Mailman 3 June 2009 - Python-announce-list

mailog - a minimalstic blog engine
by simon oberhammer 24 Jun '09

24 Jun '09

serving static html (enhanced with ajax) created by a python daemon fetching markdowned emails via imap. * post and comment per email o youremail+post(a)example.com o youremail+comment(a)example.com * no database, no dependencies (only python, which you should already have) * use markdown to format your posts * attach images you want to embed in your post * your emails go through the mail server, therefore: o you get free spam protection o automatic backups (in imap mailbox) MIT license. stable. more infos http://code.google.com/p/mailog/

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timelib 0.2 - parse english textual date descriptions
by Ralf Schmitt 24 Jun '09

24 Jun '09

Hi all, timelib is a short wrapper around php's internal timelib module. It currently only provides two functions for parsing textual date descriptions: timelib.strtodatetime: >>> timelib.strtodatetime('today') datetime.datetime(2009, 6, 23, 0, 0) >>> timelib.strtodatetime('today') datetime.datetime(2009, 6, 23, 0, 0) >>> timelib.strtodatetime('next friday') datetime.datetime(2009, 6, 26, 0, 0) >>> timelib.strtodatetime('29 feb 2008 -108 years') datetime.datetime(1900, 3, 1, 0, 0) timelib.strtotime: >>> import time, timelib >>> time.ctime(timelib.strtotime("now")) 'Tue Jun 23 15:17:32 2009' >>> time.ctime(timelib.strtotime("4 hours ago")) 'Tue Jun 23 11:17:38 2009' >>> time.ctime(timelib.strtotime("20080229 -1 year")) 'Thu Mar 1 01:00:00 2007' timelib is available via PyPI: http://pypi.python.org/pypi/timelib/ Regards, - Ralf

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CodeInvestigator version 0.13.0 was released on June 24
by hans moleman 24 Jun '09

24 Jun '09

CodeInvestigator version 0.13.0 was released on June 24. Bug fix: Changes to imported files were not taken into account. This version only works with Python 2.6. Some modules disappear in Python 3.0 and this version has these modules replaced. CodeInvestigator is a tracing tool for Python programs. Running a program through CodeInvestigator creates a recording. Program flow, function calls, variable values and conditions are all stored for every line the program executes. The recording is then viewed with an interface consisting of the code. The code can be clicked: A clicked variable displays its value, a clicked loop displays its iterations. You read code, and have at your disposal all the run time details of that code. A computerized desk check tool and another way to learn about your program. http://sourceforge.net/project/showfiles.php?group_id=183942

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Guppy-PE/Heapy 0.1.9 released
by Sverker Nilsson 23 Jun '09

23 Jun '09

I am happy to announce Guppy-PE 0.1.9 Guppy-PE is a library and programming environment for Python, currently providing in particular the Heapy subsystem, which supports object and heap memory sizing, profiling and debugging. It also includes a prototypical specification language, the Guppy Specification Language (GSL), which can be used to formally specify aspects of Python programs and generate tests and documentation from a common source. The main news in this release: o A patch by Chad Austin to compile with Visual Studio 2003 and Python 2.5 C compilers. I think this may fix similar problems with other Microsoft compilers. o Interactive help system, providing a .doc attribute that can be used to get info on available attributes in text form and also by invoking a browser. o New documentation file, heapy_tutorial.html. It contains for now an example of how to get started and use the interactive help. o Bug fix wrt pop for mutable bitset. (Not used in heapy, only in sets/test.py) o guppy.hpy().test() now includes the set-specific tests. o Remote monitor does not longer require readline library being installed. License: MIT Guppy-PE 0.1.9 is available in source tarball format on the Python Package Index (a.k.a. Cheeseshop): http://pypi.python.org/pypi/guppy/0.1.9 The project homepage is on Sourceforge: http://guppy-pe.sourceforge.net Enjoy, Sverker Nilsson Expertise in Linux, embedded systems, image processing, C, Python... http://sncs.se

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ANN: Numexpr 1.3.1 released
by Francesc Alted 23 Jun '09

23 Jun '09

========================== Announcing Numexpr 1.3.1 ========================== Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like "3*a+4*b") are accelerated and use less memory than doing the same calculation in Python. This is a maintenance release. On it, support for the `unit32` type has been added (it is internally upcasted to `int64`), as well as a new `abs()` function (thanks to Pauli Virtanen for the patch). Also, a little tweaking in the treatment of unaligned arrays on Intel architectures allowed for up to 2x speedups in computations involving unaligned arrays. For example, for multiplying 2 arrays (see the included ``unaligned-simple.py`` benchmark), figures before the tweaking were: NumPy aligned: 0.63 s NumPy unaligned: 1.66 s Numexpr aligned: 0.65 s Numexpr unaligned: 1.09 s while now they are: NumPy aligned: 0.63 s NumPy unaligned: 1.65 s Numexpr aligned: 0.65 s Numexpr unaligned: 0.57 s <-- almost 2x faster than above You can also see how the unaligned case can be even faster than the aligned one. The explanation is that the 'aligned' array was actually a strided one (actually a column of an structured array), and the total working data size was a bit larger for this case. In case you want to know more in detail what has changed in this version, see: http://code.google.com/p/numexpr/wiki/ReleaseNotes or have a look at RELEASE_NOTES.txt in the tarball. Where I can find Numexpr? ========================= The project is hosted at Google code in: http://code.google.com/p/numexpr/ And you can get the packages from PyPI as well: http://pypi.python.org/pypi How it works? ============= See: http://code.google.com/p/numexpr/wiki/Overview for a detailed description by the original author (David M. Cooke). Share your experience ===================== Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. Enjoy! -- Francesc Alted

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ANN: HDF5 for Python 1.2
by Andrew Collette 22 Jun '09

22 Jun '09

Announcing HDF5 for Python (h5py) 1.2 ===================================== I'm pleased to announce the availability of HDF5 for Python 1.2 final! This release represents a significant update to the h5py feature set. Some of the new new features are: - Support for variable-length strings! - Use of built-in Python exceptions (KeyError, etc), alongside H5Error - Top-level support for HDF5 CORE, SEC2, STDIO, WINDOWS and FAMILY drivers - Support for ENUM and ARRAY types - Support for Unicode file names - Big speedup (~3x) when using single-index slicing on a chunked dataset Main site: http://h5py.alfven.org Google code: http://h5py.googlecode.com 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. Full list of new features 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. - HDF5 exceptions now inherit from common Python built-ins like TypeError and ValueError (in addition to current HDF5 error hierarchy), freeing the user from knowledge of the HDF5 error system. Existing code which uses H5Error will continue to work. - 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. - Groups and attributes now support the standard Python dictionary interface methods, including keys(), values() and friends. The existing methods (listnames(), listobjects(), etc.) remain and will not be removed until at least h5py 1.4 or equivalent. - Workaround for an HDF5 bug has sped up reading/writing of chunked datasets. When using a slice with fewer dimensions than the dataset, there can be as much as a 3x improvement in write times over h5py 1.1. - 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. - Unicode file names are now supported - It's now possible to explicitly set the type of an attribute, and to preserve the type of an attribute while modifying it. - High-level objects now have .parent and .file attributes, to make the navigation of HDF5 files more convenient. 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. - 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.

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ANN: Leo 4.6 beta 2 released
by Edward K Ream 22 Jun '09

22 Jun '09

Leo 4.6 b2 is now available at: http://sourceforge.net/project/showfiles.php?group_id=3458&package_id=29106 Leo is a text editor, data organizer, project manager and much more. See: http://webpages.charter.net/edreamleo/intro.html The highlights of Leo 4.6: -------------------------- - Cached external files *greatly* reduces the time to load .leo files. - Leo now features a modern Qt interface by default. Leo's legacy Tk interface can also be used. - New --config, --file and --gui command-line options. - Leo tests syntax of .py files when saving them. - Leo can now open any kind of file into @edit nodes. - @auto-rst nodes support "round-tripping" of reStructuredText files. - Properties of commanders, positions and nodes simplify programming. - Improved Leo's unit testing framework. - Leo now requires Python 2.4 or later. - Dozens of small improvements and bug fixes. Links: ------ Leo: http://webpages.charter.net/edreamleo/front.html Forum: http://groups.google.com/group/leo-editor Download: http://sourceforge.net/project/showfiles.php?group_id=3458 Bzr: http://code.launchpad.net/leo-editor/ Quotes: http://webpages.charter.net/edreamleo/testimonials.html -- -------------------------------------------------------------------- Edward K. Ream email: edreamleo(a)yahoo.com Leo: http://webpages.charter.net/edreamleo/front.html --------------------------------------------------------------------

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[ANN] BleachBit 0.5.2
by Andrew Ziem 22 Jun '09

22 Jun '09

BleachBit is a Internet history, locale, registry, privacy, and temporary file cleaner for Linux and Windows on Python v2.4 - v2.6. Notable changes for 0.5.2: * Add cleaners for Pidgin, Miro, Nexuiz, gedit, Winamp, Yahoo! Messenger, and Windows temporary folder * Clean more of Firefox, Vuze/Azureus, OpenOffice.org, aMSN, espeak, and GNOME's trash. * Add Dutch and Hungarian translations. * Update Arabic, Brazilian Portuguese, Czech, German, Italian, and Slovak translations. * Fix bugs regarding Firefox, cleaning resulting in size increases, shredding write protected files, compatibility with Python 2.6. * Fix many bugs on the new Microsoft Windows port. Detailed release notes http://bleachbit.blogspot.com/2009/06/bleachbit-052-released.html Download http://bleachbit-project.appspot.com/download/

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Re: ride tab editor 2.02 released
by edexter 22 Jun '09

22 Jun '09

On Jun 22, 3:55 am, edexter <Eric_Dex...(a)msn.com> wrote: > 2.01 > > more changes in the menu to give it a more traditional look > custom tab formats have been included to let the user do what they > wish > more options under help message board and iran.org (support democracy > in iran) > > 2.02 > > custom instruments added (banjo, mandolin, ukulele) > alternitive tunings for guitar (dropped d, dadgad) > example of creating a custom tab piano roll for csound. > changes to the about box > > ride tab editor is a tab editor created in 2004 that originally > allowed guitar, bass and drums. > ride tab editor 2 is started to address problems people had of finding > tab editors for other instruments > by allowing them to create custom format definitions. It is also very > useful to create text based piano rolls > for text based music programming languages such as csound. two > examples are provided. > > a drum tab to csound creater > piano roll to csound creater > > file:///C:/Ride%20Tab%20Editor/ride%20tab%20editor%202.02/ride_tab_editor.h tml > > A compiled version of the original 1.0 can be found on sourceforge for > windows, mac and linux the link came out mangeled http://dexrowem.blogspot.com/search?q=ride+tab+editor

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ride tab editor 2.02 released
by edexter 22 Jun '09

22 Jun '09

2.01 more changes in the menu to give it a more traditional look custom tab formats have been included to let the user do what they wish more options under help message board and iran.org (support democracy in iran) 2.02 custom instruments added (banjo, mandolin, ukulele) alternitive tunings for guitar (dropped d, dadgad) example of creating a custom tab piano roll for csound. changes to the about box ride tab editor is a tab editor created in 2004 that originally allowed guitar, bass and drums. ride tab editor 2 is started to address problems people had of finding tab editors for other instruments by allowing them to create custom format definitions. It is also very useful to create text based piano rolls for text based music programming languages such as csound. two examples are provided. a drum tab to csound creater piano roll to csound creater file:///C:/Ride%20Tab%20Editor/ride%20tab%20editor%202.02/ride_tab_editor.html A compiled version of the original 1.0 can be found on sourceforge for windows, mac and linux

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