Mailman 3 July 2005 - Python-announce-list

[ANN] python-dateutil 1.0
by Gustavo Niemeyer July 19, 2005

July 19, 2005

Changes since 0.9 ----------------- * Fixing parsing of XXhXXm formatted time after day/month/year has been parsed. * Adding patch by Jeffrey Harris optimizing rrule.__contains__. What is it? ----------- The dateutil module provides powerful extensions to the standard datetime module, available in Python 2.3+. Features -------- * Computing of relative deltas (next month, next year, next monday, last week of month, and a lot more); * Computing of relative deltas between two given date and/or datetime objects; * Computing of dates based on very flexible recurrence rules (every month, every week on Thursday and Friday, every Friday 13th, and a *LOT* more), using a superset of the iCalendar RFC specification. Parsing of RFC strings is supported as well. * Generic parsing of dates in almost any string format; * Timezone (tzinfo) implementations for tzfile(5) format files (/etc/localtime, /usr/share/zoneinfo, etc), TZ environment string (in all known formats), iCalendar format files, given ranges (with help from relative deltas), local machine timezone, fixed offset timezone, UTC timezone, and Windows registry-based timezones. * Internal up-to-date world timezone information based on Olson's database. * Computing of Easter Sunday dates for any given year, using Western, Orthodox or Julian algorithms; * More than 400 test cases. Where to get it? ---------------- https://moin.conectiva.com.br/DateUtil -- Gustavo Niemeyer http://niemeyer.net

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SoCal Piggies meeting: Thu. July 21st at 7PM
by Grig Gheorghiu July 18, 2005

July 18, 2005

The next meeting of the SoCal Python Interest Group will be at USC this Thursday July 21st at 7 PM. Directions to the meeting are available on the group's wiki: <http://www.socal-piggies.org/socalpiggies/USC_Salvatori_Computer_Science_Ce…> I'll be presenting an overview of the py library, with an emphasis on py.test. Grig

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Sydney Python Meetup July 21: Python, Perl, and Cold Beverages
by Alan Green July 18, 2005

July 18, 2005

Date: Thursday July 21 Time: 6:00pm-8:30pm, with drinks and food during and after. Topics: Graham Dumpleton on The Vampire mod_python extension Paul Fenwick "So you want to start a business?" Place: James Squires Brewhouse 2 The Promenade, King St Wharf Sydney Fee: $0.00 The Sydney Python meetup group is on this Thursday. The meeting time has been brought forward half an hour, and the formal part of the evening will commence promptly at 6:30pm. The James Squires Brewhouse managed to book the Python Meetup Group and the Perl Mongers in adjoining rooms for the same night. Everybody has promised to be nice and we'll be combining with them to hear from one of their Melbourne gurus. As always, everybody is welcome. Graham Dumpleton, author of Vampire, will be speaking first (6:30-7:30). He describes his presentation thusly: "Although I'll talk a bit about the motivations behind writing Vampire and why this extra layer on top of mod_python is useful, what I want to talk about more is what I have learnt from writing Vampire. From that I would like to go on to describe a new and better way of doing this same thing for mod_python that Vampire attempted to do. This new approach moves even further away from the monolithic framework approach towards small building blocks of functionality that can be slotted together to build up a web application how you want it and not how some framework dictates you should do it." More information on Vampire can be found at http://www.dscpl.com.au/projects/vampire/ Paul Fenwick of the Melbourne Perl Mongers will also be speaking (7:30-8:30). His talk, "So you want to start a business", will be presented at the SAGE-AU conference later this year, and an abstract can be found online at http://www.sage-au.org.au/conf/sage-au2005/speakers.html#fenwickabs

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Roundup Issue Tracker release 0.8.4
by Richard Jones July 18, 2005

July 18, 2005

Roundup is a simple-to-use and -install issue-tracking system with command-line, web and e-mail interfaces. It is based on the winning design from Ka-Ping Yee in the Software Carpentry "Track" design competition. This 0.8.4 release fixes some bugs: Fixed: - extra CRs in CSV export files on Windows platform (sf bug 1195742) - activity RDBMS columns were being reported in changes - fix name collision in roundup.cgi script (sf bug 1203795) - fix handling of invalid interval input - search locale files relative ro roundup installation path (sf bug 1219689) - use translation for boolean property rendering (sf bug 1225152) - enabled disabling of REMOTE_USER for when it's not a valid username (sf bug 1190187) - fix invocation of hasPermission from templating code (sf bug 1224172) - have 'roundup-admin security' display property restrictions (sf bug 1222135) - fixed templating menu() sort_on handling (sf bug 1221936) - allow specification of pagesize, sorting and filtering in "classhelp" popups (sf bug 1211800) - handle dropped properies in rdbms/metakit journal export (sf bug 1203569) - handle missing Subject lines better (sf bug 1198729) - sort/group by missing values correctly (sf bugs 1198623, 1176897) - discard, don't bounce messages to the mailgw when the messages's sender is invalid (ie. when we try to bounce, we get a 550 "unknown user account" response from the SMTP server) (sf bug 1190906) - removed debugging code from cgi/actions.py - refactored hyperdb.rawToHyperdb, allowing a number of improvements (thanks Ralf Schlatterbeck) - don't try to set a timeout for IMAPS (thanks Paul Jimenez) - present Reject exception messages to web users (sf bug 1237685) If you're upgrading from an older version of Roundup you *must* follow the "Software Upgrade" guidelines given in the maintenance documentation. Roundup requires python 2.3 or later for correct operation. To give Roundup a try, just download (see below), unpack and run:: python demo.py Source and documentation is available at the website: http://roundup.sourceforge.net/ Release Info (via download page): http://sourceforge.net/projects/roundup Mailing lists - the place to ask questions: http://sourceforge.net/mail/?group_id=31577 About Roundup ============= Roundup manages a number of issues (with flexible properties such as "description", "priority", and so on) and provides the ability to: (a) submit new issues, (b) find and edit existing issues, and (c) discuss issues with other participants. The system will facilitate communication among the participants by managing discussions and notifying interested parties when issues are edited. One of the major design goals for Roundup that it be simple to get going. Roundup is therefore usable "out of the box" with any python 2.3+ installation. It doesn't even need to be "installed" to be operational, though a disutils-based install script is provided. It comes with two issue tracker templates (a classic bug/feature tracker and a minimal skeleton) and five database back-ends (anydbm, sqlite, metakit, mysql and postgresql).

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[ANN] Release 0.42 of Task Coach
by Frank Niessink July 17, 2005

July 17, 2005

Hi all, Hi all, I'm pleased to announce release 0.42 of Task Coach. New in this release: Bugs fixed: * Double clicking a task with children in the tree view would open the edit dialog and expand or collapse the task as well. Fixed to not collapse or expand the task when double clicking it. * Adding a subtask to a collapsed parent task now automatically expands the parent task. * Changing the description of a task or effort record wouldn't mark the task file as changed. * Time spent is now updated every second. * Don't try to make a backup when loading the file fails. Reported by Scott Schroeder. * (Windows installer only) Association between .tsk files and Task Coach was broken. Feature changed: * The start date of a task can now be left unset, creating a task that is permanently inactive. This can be useful for activities that you would normally not want to plan, but have to keep a time record for, e.g. sickness. What is Task Coach? Task Coach is a simple task manager that allows for hierarchical tasks, i.e. tasks in tasks. Task Coach is open source (GPL) and is developed using Python and wxPython. You can download Task Coach from: http://taskcoach.niessink.com https://sourceforge.net/projects/taskcoach/ A binary installer is available for Windows XP, in addition to the source distribution. Note that Task Coach is alpha software, meaning that it is wise to back up your task file regularly, and especially when upgrading to a new release. Cheers, Frank

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IMDbPY 2.0 released
by alberanid＠libero.it July 17, 2005

July 17, 2005

IMDbPY 2.0 is available (tgz, deb, rpm, exe) from: http://imdbpy.sourceforge.net/ IMDbPY is a Python package useful to retrieve and manage the data of the IMDb movie database about both movies and people. This is mostly a bug-fix release; amongst the few new features, the ability to retrieve the "recommendations" and the "plot outline" information. Platform-independent and written in pure Python (and few C lines), it 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> [PGP KeyID: 0x465BFD47] http://erlug.linux.it/~da/

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ANN: MyNewspaper-1.0
by Iñigo Serna July 16, 2005

July 16, 2005

Hi there, I'm really pleased to announce the first public release of MyNewspaper. MyNewspaper is a personal RSS Aggregator and Reader, licensed under GPL. Why? As everybody says, I couldn't find any which fulfills all my requirements. In fact I used liferea and was pretty happy with it, but it eats lot of memory when you have many feeds and the program is running for much time, but the main problem was that it's a desktop program and I couldn't read the feeds from the work. So I started writing my own RSS aggregator and reader. MyNewspaper is written in Python with a bit of javascript and uses sqlite as permanent storage for the articles. It is installed as a CGI, so in order to use and manage it you need a web browser and a web server. Feeds are updated by a command run by cron or from the WebUI. Read more and download it from: http://inigo.katxi.org/devel/mynewspaper or http://www.terra.es/personal7/inigoserna/mynewspaper Of course, all comments, suggestions etc. are welcome. And yes, I know code is really awful now, but I wanted to make a public release to get some feedback while improving the code. Best regards, -- Iñigo Serna <inigoserna(a)terra.es> Katxijasotzaileak

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ReleaseForge 0.9.1 - A SourceForge & Freshmeat release tool
by stuff＠mailzilla.net July 15, 2005

July 15, 2005

ReleaseForge 0.9.1 is now available for immediate download at: http://releaseforge.sourceforge.net ------------------------------------------------------- About ReleaseForge 0.9.1: - ReleaseForge now attempts to "guess" the SourceForge CPU (Processor) type of each file added to a release based on it's filename. - A batch update facility was added which allows the user to quickly modify the status (hidden or active) of multiple releases. - Context sensitive menus (right-click) have been added to the main window\'s projects & packages (listviews). - ReleaseForge now also checks for Windows $HOMEDRIVE & $HOMEPATH environment variables on startup if $HOME is not found. ------------------------------------------------------- About ReleaseForge: ReleaseForge is a GUI application designed for project administrators and release engineers of projects that are hosted at SourceForge. It is intended to make it easier and faster to create a new release and edit existing releases rather than using the SourceForge Web interface. ReleaseForge streamlines the release effort by prompting you for information regarding your new release (version info, change log, release notes, files to include, etc). It then seamlessly negotiates with the SourceForge Web server, creating your release, posting your release notes/change log, uploading your files to the SourceForge FTP server, selecting the files for inclusion in your release on the SourceForge Web server, updating the file attributes of each of the files and then, if appropriate, notifying monitoring users of the new release. ReleaseForge also includes support for posting Freshmeat news announcements and SourceForge project news announcements. ------------------------------------------------------- http://releaseforge.sourceforge.net

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Kamaelia Talk & Mini Sprint at Open Tech 2005, London, July 23
by Michael Sparks July 15, 2005

July 15, 2005

Hi, Apologies first to those outside the UK... Open Tech 2005* is a follow on from previous years' NotCon events which are community driven low cost events by geeks & developers for geeks & developers. (Much like Pycon & Europython but much more general in nature) Website: http://www.ukuug.org/events/opentech2005/ Where/When: Hammersmith, London, UK, July 23rd The reason I'm posting about it is because I'm going to be talking about Kamaelia there. Unlike Python UK & Europython this is going to be a 15 minute talk, so I'll be focussing on what we've been doing with Kamaelia, what you can do with Kamaelia, and so on rather than going through internals. In addition since my talk on Kamaelia is before lunch, I'd really like to help people get started using Kamaelia (this really the point of giving talks!), so I'm going to be running a small ad-hoc/mini sprint that afternoon. There's a variety of possible sprintable things ranging from how to put together simple Kamaelia systems through to using Kamaelia for simplifying networking on Nokia mobiles through to using Kamaelia for writing games (since we have some nice Pygame based components now). I'll probably be sprinting on converting a proof of concept P2P swarming algorithm into a protocol for creating TCP server swarms. This is for joining together multicast islands to make it so that internet broadcasting, rather than narrowcasting, can become a reality for the BBC - which has clear benefits for everyone! (Even though the internet is not TV :) Kamaelia is designed to be able to picked up relatively quickly/easily, but having a working knowledge of python is probably a necessity. If you're interested, please let me know! (Either before, or at Open Tech :) Sprint Info: http://kamaelia.sourceforge.net/OpenTech2005.html Best Regards, Michael. -- Michael.Sparks(a)rd.bbc.co.uk, http://kamaelia.sourceforge.net/ British Broadcasting Corporation, Research and Development Kingswood Warren, Surrey KT20 6NP This message (and any attachments) may contain personal views which are not the views of the BBC unless specifically stated.

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ANN: PyTables 1.1 released
by Francesc Altet July 15, 2005

July 15, 2005

========================= Announcing PyTables 1.1 ========================= After quite a few testing iterations, the PyTables development team is happy to announce the availability of PyTables 1.1. On this version you will find support for a nice set of new features, like nested datatypes, enumerated datatypes, nested iterators (for reading only), support for native HDF5 multidimensional attributes, a new object for dealing with compressed, non-enlargeable arrays (CArray), bzip2 compression support and more. Many bugs has been addressed as well. Go to the PyTables web site for downloading the new beast: http://pytables.sourceforge.net/ or keep reading for more info about the new features and bugs fixed. Changes more in depth ===================== Improvements: - Support for nested datatypes is in place. You can now made columns of tables that host another columns for an unlimited depth (well, theoretically, in practice until the python recursive limit would be reached). Convenient NestedRecArray objects has been implemented as data containers. Cols and Description accessors has been improved so you can navigate on the type hierarchy very easily (natural naming is has been implemented for the task). - ``Table``, ``EArray`` and ``VLArray`` objects now support enumerated types. ``Array`` objects support opening existing HDF5 enumerated arrays. Enumerated types are restricted sets of ``(name, value)`` pairs. Use the ``Enum`` class to easily define new enumerations that will be saved along with your data. - Now, the HDF5 library is responsible to do data conversions when the datasets are written in a machine with different byte-ordering than the machine that reads the dataset. With this, all the data is converted on-the-fly and you always get native datatypes in memory. I think this approach to be more convenient in terms of CPU consumption when using these datasets. Right now, this only works for tables, though. - Added support for native HDF5 multidimensional attributes. Now, you can load native HDF5 files that contains fully multidimensional attributes; these attributes will be mapped to NumArray objects. Also, when you save NumArray objects as attributes, they get saved as native HDF5 attributes (before, NumArray attributes where pickled). - A brand-new class, called CArray, has been introduced. It's mainly like an Array class (i.e. non-enlargeable), but with compression capabilities enabled. The existence of CArray also allows PyTables to read native HDF5 chunked, non-enlargeable datasets. - Bzip2 compressor is supported. Such a support was already in PyTables 1.0, but forgot to announce it. - New LZO2 (http://www.oberhumer.com/opensource/lzo/lzonews.php) compressor is supported. The installer now recognizes whether LZO1 or LZO2 is installed, and adapts automatically to it. If both are installed in your system, then LZO2 is chosen. LZO2 claims to be fully compatible (both backward and forward) with LZO1, so you should not experience any problem during this transition. - The old limit of 256 columns in a table has been released. Now, you can have tables with any number of columns, although if you try to use a too high number (i.e. > 1024), you will start to consume a lot of system resources. You have been warned!. - The limit in the length of column names has been released also. - Nested iterators for reading in tables are supported now. - A new section in tutorial about how to modify values in tables and arrays has been added to the User's Manual. Backward-incompatible changes: - None. Bug fixes: - VLArray now correctly updates the number of rows internal counter when opening an existing VLArray object. Now you can add new rows to existing VLA's without problems. - Tuple flavor for VLArrays now works as intended, i.e. reading VLArray objects will always return tuples even in the case of multidimensional Atoms. Before, this operations returned a mix of tuples and lists. - If a column was not able to be indexed because it has too few entries, then _whereInRange is called instead of _whereIndexed. Fixes #1203202. - You can call now Row.append() in the middle of Table iterators without resetting loop counters. Fixes #1205588. - PyTables used to give a segmentation fault when removing the last row out of a table with the table.removeRows() method. This is due to a limitation in the HDF5 library. Until this get fixed in HDF5, a NotImplemented error is raised when trying to do that. Address #1201023. - You can safely break a loop over an iterator returned by Table.where(). Fixes #1234637. - When removing a Group with hidden child groups, those are effectively closed now. - Now, there is a distinction between shapes 1 and (1,) in tables. The former represents a scalar, and the later a 1-D array with just one element. That follows the numarray convention for records, and makes more sense as well. Before 1.1, shapes 1 and (1,) were represented by an scalar on disk. Known bugs: - Classes inheriting from IsDescription subclasses do not inherit columns defined in the super-class. See SF bug #1207732 for more info. - Time datatypes are non-portable between big-endian and little-endian architectures. This is ultimately a consequence of a HDF5 limitation. See SF bug #1234709 for more info. Important note for MacOSX users =============================== UCL compressor seems to work badly on MacOSX platforms. Until the problem would be isolated and eventually solved, UCL will not be compiled by default on MacOSX platforms, even if the installer finds it in the system. However, if you still want to get UCL support on MacOSX, you can use the --force-ucl flag in setup.py. Important note for Python 2.4 and Windows users =============================================== If you are willing to use PyTables with Python 2.4 in Windows platforms, you will need to get the HDF5 library compiled for MSVC 7.1, aka .NET 2003. It can be found at: ftp://ftp.ncsa.uiuc.edu/HDF/HDF5/current/bin/windows/5-164-win-net.ZIP Users of Python 2.3 on Windows will have to download the version of HDF5 compiled with MSVC 6.0 available in: ftp://ftp.ncsa.uiuc.edu/HDF/HDF5/current/bin/windows/5-164-win.ZIP What it is ========== **PyTables** is a package for managing hierarchical datasets and designed to efficiently cope with extremely large amounts of data (with support for full 64-bit file addressing). It features an object-oriented interface that, combined with C extensions for the performance-critical parts of the code, makes it a very easy-to-use tool for high performance data storage and retrieval. Perhaps its more interesting feature is that it optimizes memory and disk resources so that data take much less space (between a factor 3 to 5, and more if the data is compressible) than other solutions, like for example, relational or object oriented databases. Besides, PyTables I/O for table objects is buffered, implemented in C and carefully tuned so that you can reach much better performance with PyTables than with your own home-grown wrappings to the HDF5 library. PyTables sports indexing capabilities as well, allowing doing selections in tables exceeding one billion of rows in just seconds. Where can PyTables be applied? ============================== PyTables is not designed to work as a relational database competitor, but rather as a teammate. If you want to work with large datasets of multidimensional data (for example, for multidimensional analysis), or just provide a categorized structure for some portions of your cluttered RDBS, then give PyTables a try. It works well for storing data from data acquisition systems (DAS), simulation software, network data monitoring systems (for example, traffic measurements of IP packets on routers), very large XML files, or for creating a centralized repository for system logs, to name only a few possible uses. What is a table? ================ A table is defined as a collection of records whose values are stored in fixed-length fields. All records have the same structure and all values in each field have the same data type. The terms "fixed-length" and "strict data types" seem to be quite a strange requirement for a language like Python that supports dynamic data types, but they serve a useful function if the goal is to save very large quantities of data (such as is generated by many scientific applications, for example) in an efficient manner that reduces demand on CPU time and I/O resources. What is HDF5? ============= For those people who know nothing about HDF5, it is a general purpose library and file format for storing scientific data made at NCSA. HDF5 can store two primary objects: datasets and groups. A dataset is essentially a multidimensional array of data elements, and a group is a structure for organizing objects in an HDF5 file. Using these two basic constructs, one can create and store almost any kind of scientific data structure, such as images, arrays of vectors, and structured and unstructured grids. You can also mix and match them in HDF5 files according to your needs. Platforms ========= We are using Linux on top of Intel32 as the main development platform, but PyTables should be easy to compile/install on other UNIX machines. This package has also been successfully compiled and tested on a FreeBSD 5.4 with Opteron64 processors, a UltraSparc platform with Solaris 7 and Solaris 8, a SGI Origin3000 with Itanium processors running IRIX 6.5 (using the gcc compiler), Microsoft Windows and MacOSX (10.2 although 10.3 should work fine as well). In particular, it has been thoroughly tested on 64-bit platforms, like Linux-64 on top of an Intel Itanium, AMD Opteron (in 64-bit mode) or PowerPC G5 (in 64-bit mode) where all the tests pass successfully. Regarding Windows platforms, PyTables has been tested with Windows 2000 and Windows XP (using the Microsoft Visual C compiler), but it should also work with other flavors as well. Web site ======== Go to the PyTables web site for more details: http://pytables.sourceforge.net/ To know more about the company behind the PyTables development, see: http://www.carabos.com/ Share your experience ===================== Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. ---- **Enjoy data!** -- The PyTables Team

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