Mailman 3 April 2013 - Python-announce-list

ANN: psutil 0.7.0 released
by Giampaolo Rodolà 12 Apr '13

12 Apr '13

Hi there folks, I'm pleased to announce the 0.7.0 release of psutil: http://code.google.com/p/psutil/ This is mainly a bugfix release addressing a couple of high priority issues on Linux and FreeBSD. Complete list of bugfixes and enhancements is here: https://psutil.googlecode.com/hg/HISTORY === New features === - psutil.get_boot_time() - get/set process IO priority on Windows - psutil.cpu_times() on Linux now includes new 'steal', 'guest' and guest_nice' fields available on recent kernels - psutil.cpu_times_percent() which provides utilization percentages for each specific CPU time as is returned by cpu_times() - source code has been migrated from SVN to Mercurial === Compatitility notes === - Process cmdline and ppid properties are no longer cached after first access - psutil.error module is deprecated and scheduled for removal === Links === - Home: http://code.google.com/p/psutil - Sources: http://psutil.googlecode.com/files/psutil-0.7.0.tar.gz - Docs: http://code.google.com/p/psutil/wiki/Documentation Please try out this new release and let me know if you experience any problem by filing issues on the bug tracker. Thanks in advance. --- Giampaolo Rodola' http://code.google.com/p/pyftpdlib/ http://code.google.com/p/psutil/ http://code.google.com/p/pysendfile/

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Camelot 13.04.13 released
by erikj 12 Apr '13

12 Apr '13

Hello, Camelot 13.04.13 has been released. Camelot provides components to build business applications on top Python, SQLAlchemy and Qt. For screenshots, see : http://www.python-camelot.com/ An overview of the changes can be found here : http://www.python-camelot.com/3/post/2013/04/release-130413.html Cheers, Erik

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ANN Queues: Distributed, Fault-Tolerant Message Processing by PiCloud
by John Riley 12 Apr '13

12 Apr '13

PiCloud's (http://www.picloud.com) latest feature gives Python users a distributed, fault-tolerant message queue with a scalable message processing system. We ensure that you never lose any messages, and that they're processed at the speed you need--even thousands of messages per second. More information: Blog Post: http://blog.picloud.com/2013/04/03/introducing-queues-creating-a-pipeline-i… Documentation: http://docs.picloud.com/queue.html What's it for? Queues let you decouple discrete components of your application, and simplify communication between them as the pushing and popping of messages. Queues are perfect for integrating PiCloud into a web application backend, or any realtime, high-throughput system. If your workloads have been too short (< 1s) to use our job system effectively, or you've found difficulty creating a multi-stage pipeline with jobs, then you'll want to give queues a try! You'll need the latest cloud library v2.7.7 to use the feature. Best Regards, John

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ANN: phileas0.8 now available
by Larry Myerscough 11 Apr '13

11 Apr '13

phileas = "Python/HTML integration: Larry's Elegant Alternative Solution" Source and documentation can be accessed at: http://larry.myerscough.nl/phileas_project/ N.B. This really is an alternative solution; the other available approaches to this subject don't work for me... ... but may work for you, so be sure also to check pypi.python.org to see the bigger picture! Larry Myerscough, aka paphippo

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ANN: pyftpdlib 1.1.0 released
by Giampaolo Rodolà 09 Apr '13

09 Apr '13

Hi there guys, I'm pleased to announce pyftpdlib 1.1.0. This is mainly a bugfix release, see: https://pyftpdlib.googlecode.com/svn/trunk/HISTORY === Links === Home: http://code.google.com/p/pyftpdlib/ Download: https://pyftpdlib.googlecode.com/files/pyftpdlib-1.1.0.tar.gz Tutorial: http://code.google.com/p/pyftpdlib/wiki/Tutorial Enjoy, Giampaolo

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ANN: eGenix mxODBC Connect - Python ODBC Database Interface 2.0.3
by eGenix Team: M.-A. Lemburg 09 Apr '13

09 Apr '13

________________________________________________________________________ ANNOUNCING eGenix.com mxODBC Connect Python ODBC Database Interface Version 2.0.3 mxODBC Connect is our commercially supported client-server product for connecting Python applications to relational databases in a truly platform independent way. This announcement is also available on our web-site for online reading: http://www.egenix.com/company/news/eGenix-mxODBC-Connect-2.0.3-GA.html ________________________________________________________________________ INTRODUCTION 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, convenient and secure way. Python Database Connectivity the Easy 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 application. Instead you use an easy to install royalty-free Python client library which connects directly to the mxODBC Connect database server over the network. This makes mxODBC Connect a great basis for writing cross-platform multi-tier database applications 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. Ideal for Database Driven Client Applications --------------------------------------------- By removing the need to install and configure ODBC drivers on the client side and dealing with complicated network setups for each set of drivers, mxODBC Connect greatly simplifies deployment 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 have a look at the mxODBC Connect product page, in particular, the full list of available features. For more information, please see the product page: http://www.egenix.com/products/python/mxODBCConnect/ ________________________________________________________________________ NEWS The 2.0.3 release of mxODBC Connect includes the following enhancements and fixes: Security Enhancements --------------------- * Upgraded client and server to the most recent eGenix pyOpenSSL 0.13.1.1.0.1.5. Server Enhancements ------------------- * Updated the server to use mxODBC 3.2.2 for database connectivity. Client Enhancements ------------------- * Added support for the new .cursortype attribute in mxODBC 3.2.2 which is available on both connections and cursors to adjust the used ODBC cursor type. Performance Enhancements ------------------------ * MS SQL Server performance can now be much enhanced, and increased to levels beyond that of mxODBC Connect 2.0.2 and previous releases, by adjusting the default cursor type to forward-only cursors instead of static cursors: # Connect to the remote database from mx.ODBCConnect.Client import ServerSession session = ServerSession(...) ODBC = session.open() connection = ODBC.DriverConnect(...) # Use the faster forward-only cursors connection.cursortype = ODBC.SQL.CURSOR_FORWARD_ONLY # Cursors created on this connection will then default # to forward only cursors cursor = connection.cursor() * The performance increase compared to mxODBC Connect 2.0.2 is enormous: from 2-3x faster executes/fetches for average queries, up to 300x faster for simple cases. In mxODBC Connect 2.1, we will switch to using forward-only cursors per default for all database backends. * IBM DB2 can benefit from the same performance enhancements using forward-only cursors. The effect is a lot smaller compared to MS SQL Server, but still noticeable: up to 2x faster executes/fetches with forward-only cursors, compared to mxODBC Connect 2.0.2. * Added documentation to explain the different cursor types, compatibility with different database backends and effects on performance to the mxODBC documentation. New License Structure --------------------- Due to popular demand, we have added an unlimited connections server license, so now you can choose between: * the entry-level 20-connections server license, * an average use 50-connections server license. * and the unlimited connections server license for our high-end users. For the full set of changes, please check the mxODBC Connect change log. http://www.egenix.com/products/python/mxODBCConnect/changelog.html mxODBC Connect 2.0 Highlights ----------------------------- mxODBC Connect 2.0 was released on 2012-08-20. These are the most important highlights: * mxODBC Connect Server now uses mxODBC 3.2 internally and makes its API available in the mxODBC Connect Client. This is a major step forward from the mxODBC 3.0 version used in mxODBC Connect Server 1.0. * We've added native Windows x64 builds. * mxODBC Connect Client now integrates directly with gevent, allowing client applications to run asynchronous tasks while performing remote database queries. Please see the release announcement for full details: http://www.egenix.com/company/news/eGenix-mxODBC-Connect-2.0.0-GA.html ________________________________________________________________________ UPGRADING You are encouraged to upgrade to this latest mxODBC Connect release. When upgrading, please always upgrade both the server and the client installations to the same version - even for patch level releases. Customers who have purchased mxODBC Connect 2.0 licenses can continue to use their licenses with this patch level release. Customers who have purchased mxODBC Connect 1.x licenses can request 20% discount coupons for upgrade purchases. Please contact the eGenix.com Sales Team (sales(a)egenix.com) with your existing license serials for details. Users of our stand-alone mxODBC product will have to purchase new licenses from our online shop in order to use mxODBC Connect. You can request 30-day evaluation licenses by visiting our web-site or writing to sales(a)egenix.com, stating your name (or the name of the company) and the number of eval licenses that you need. http://www.egenix.com/products/python/mxODBCConnect/#Evaluation ________________________________________________________________________ DOWNLOADS The download archives as well as instructions for installation and configuration of the product can be found on the product page: http://www.egenix.com/products/python/mxODBCConnect/ If you want to try the package, jump straight to the download instructions: https://cms.egenix.com/products/python/mxODBCConnect/#Download Fully functional evaluation licenses for the mxODBC Connect Server are available free of charge: http://www.egenix.com/products/python/mxODBCConnect/#Evaluation mxODBC Connect Client is always free of charge. _______________________________________________________________________ SUPPORT Commercial support for this product is available from eGenix.com. Please see http://www.egenix.com/services/support/ for details about our support offerings. _______________________________________________________________________ INFORMATION About Python (http://www.python.org/): Python is an object-oriented Open Source programming language which runs on all modern platforms. By integrating ease-of-use, clarity in coding, enterprise application connectivity and rapid application design, Python establishes an ideal programming platform for today's IT challenges. About eGenix (http://www.egenix.com/): eGenix is a software project, consulting and product company focusing on expert project services and professional quality products for companies, Python users and developers. Enjoy, -- Marc-Andre Lemburg eGenix.com Professional Python Services directly from the Source (#1, Apr 09 2013) >>> Python Projects, Consulting and Support ... http://www.egenix.com/ >>> mxODBC.Zope/Plone.Database.Adapter ... http://zope.egenix.com/ >>> mxODBC, mxDateTime, mxTextTools ... http://python.egenix.com/ ________________________________________________________________________ 2013-04-02: Released mxODBC Zope DA 2.1.1 ... http://egenix.com/go41 2013-04-10: Python Meeting Duesseldorf ... tomorrow ::::: Try our mxODBC.Connect Python Database Interface 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 http://www.egenix.com/company/contact/

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ANN: SciPy 0.12.0 release
by Ralf Gommers 07 Apr '13

07 Apr '13

We are pleased to announce the availability of SciPy 0.12.0. This release has some cool new features (see highlights below) and a large amount of bug fixes and maintenance work under the hood. The number of contributors also keeps rising steadily - 75 people contributed patches to this release. We hope to see this trend continue. Some of the highlights of this release are: - Completed QHull wrappers in scipy.spatial. - cKDTree now a drop-in replacement for KDTree. - A new global optimizer, basinhopping. - Support for Python 2 and Python 3 from the same code base (no more 2to3). This release requires Python 2.6, 2.7 or 3.1-3.3 and NumPy 1.5.1 or greater. Support for Python 2.4 and 2.5 has been dropped as of this release. Sources and binaries can be found at http://sourceforge.net/projects/scipy/files/scipy/0.12.0/, release notes are copied below. Enjoy, The SciPy developers ========================== SciPy 0.12.0 Release Notes ========================== SciPy 0.12.0 is the culmination of 7 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been a number of deprecations and API changes in this release, which are documented below. All users are encouraged to upgrade to this release, as there are a large number of bug-fixes and optimizations. Moreover, our development attention will now shift to bug-fix releases on the 0.12.x branch, and on adding new features on the master branch. Some of the highlights of this release are: - Completed QHull wrappers in scipy.spatial. - cKDTree now a drop-in replacement for KDTree. - A new global optimizer, basinhopping. - Support for Python 2 and Python 3 from the same code base (no more 2to3). This release requires Python 2.6, 2.7 or 3.1-3.3 and NumPy 1.5.1 or greater. Support for Python 2.4 and 2.5 has been dropped as of this release. New features ============ ``scipy.spatial`` improvements ------------------------------ cKDTree feature-complete ^^^^^^^^^^^^^^^^^^^^^^^^ Cython version of KDTree, cKDTree, is now feature-complete. Most operations (construction, query, query_ball_point, query_pairs, count_neighbors and sparse_distance_matrix) are between 200 and 1000 times faster in cKDTree than in KDTree. With very minor caveats, cKDTree has exactly the same interface as KDTree, and can be used as a drop-in replacement. Voronoi diagrams and convex hulls ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ `scipy.spatial` now contains functionality for computing Voronoi diagrams and convex hulls using the Qhull library. (Delaunay triangulation was available since Scipy 0.9.0.) Delaunay improvements ^^^^^^^^^^^^^^^^^^^^^ It's now possible to pass in custom Qhull options in Delaunay triangulation. Coplanar points are now also recorded, if present. Incremental construction of Delaunay triangulations is now also possible. Spectral estimators (``scipy.signal``) -------------------------------------- The functions ``scipy.signal.periodogram`` and ``scipy.signal.welch`` were added, providing DFT-based spectral estimators. ``scipy.optimize`` improvements ------------------------------- Callback functions in L-BFGS-B and TNC ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ A callback mechanism was added to L-BFGS-B and TNC minimization solvers. Basin hopping global optimization (``scipy.optimize.basinhopping``) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ A new global optimization algorithm. Basinhopping is designed to efficiently find the global minimum of a smooth function. ``scipy.special`` improvements ------------------------------ Revised complex error functions ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The computation of special functions related to the error function now uses a new `Faddeeva library from MIT <http://ab-initio.mit.edu/Faddeeva>`__ which increases their numerical precision. The scaled and imaginary error functions ``erfcx`` and ``erfi`` were also added, and the Dawson integral ``dawsn`` can now be evaluated for a complex argument. Faster orthogonal polynomials ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Evaluation of orthogonal polynomials (the ``eval_*`` routines) in now faster in ``scipy.special``, and their ``out=`` argument functions properly. ``scipy.sparse.linalg`` features -------------------------------- - In ``scipy.sparse.linalg.spsolve``, the ``b`` argument can now be either a vector or a matrix. - ``scipy.sparse.linalg.inv`` was added. This uses ``spsolve`` to compute a sparse matrix inverse. - ``scipy.sparse.linalg.expm`` was added. This computes the exponential of a sparse matrix using a similar algorithm to the existing dense array implementation in ``scipy.linalg.expm``. Listing Matlab(R) file contents in ``scipy.io`` ----------------------------------------------- A new function ``whosmat`` is available in ``scipy.io`` for inspecting contents of MAT files without reading them to memory. Documented BLAS and LAPACK low-level interfaces (``scipy.linalg``) ------------------------------------------------------------------ The modules `scipy.linalg.blas` and `scipy.linalg.lapack` can be used to access low-level BLAS and LAPACK functions. Polynomial interpolation improvements (``scipy.interpolate``) ------------------------------------------------------------- The barycentric, Krogh, piecewise and pchip polynomial interpolators in ``scipy.interpolate`` accept now an ``axis`` argument. Deprecated features =================== `scipy.lib.lapack` ------------------ The module `scipy.lib.lapack` is deprecated. You can use `scipy.linalg.lapack` instead. The module `scipy.lib.blas` was deprecated earlier in Scipy 0.10.0. `fblas` and `cblas` ------------------- Accessing the modules `scipy.linalg.fblas`, `cblas`, `flapack`, `clapack` is deprecated. Instead, use the modules `scipy.linalg.lapack` and `scipy.linalg.blas`. Backwards incompatible changes ============================== Removal of ``scipy.io.save_as_module`` -------------------------------------- The function ``scipy.io.save_as_module`` was deprecated in Scipy 0.11.0, and is now removed. Its private support modules ``scipy.io.dumbdbm_patched`` and ``scipy.io.dumb_shelve`` are also removed. Other changes ============= Authors ======= * Anton Akhmerov + * Alexander Eberspächer + * Anne Archibald * Jisk Attema + * K.-Michael Aye + * bemasc + * Sebastian Berg + * François Boulogne + * Matthew Brett * Lars Buitinck * Steven Byrnes + * Tim Cera + * Christian + * Keith Clawson + * David Cournapeau * Nathan Crock + * endolith * Bradley M. Froehle + * Matthew R Goodman * Christoph Gohlke * Ralf Gommers * Robert David Grant + * Yaroslav Halchenko * Charles Harris * Jonathan Helmus * Andreas Hilboll * Hugo + * Oleksandr Huziy * Jeroen Demeyer + * Johannes Schönberger + * Steven G. Johnson + * Chris Jordan-Squire * Jonathan Taylor + * Niklas Kroeger + * Jerome Kieffer + * kingson + * Josh Lawrence * Denis Laxalde * Alex Leach + * Tim Leslie * Richard Lindsley + * Lorenzo Luengo + * Stephen McQuay + * MinRK * Sturla Molden + * Eric Moore + * mszep + * Matt Newville + * Vlad Niculae * Travis Oliphant * David Parker + * Fabian Pedregosa * Josef Perktold * Zach Ploskey + * Alex Reinhart + * Gilles Rochefort + * Ciro Duran Santillli + * Jan Schlueter + * Jonathan Scholz + * Anthony Scopatz * Skipper Seabold * Fabrice Silva + * Scott Sinclair * Jacob Stevenson + * Sturla Molden + * Julian Taylor + * thorstenkranz + * John Travers + * True Price + * Nicky van Foreest * Jacob Vanderplas * Patrick Varilly * Daniel Velkov + * Pauli Virtanen * Stefan van der Walt * Warren Weckesser A total of 75 people contributed to this release. People with a "+" by their names contributed a patch for the first time.

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[RELEASED] Python 3.2.4 and Python 3.3.1
by Georg Brandl 06 Apr '13

06 Apr '13

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 On behalf of the Python development team, I am pleased to announce the final releases of Python 3.2.4 and 3.3.1. Python 3.2.4 is the final regular maintenance release for the Python 3.2 series, while Python 3.3.1 is the first maintenance release for the 3.3 series. Both releases include hundreds of bugfixes. There has recently been a lot of discussion about XML-based denial of service attacks. Specifically, certain XML files can cause XML parsers, including ones in the Python stdlib, to consume gigabytes of RAM and swamp the CPU. These releases do not include any changes in Python XML code to address these issues. Interested parties should examine the defusedxml package on PyPI: https://pypi.python.org/pypi/defusedxml To download Python 3.2.4 or Python 3.3.1, visit: http://www.python.org/download/releases/3.2.4/ or http://www.python.org/download/releases/3.3.1/ respectively. As always, please report bugs to http://bugs.python.org/ Enjoy! - -- Georg Brandl, Release Manager georg at python.org (on behalf of the entire python-dev team and all contributors) -----BEGIN PGP SIGNATURE----- Version: GnuPG v2.0.19 (GNU/Linux) iEYEARECAAYFAlFgiN8ACgkQN9GcIYhpnLAXxQCdHAd2lECpYfmYM4Wbd3I01es4 898AoKBDvHtgecD/PeVRKUrdQRSWGPJg =K8RQ -----END PGP SIGNATURE-----

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[RELEASE] Python 2.7.4
by Benjamin Peterson 06 Apr '13

06 Apr '13

I'm thrilled to announce the release of Python 2.7.4. 2.7.4 is the latest maintenance release in the Python 2.7 series. It includes hundreds of bugfixes to the core language and standard library. Downloads are at http://python.org/download/releases/2.7.4/ As always, please report bugs to http://bugs.python.org/ Several regressions found in the release candidate have been fixed. Many thanks to those who tested the preview release. There has recently been a lot of discussion about XML-based denial of service attacks. Specifically, certain XML files can cause XML parsers, including ones in the Python stdlib, to consume gigabytes of RAM and swamp the CPU. 2.7.4 does not include any changes in Python XML code to address these issues. Interested parties should examine the defusedxml package on PyPI: https://pypi.python.org/pypi/defusedxml This is a production release. Best wishes, Benjamin Peterson 2.7 Release Manager (on behalf of all of Python 2.7's contributors)

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ANN: sqlparse 0.1.7
by Andi Albrecht 06 Apr '13

06 Apr '13

Hi, I'm pleased to announce sqlparse 0.1.7, a bug fix release. sqlparse is a non-validating SQL parser module. Download: https://pypi.python.org/packages/source/s/sqlparse/sqlparse-0.1.7.tar.gz Bug Fixes * Fix Python 3 compatibility of sqlformat script (by Piet Delport). * Fix parsing of SQL statements that contain binary data (by Alexey Malyshev). * Fix a bug where keywords were identified as aliased identifiers in invalid SQL statements. * Fix parsing of identifier lists where identifiers are keywords too (issue10). Enhancements * Top-level API functions now accept encoding keyword to parse statements in certain encodings more reliable (issue20). * Improve parsing speed when SQL contains CLOBs or BLOBs (issue86). * Improve formatting of ORDER BY clauses (issue89). * Formatter now tries to detect runaway indentations caused by parsing errors or invalid SQL statements. When re-indenting such statements the formatter flips back to column 0 before going crazy. Other * Documentation updates. What is sqlparse? ================= sqlparse is a non-validating SQL parser module for Python. The module provides functions for splitting, formatting and parsing SQL statements. Please file bug reports and feature request on the issue tracker. Project Page: https://github.com/andialbrecht/sqlparse Documentation: http://readthedocs.org/docs/sqlparse/en/latest/ Discussions: http://groups.google.com/group/sqlparse Issues/Bugs: https://github.com/andialbrecht/sqlparse/issues Online Demo: http://sqlformat.org Regards, Andi

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