy using Veusz, I would love to hear from you. Please join
the mailing lists at
https://gna.org/mail/?group=veusz
to discuss new features or if you'd like to contribute code. The
latest code can always be found in the SVN repository.
Jeremy Sanders
We are proud to announce the release of Resolver One, version 1.5.
Resolver One is a Windows-based spreadsheet that integrates Python
deeply into its recalculation loop, making the models you build more
reliable and more maintainable.
For version 1.5, we've added a console; this new command-line window
gives you a way to interact with your spreadsheet using Python
statements. Here's a screencast showing why this is worth doing:
<http://www.resolversystems.com/screencasts/console/>
We have a 31-day free trial version, so if you would like to take a
look, you can download it from our website:
<http://www.resolversystems.com/download/>
If you want to use Resolver One in an Open Source project, we offer
free licenses for that:
<http://www.resolversystems.com/opensource/>
Best regards,
Giles
--
Giles Thomas
giles.thomas(a)resolversystems.com
+44 (0) 20 7253 6372
Win up to $17,000 for a spreadsheet: <http://www.resolversystems.com/
competition/>
17a Clerkenwell Road, London EC1M 5RD, UK
VAT No.: GB 893 5643 79
Registered in England and Wales as company number 5467329.
Registered address: 843 Finchley Road, London NW11 8NA, UK
At long last, we are finally releasing Dabo 0.9.2. This fixes the
errors that were found in 0.9.1; adds a brand-new Web Update
implementation that should make keeping current much easier, as well
as a whole bunch of improvements under the hood.
You can grab the latest version at http://dabodev.com/download.
-- Ed Leafe