Mailman 3 December 2004 - Python-announce-list

ANN: eGenix mx Experimental Package 0.9.0 (mxNumber, mxTidy, mxURL, etc.)
by M.-A. Lemburg 06 Dec '04

06 Dec '04

________________________________________________________________________ ANNOUNCING eGenix.com mx Experimental Extension Package Version 0.9.0 Experimental Python extensions providing important and useful services for Python programmers. ________________________________________________________________________ ABOUT The eGenix.com mx Experimental Extensions for Python are a collection of beta quality software tools for Python which will be integrated into the other mx Extension Packages after they have matured to professional quality tools. * About Python: Python is an object-oriented Open Source programming language which runs on all modern platforms (http://www.python.org/). By integrating ease-of-use, clarity in coding, enterprise application connectivity and rapid application design, Python establishes an ideal programming platform for todays IT challenges. * About eGenix: eGenix is a consulting and software product company focused on providing professional quality services and products to Python users and developers (http://www.egenix.com/). ________________________________________________________________________ NEWS The new version includes patches needed to compile the package for Python 2.4. It now supports all Python versions 1.5.2 - 2.4. As always we are providing pre-compiled versions of the package for Windows and Linux as well as sources which allow you to install the package on all other supported platforms. ________________________________________________________________________ EGENIX MX EXPERIMENTAL PACKAGE OVERVIEW mxNumber - Python Interface to GNU MP Number Types mxNumber provides direct access to the high performance numeric types available in the GNU Multi-Precision Lib (GMP). This library is licensed under the LGPL and runs on practically all Unix platforms. eGenix.com has ported the GMP lib to Windows, to also provide our Windows users with the added benefit of being able to do arbitrary precision calculations and to easily port applications based on mxNumber from Unix to Windows or vice-versa. The package currently provide theses numerical types: 1. Integer(value) -- arbitrary precision integers much like Python longs only faster 2. Rational(nom,denom) -- rational numbers with Integers as numerator and denominator 3. Float(value[,prec]) -- floating point number with at least prec bits precision 4. FareyRational(value, maxden) -- calculate the best rational representation n/d of value such that d < maxden mxTidy - Interface to HTML Tidy (HTML/XML cleanup tool) mxTidy provides a Python interface to a thread-safe, library version of the HTML Tidy. command line tool. HTML Tidy helps you to cleanup coding errors in HTML and XML files and produce well-formed HTML, XHTML or XML as output. This allows you to pre-process web-page for inclusion in XML repositories, prepare broken XML files for validation and also makes it possible to write converters from well-known word processing applications such as MS Word to other structured data representations by using XML as intermediate format. mxURL - A fast URL Data-Type mxURL provides a new data-type for storing and manipulating URL values as well as a few helpers related to URL building, encoding and decoding. The main intention of the package is to provide an easy to use, fast and lightweight data-type for Universal Resource Locators (note the W3C now calls these URIs). mxUID - A fast UID Data-Type mxUID provides a fast mechanism for generating universal identification strings (UIDs). The intent is to make these UIDs unique with high probability in order to serve as object or data set identifiers. A typical use lies in generating session IDs. Other areas where unique IDs play an important role are RPC-implementations, ORBs, etc. ________________________________________________________________________ DOWNLOADS The download archives and instructions for installing the packages can be found at: http://www.egenix.com/ Note that in order to use the eGenix mx Experimental package you will first need to install the eGenix mx Base package which can be downloaded from the same location. ________________________________________________________________________ LICENSES & COSTS The mx-Experimental packages uses different licenses in its sub-packages. Please refer to the sub-package documentation for details. Some of them may be integrated into the eGenix mx Base package, others will be integrated into the eGenix mx Commercial package. The package comes with full source code ________________________________________________________________________ SUPPORT Commercial quality support for these packages is available from eGenix.com. Please see http://www.egenix.com/files/python/eGenix-mx-Extensions.html#Support for details about our support offerings. -- Marc-Andre Lemburg eGenix.com Professional Python Services directly from the Source (#1, Dec 06 2004) >>> Python/Zope Consulting and Support ... http://www.egenix.com/ >>> mxODBC.Zope.Database.Adapter ... http://zope.egenix.com/ >>> mxODBC, mxDateTime, mxTextTools ... http://python.egenix.com/ ________________________________________________________________________ ::: Try mxODBC.Zope.DA for Windows,Linux,Solaris,FreeBSD for free ! ::::

1 0

Announce: Zope Technical Solutions Training January 24th - 27th
by Brian Lloyd 06 Dec '04

06 Dec '04

Zope Technical Solutions Session -------------------------------- The next session will be held January 24th - 27th at our headquarters in Fredericksburg, VA. This three day course will familiarize students with Zope software from introductory through advanced topics. We will demonstrate the flexibility and effectiveness of Zope as an Open Source web development and content management environment. We will also explore Zope architecture and provide hands-on exercises using Zope to develop and manage a robust web site. We offer several opportunities to meet with and share ideas over lunch with Jim Fulton (CTO) and the Zope engineering teams. Course Objectives: After completing this course students will understand: - Zope's use of objects, methods, etc. - Zope's Management Interface. - Zope's server-side scripting language (DTML). - Page Templates. - Web site content creation and management. - Web site security through user privileges and roles. - Using Zope to integrate web sites with existing + relational databases. - Downloading/installing a Zope Product, and - Introduction to CMF. The course is intended for those interested in using a full-featured open source environment to develop and manage robust corporate internet or intranet web sites. This includes web site designers, content creators, content managers and web developers. Participants should be familiar with HTML and basic web architecture (e.g., how a web server and web browser work together). Knowledge of object-oriented concepts and SQL is recommended. For more detailed information about the course, including pricing, travel and accommodations, please go to our website www.zope.com or email training at zope.com. Please note that "Early Bird" pricing expires at the close of business on Friday, Dec 24, 2004. Brian Lloyd brian(a)zope.com V.P. Engineering 540.361.1716 Zope Corporation http://www.zope.com

1 0

Ptyon 2.3.5 probably coming in January; get your bugs/patches reported!
by Brett C. 06 Dec '04

06 Dec '04

Anthony Baxter, our ever-diligent release manager, mentioned this past week that Python 2.3.5 will most likely come to fruition some time in January (this is not guaranteed date). This means that in order to have enough time to proper evaluate new patches and bugs they must be reported **now**! A one month lead time is necessary to properly look at, test, and commit patches, let alone coming up with solutions to any reported bugs. Please realize, though, that reporting a bug or submitting a patch now does not guarantee that it will committed in time! The free time of the development team is limited. If you want to help a bug or patch along to make it easier to be evaluated and thus raise its chances of being dealt with please see the "Helping Out" section of the 'Intro to Development' essay at http://www.python.org/dev/dev_intro.html . As always, both bugs and patches should be reported to Python's SourceForge tracker at http://sourceforge.net/bugs/?group_id=5470 and http://sourceforge.net/patch/?group_id=5470, respectively. -Brett Cannon

1 0

BayPIGgies: December 9, 7:30pm
by Aahz 06 Dec '04

06 Dec '04

The next meeting of BayPIGgies will be Thurs, Dec 9 at 7:30pm. Stephen McInerney and Terry Carroll lead a discussion on how to make your employer open-source-friendly: - how to get your work published - how to package your work for distribution - how to negotiate open-source clauses in a contract - the different types of license (which is suited to what) BayPIGgies meetings are in Stanford, California. For more information and directions, see http://www.baypiggies.net/ Before the meeting, we may meet at 6pm for dinner in downtown Palo Alto. Discussion of dinner plans is handled on the BayPIGgies mailing list. Advance notice: The January 13 meeting agenda has not been set. Please send e-mail to baypiggies(a)baypiggies.net if you want to make a presentation. -- Aahz (aahz(a)pythoncraft.com) <*> http://www.pythoncraft.com/ WiFi is the SCSI of the 21st Century -- there are fundamental technical reasons for sacrificing a goat. (with no apologies to John Woods)

1 0

ANN: ElementTree 1.2.2 (december 5, 2004)
by Fredrik Lundh 05 Dec '04

05 Dec '04

The Element type is a simple but flexible container object, designed to store hierarchical data structures, such as simplified XML infosets, in memory. The ElementTree package provides a Python implementation of this type, plus code to serialize element trees to and from XML files. ElementTree 1.2.2 is 1.2.1 plus an improved version of the HTML parser, backported from the 1.3 development branch. The new parser supports arbitrary character data encodings, and properly handles documents that mixes non-ASCII character data with non-ASCII character references and entities. You can get the ElementTree package from: http://effbot.org/downloads Documentation, code samples, and points to articles about the Element- Tree module are available from: http://effbot.org/zone/element.htm enjoy /F

1 0

ANN: Naja 1.1.3 is now available
by webmaster＠keyphrene.com 05 Dec '04

05 Dec '04

Naja is a download manager and a website grabber written in Python/wxPython.You can add some plugins (newsreader, FTP client,WebDAV client) and take control of your downloads from your office. Naja supports proxy(HTTP, HTTPS, FTP, SOCKS v4a, SOCKS v5), and use some authentication methods. The downloading maybe achieved by splitting the file being downloaded into several parts and downloading these parts at the same time (HTTP, HTTPS, FTP). Donwload speeds are increased by downloading the file from the mirrors sites, when the sites propose it. Others features: Csv filter Cheksums (CRC32, MD2, MD4, MD5, SHA, SHA1, MDC2, RMD160) Crypt (Only for the eXtended version) and Decrypt (AES, DES, 3DES ...) newsreader, newsposter (uue, yEnc) CGI & WebDAV Server Web Interface basic and digest authentication for client and server Compress and decompress (zip, tar.gz, tar.bz2) Picture viewer Text Editor Naja is available for download from the Keyphrene web site: http://www.keyphrene.com/products/naja

1 0

Updated Cygwin Package: python-2.4-1
by Jason Tishler 05 Dec '04

05 Dec '04

New News: === ==== I have updated the version of Python to 2.4-1. The tarballs should be available on a Cygwin mirror near you shortly. The following is the only notable change since the previous release: o upgrade to Python 2.4 Old News: === ==== Python is an interpreted, interactive, object-oriented programming language. If interested, see the Python web site for more details: http://www.python.org/ Please read the README file: /usr/share/doc/Cygwin/python-2.4.README since it covers requirements, installation, known issues, etc. Standard News: ======== ==== 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 . *** CYGWIN-ANNOUNCE UNSUBSCRIBE INFO *** If you want to unsubscribe from the cygwin-announce mailing list, look at the "List-Unsubscribe: " tag in the email header of this message. Send email to the address specified there. It will be in the format: cygwin-announce-unsubscribe-you=yourdomain.com(a)cygwin.com If you need more information on unsubscribing, start reading here: http://sources.redhat.com/lists.html#unsubscribe-simple Please read *all* of the information on unsubscribing that is available starting at this URL. Jason -- PGP/GPG Key: http://www.tishler.net/jason/pubkey.asc or key servers Fingerprint: 7A73 1405 7F2B E669 C19D 8784 1AFD E4CC ECF4 8EF6

1 0

ANN: PyEnchant 0.9.0
by Ryan Kelly 04 Dec '04

04 Dec '04

Hi All, I've just released my work on producing Python bindings for the Enchant spellchecker wrapper library. Enchant (http://www.abisource.com/enchant/) is the spellchecking package behind the AbiWord word processor, is being considered for inclusion in the KDE office suite, and is proposed as a FreeDesktop.org standard. It's completely cross-platform because it wraps the native spellchecking engine to provide a uniform interface. PyEnchant brings this simple, powerful and flexible spellchecking engine to Python: http://www.rfk.id.au/software/projects/pyenchant/ Current Version: 0.9.0 Licence: LGPL with exemptions, as per Enchant itself Cheers, Ryan -- Ryan Kelly http://www.rfk.id.au ryan(a)rfk.id.au

1 0

ANN: PyTables 0.9.1 is out
by Francesc Altet 04 Dec '04

04 Dec '04

Announcing PyTables 0.9.1 ------------------------- This release is mainly a maintenance version. In it, some bugs has been fixed and a few improvements has been made. One important thing is that chunk sizes in EArrays has been re-tuned to get much better performance and compression rations. Besides, it has been tested against the latest Python 2.4 and all test units seems to pass fine. What it is ---------- PyTables is a solid hierarchical database package designed to efficiently manage 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. It is built on top of the HDF5 library and the numarray package, and provides containers for both heterogeneous data (Tables) and homogeneous data (Array, EArray) as well as containers for keeping lists of objects of variable length (like Unicode strings or general Python objects) in a very efficient way (VLArray). It also sports a series of filters allowing you to compress your data on-the-fly by using different compressors and compression enablers. But perhaps the more interesting features are its powerful browsing and searching capabilities that allow you to perform data selections over heterogeneous datasets exceeding gigabytes of data in just tenths of second. Besides, all the PyTables I/O 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. Changes more in depth --------------------- Improvements: - The chunksize computation for EArrays has been re-tuned to allow better performance and *much* better compression rations. - New --unpackshort and --quantize flags has been added to nctoh5 script. --unpackshort unpack short integer variables to float variables using scale_factor and add_offset netCDF variable attributes. --quantize quantize data to improve compression using least_significant_digit netCDF variable attribute (not active by default). See http://www.cdc.noaa.gov/cdc/conventions/cdc_netcdf_standard.shtml for further explanation of what this attribute means. Thanks to Jeff Whitaker for providing this. - Table.itersequence has received a new parameter called "sort". This allows to disable the sorting of the sequence in case the user wants so. Backward-incompatible changes: - Now, the AttributeSet class throw an AttributeError on __getattr__ for nonexistent attributes in it. Formerly, the routine returned None, which is pretty much against convention in Python and breaks the built-in hasattr() function. Thanks to Norbert Nemec for noting this and offering a patch. - VLArray.read() has changed its behaviour. Now, it always returns a list, as stated in documentation, even when the number of elements to return is 0 or 1. This is much more consistent when representing the actual number of elements on a certain VLArray row. API additions: - A Row.getTable() has been added. It is an accessor for the associated Table object. - A File.copyAttrs() has been added. It allows copying attributes from one leaf to other. Properly speaking, this was already there, but not documented :-/ Bug fixes: - Now, the copy of hierarchies works even when there are scalar Arrays (i.e. Arrays which shape is ()) on it. Thanks to Norbert Nemec for providing a patch. - Solved a memory leak regarding the Filters instance associated with the File object, that was not released after closing the file. Now, there are no known leaks on PyTables itself. - Fixed a bug in Table.append() when the table was indexed. The problem was that if table was in auto-indexing mode, some rows were lost in the indexation process and hence, not indexed correctly. - Improved security of nodes name checking. Closes #1074335 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 (and possible LZO and UCL as well, if you want support for LZO and UCL at all). It can be found at: ftp://ftp.ncsa.uiuc.edu/HDF/HDF5/current/bin/windows/5-163-winxp-net2003.zip 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 --------- I'm using Linux (Intel 32-bit) as the main development platform, but PyTables should be easy to compile/install on many other UNIX machines. This package has also passed all the tests on a UltraSparc platform with Solaris 7 and Solaris 8. It also compiles and passes all the tests on a SGI Origin2000 with MIPS R12000 processors, with the MIPSPro compiler and running IRIX 6.5. It also runs fine on Linux 64-bit platforms, like AMD Opteron running GNU/Linux 2.4.21 Server, Intel Itanium (IA64) running GNU/Linux 2.4.21 or PowerPC G5 with Linux 2.6.x in 64bit mode. It has also been tested in MacOSX platforms (10.2 but should also work on newer versions). 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 me know of any bugs, suggestions, gripes, kudos, etc. you may have. Enjoy data! -- Francesc Altet Who's your data daddy? PyTables

1 0

ANN: python-ldap-2.0.6
by Michael Ströder 03 Dec '04

03 Dec '04

Find a new release of python-ldap: http://python-ldap.sourceforge.net/ python-ldap provides an object-oriented API to access LDAP directory servers from Python programs. It mainly wraps the OpenLDAP 2.x libs for that purpose. Additionally it contains modules for other LDAP-related stuff (e.g. processing LDIF, LDAPURLs and LDAPv3 schema). ---------------------------------------------------------------- Released 2.0.6 2004-12-03 Changes since 2.0.5: Lib/: * Added sub-module ldap.dn * Added function ldap.dn.escape_dn_chars() * Special check when implicitly setting SUP 'top' to structural object classes without SUP defined to avoid a loop in the super class chain.

1 0