Mailman 3 February 2013 - Python-announce-list

makefile based python build
by Antonio Cavallo Feb. 11, 2013

Feb. 11, 2013

Hi, I'm releasing my first attempt to cross compile python on android using a simple makefile based build system: https://bitbucket.org/cavallo71/android As side effect it can also build on a gcc based system as (linux so far). The attempt was started in order to simplify the build system and cross compiling modules. In future the hope is to remove distutils package and clear other modules (notably sysconfig.py and site.py). Thanks Antonio

1 0

Jython 2.5.4rc1 and Jython 2.7b1 released!
by Frank Wierzbicki Feb. 10, 2013

Feb. 10, 2013

On behalf of the Jython development team, I'm pleased to announce that the first release candidate of Jython 2.5.4 and the first beta of Jython 2.7 are available. The 2.5.4rc1 details are here: http://fwierzbicki.blogspot.com/2013/02/jython-254-rc1-released.html The 2.7b1 details are here: http://fwierzbicki.blogspot.com/2013/02/jython-27-beta1-released.html Thanks to Adconion Media Group for sponsoring my work on Jython, and thanks to the many contributors to Jython! -Frank

1 0

pyPEG 2.10 released
by Volker Birk Feb. 10, 2013

Feb. 10, 2013

Hello, pyPEG 2.10 is a maintenance release. Now optional attributes are supported by the XML backend. There are several bugfixes. pyPEG 2 for Python 2.7 and 3.x Python is a nice scripting language. It even gives you access to its own parser and compiler. It also gives you access to different other parsers for special purposes like XML and string templates. But sometimes you may want to have your own parser. This is what's pyPEG for. And pyPEG supports Unicode. The source code for all you can find on bitbucket: https://bitbucket.org/fdik/pypeg/ To build the documentation, you'll need YML 2. You can download YML here: Homepage: http://fdik.org/yml/ Toolchain: http://fdik.org/yml2.tar.bz2 pyPEG 2 depends on lxml, see http://lxml.de/ Yours, VB. -- “Wer also seinen Anwendern Übles will, sollte unbedingt die Einführung von Windows 8 in Produktivumgebungen forcieren.” Susanne Nolte in der iX

1 0

ANN: NumPy 1.7.0 release
by Ondřej Čertík Feb. 9, 2013

Feb. 9, 2013

Hi, I'm pleased to announce the availability of the final release of NumPy 1.7.0. Sources and binary installers can be found at https://sourceforge.net/projects/numpy/files/NumPy/1.7.0/ This release is equivalent to the 1.7.0rc2 release, since no more problems were found. For release notes see below. I would like to thank everybody who contributed to this release. Cheers, Ondrej ========================= NumPy 1.7.0 Release Notes ========================= This release includes several new features as well as numerous bug fixes and refactorings. It supports Python 2.4 - 2.7 and 3.1 - 3.3 and is the last release that supports Python 2.4 - 2.5. Highlights ========== * ``where=`` parameter to ufuncs (allows the use of boolean arrays to choose where a computation should be done) * ``vectorize`` improvements (added 'excluded' and 'cache' keyword, general cleanup and bug fixes) * ``numpy.random.choice`` (random sample generating function) Compatibility notes =================== In a future version of numpy, the functions np.diag, np.diagonal, and the diagonal method of ndarrays will return a view onto the original array, instead of producing a copy as they do now. This makes a difference if you write to the array returned by any of these functions. To facilitate this transition, numpy 1.7 produces a FutureWarning if it detects that you may be attempting to write to such an array. See the documentation for np.diagonal for details. Similar to np.diagonal above, in a future version of numpy, indexing a record array by a list of field names will return a view onto the original array, instead of producing a copy as they do now. As with np.diagonal, numpy 1.7 produces a FutureWarning if it detects that you may be attempting to write to such an array. See the documentation for array indexing for details. In a future version of numpy, the default casting rule for UFunc out= parameters will be changed from 'unsafe' to 'same_kind'. (This also applies to in-place operations like a += b, which is equivalent to np.add(a, b, out=a).) Most usages which violate the 'same_kind' rule are likely bugs, so this change may expose previously undetected errors in projects that depend on NumPy. In this version of numpy, such usages will continue to succeed, but will raise a DeprecationWarning. Full-array boolean indexing has been optimized to use a different, optimized code path. This code path should produce the same results, but any feedback about changes to your code would be appreciated. Attempting to write to a read-only array (one with ``arr.flags.writeable`` set to ``False``) used to raise either a RuntimeError, ValueError, or TypeError inconsistently, depending on which code path was taken. It now consistently raises a ValueError. The <ufunc>.reduce functions evaluate some reductions in a different order than in previous versions of NumPy, generally providing higher performance. Because of the nature of floating-point arithmetic, this may subtly change some results, just as linking NumPy to a different BLAS implementations such as MKL can. If upgrading from 1.5, then generally in 1.6 and 1.7 there have been substantial code added and some code paths altered, particularly in the areas of type resolution and buffered iteration over universal functions. This might have an impact on your code particularly if you relied on accidental behavior in the past. New features ============ Reduction UFuncs Generalize axis= Parameter ------------------------------------------- Any ufunc.reduce function call, as well as other reductions like sum, prod, any, all, max and min support the ability to choose a subset of the axes to reduce over. Previously, one could say axis=None to mean all the axes or axis=# to pick a single axis. Now, one can also say axis=(#,#) to pick a list of axes for reduction. Reduction UFuncs New keepdims= Parameter ---------------------------------------- There is a new keepdims= parameter, which if set to True, doesn't throw away the reduction axes but instead sets them to have size one. When this option is set, the reduction result will broadcast correctly to the original operand which was reduced. Datetime support ---------------- .. note:: The datetime API is *experimental* in 1.7.0, and may undergo changes in future versions of NumPy. There have been a lot of fixes and enhancements to datetime64 compared to NumPy 1.6: * the parser is quite strict about only accepting ISO 8601 dates, with a few convenience extensions * converts between units correctly * datetime arithmetic works correctly * business day functionality (allows the datetime to be used in contexts where only certain days of the week are valid) The notes in `doc/source/reference/arrays.datetime.rst <https://github.com/numpy/numpy/blob/maintenance/1.7.x/doc/source/reference/…>`_ (also available in the online docs at `arrays.datetime.html <http://docs.scipy.org/doc/numpy/reference/arrays.datetime.html>`_) should be consulted for more details. Custom formatter for printing arrays ------------------------------------ See the new ``formatter`` parameter of the ``numpy.set_printoptions`` function. New function numpy.random.choice --------------------------------- A generic sampling function has been added which will generate samples from a given array-like. The samples can be with or without replacement, and with uniform or given non-uniform probabilities. New function isclose -------------------- Returns a boolean array where two arrays are element-wise equal within a tolerance. Both relative and absolute tolerance can be specified. Preliminary multi-dimensional support in the polynomial package --------------------------------------------------------------- Axis keywords have been added to the integration and differentiation functions and a tensor keyword was added to the evaluation functions. These additions allow multi-dimensional coefficient arrays to be used in those functions. New functions for evaluating 2-D and 3-D coefficient arrays on grids or sets of points were added together with 2-D and 3-D pseudo-Vandermonde matrices that can be used for fitting. Ability to pad rank-n arrays ---------------------------- A pad module containing functions for padding n-dimensional arrays has been added. The various private padding functions are exposed as options to a public 'pad' function. Example:: pad(a, 5, mode='mean') Current modes are ``constant``, ``edge``, ``linear_ramp``, ``maximum``, ``mean``, ``median``, ``minimum``, ``reflect``, ``symmetric``, ``wrap``, and ``<function>``. New argument to searchsorted ---------------------------- The function searchsorted now accepts a 'sorter' argument that is a permutation array that sorts the array to search. Build system ------------ Added experimental support for the AArch64 architecture. C API ----- New function ``PyArray_RequireWriteable`` provides a consistent interface for checking array writeability -- any C code which works with arrays whose WRITEABLE flag is not known to be True a priori, should make sure to call this function before writing. NumPy C Style Guide added (``doc/C_STYLE_GUIDE.rst.txt``). Changes ======= General ------- The function np.concatenate tries to match the layout of its input arrays. Previously, the layout did not follow any particular reason, and depended in an undesirable way on the particular axis chosen for concatenation. A bug was also fixed which silently allowed out of bounds axis arguments. The ufuncs logical_or, logical_and, and logical_not now follow Python's behavior with object arrays, instead of trying to call methods on the objects. For example the expression (3 and 'test') produces the string 'test', and now np.logical_and(np.array(3, 'O'), np.array('test', 'O')) produces 'test' as well. The ``.base`` attribute on ndarrays, which is used on views to ensure that the underlying array owning the memory is not deallocated prematurely, now collapses out references when you have a view-of-a-view. For example:: a = np.arange(10) b = a[1:] c = b[1:] In numpy 1.6, ``c.base`` is ``b``, and ``c.base.base`` is ``a``. In numpy 1.7, ``c.base`` is ``a``. To increase backwards compatibility for software which relies on the old behaviour of ``.base``, we only 'skip over' objects which have exactly the same type as the newly created view. This makes a difference if you use ``ndarray`` subclasses. For example, if we have a mix of ``ndarray`` and ``matrix`` objects which are all views on the same original ``ndarray``:: a = np.arange(10) b = np.asmatrix(a) c = b[0, 1:] d = c[0, 1:] then ``d.base`` will be ``b``. This is because ``d`` is a ``matrix`` object, and so the collapsing process only continues so long as it encounters other ``matrix`` objects. It considers ``c``, ``b``, and ``a`` in that order, and ``b`` is the last entry in that list which is a ``matrix`` object. Casting Rules ------------- Casting rules have undergone some changes in corner cases, due to the NA-related work. In particular for combinations of scalar+scalar: * the `longlong` type (`q`) now stays `longlong` for operations with any other number (`? b h i l q p B H I`), previously it was cast as `int_` (`l`). The `ulonglong` type (`Q`) now stays as `ulonglong` instead of `uint` (`L`). * the `timedelta64` type (`m`) can now be mixed with any integer type (`b h i l q p B H I L Q P`), previously it raised `TypeError`. For array + scalar, the above rules just broadcast except the case when the array and scalars are unsigned/signed integers, then the result gets converted to the array type (of possibly larger size) as illustrated by the following examples:: >>> (np.zeros((2,), dtype=np.uint8) + np.int16(257)).dtype dtype('uint16') >>> (np.zeros((2,), dtype=np.int8) + np.uint16(257)).dtype dtype('int16') >>> (np.zeros((2,), dtype=np.int16) + np.uint32(2**17)).dtype dtype('int32') Whether the size gets increased depends on the size of the scalar, for example:: >>> (np.zeros((2,), dtype=np.uint8) + np.int16(255)).dtype dtype('uint8') >>> (np.zeros((2,), dtype=np.uint8) + np.int16(256)).dtype dtype('uint16') Also a ``complex128`` scalar + ``float32`` array is cast to ``complex64``. In NumPy 1.7 the `datetime64` type (`M`) must be constructed by explicitly specifying the type as the second argument (e.g. ``np.datetime64(2000, 'Y')``). Deprecations ============ General ------- Specifying a custom string formatter with a `_format` array attribute is deprecated. The new `formatter` keyword in ``numpy.set_printoptions`` or ``numpy.array2string`` can be used instead. The deprecated imports in the polynomial package have been removed. ``concatenate`` now raises DepractionWarning for 1D arrays if ``axis != 0``. Versions of numpy < 1.7.0 ignored axis argument value for 1D arrays. We allow this for now, but in due course we will raise an error. C-API ----- Direct access to the fields of PyArrayObject* has been deprecated. Direct access has been recommended against for many releases. Expect similar deprecations for PyArray_Descr* and other core objects in the future as preparation for NumPy 2.0. The macros in old_defines.h are deprecated and will be removed in the next major release (>= 2.0). The sed script tools/replace_old_macros.sed can be used to replace these macros with the newer versions. You can test your code against the deprecated C API by #defining NPY_NO_DEPRECATED_API to the target version number, for example NPY_1_7_API_VERSION, before including any NumPy headers. The ``NPY_CHAR`` member of the ``NPY_TYPES`` enum is deprecated and will be removed in NumPy 1.8. See the discussion at `gh-2801 <https://github.com/numpy/numpy/issues/2801>`_ for more details. Checksums ========= 7b72cc17b6a9043f6d46af4e71cd3dbe release/installers/numpy-1.7.0-win32-superpack-python3.3.exe 4fa54e40b6a243416f0248123b6ec332 release/installers/numpy-1.7.0.tar.gz 9ef1688bb9f8deb058a8022b4788686c release/installers/numpy-1.7.0-win32-superpack-python2.7.exe 909fe47da05d2a35edd6909ba0152213 release/installers/numpy-1.7.0-win32-superpack-python3.2.exe 5d4318b722d0098f78b49c0030d47026 release/installers/numpy-1.7.0-win32-superpack-python2.6.exe 92b61d6f278a81cf9a5033b0c8e7b53e release/installers/numpy-1.7.0-win32-superpack-python3.1.exe 51d6f4f854cdca224fa56a327ad7c620 release/installers/numpy-1.7.0-win32-superpack-python2.5.exe ca27913c59393940e880fab420f985b4 release/installers/numpy-1.7.0.zip 3f20becbb80da09412d94815ad3b586b release/installers/numpy-1.7.0-py2.5-python.org-macosx10.3.dmg 600dfa4dab31db5dc2ed9655521cfa9e release/installers/numpy-1.7.0-py2.6-python.org-macosx10.3.dmg a907a37416163b3245a30cfd160506ab release/installers/numpy-1.7.0-py2.7-python.org-macosx10.3.dmg

1 0

[ANN] Leipzig Python User Group - Meeting, February 12, 2013, 08:00 p.m.
by Mike Müller Feb. 9, 2013

Feb. 9, 2013

=== Leipzig Python User Group === We will meet on Tuesday, February 12 at 8:00 p.m. at the training center of Python Academy in Leipzig, Germany ( http://www.python-academy.com/center/find.html ). Mike Müller (me ;)) will talk about IPython [1] and especially the new IPython notebook. IPython is a greatly enhanced alternative to the interactive Python prompt. The notebook allows to create interactive documents in a browser with markdown, Python code and matplotlib graphics. Even though IPython is traditionally only widely used among scientists, it offers interesting opportunities for all Python users. Everybody who uses Python, plans to do so or is interested in learning more about the language is encouraged to participate. While the meeting language will be mainly German, we will provide English translation if needed. Food and soft drinks are provided. Please send a short confirmation mail to info(a)python-academy.de, so we can prepare appropriately. Current information about the meetings are at http://www.python-academy.com/user-group . Mike == Leipzig Python User Group === Wir treffen uns am Dienstag, 12.02.2013 um 20:00 Uhr im Schulungszentrum der Python Academy in Leipzig ( http://www.python-academy.de/Schulungszentrum/anfahrt.html ). Mike Müller (das bin ich ;)) stellt IPython [1] und insbesondere das neue IPython-Notebook vor. IPython bietet eine stark erweiterte Alternative zum interaktiven Python-Prompt. Mit dem neuen Notebook lassen sich im Browser interaktive Dokumente mit Markdown, Python-Code und Matplotlib-Grafiken anlegen. Obwohl IPython vor allem im wissenschaftlichen Umfeld verbreitet ist, bietet es interessante Möglichkeiten für alle Python-Nutzer. Weitere Infos: http://www.python-academy.de/User-Group/index.html Willkommen ist jeder, der Interesse an Python hat, die Sprache bereits nutzt oder nutzen möchte. Für das leibliche Wohl wird gesorgt. Eine Anmeldung unter info(a)python-academy.de wäre nett, damit wir genug Essen besorgen können. Aktuelle Informationen zu den Treffen sind unter http://www.python-academy.de/User-Group zu finden. Viele Grüße Mike [1] http://ipython.org/

1 0

Updated Cygwin Package: python-2.7.3-1
by Jason Tishler Feb. 8, 2013

Feb. 8, 2013

New News: === ==== *** Cygwin has migrating from Python 2.6 to 2.7. *** I have updated the version of Python to 2.7.3-1. The tarballs should be available on a Cygwin mirror near you shortly. The following is the only change since the previous release: o promote from experimental to current Note that all Python dependent packages have been rebuilt against 2.7. I would like to thank Yaakov Selkowitz for managing the migration from Python 2.6 to 2.7. 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.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. *** CYGWIN-ANNOUNCE UNSUBSCRIBE INFO *** If you want to unsubscribe from the cygwin-announce mailing list, please use the automated form at: http://cygwin.com/lists.html#subscribe-unsubscribe If you need more information on unsubscribing, start reading here: http://sourceware.org/lists.html#unsubscribe-simple Please read *all* of the information on unsubscribing that is available starting at this URL. Jason

1 0

Karlsruhe (Germany) Python User Group, February 15th 2013, 7pm
by Jürgen A. Erhard Feb. 8, 2013

Feb. 8, 2013

The Karlsruhe Python User Group (KaPy) meets again. Friday, 2013-02-15 (February 15th) at 19:00 (7pm) in the rooms of Entropia eV (the local affiliate of the CCC). See http://entropia.de/wiki/Anfahrt on how to get there. For your calendars: meetings are held monthly, on the 3rd Friday. There's also a mailing list at https://lists.bl0rg.net/cgi-bin/mailman/listinfo/kapy.

1 0

PyCon Singapore 2013 Call for Proposals
by George Goh Feb. 7, 2013

Feb. 7, 2013

Hi, On behalf of the organizing committee of PyCon SG 2013, we are inviting for Proposals for Presentations and Tutorials for the 2013 PyCon Singapore Conference, to be held in Singapore from June 13 to 15, 2013. Presentation and Tutorial Submission detail can be found at https://pycon.sg/proposals/ And the submission deadline for both is April 1, 2013 For enquiries, pls direct them to conference(a)pycon.sg We look forward to receiving your proposals! And to a great conference this year. Best regards, George Goh PyCon SG 2013 Programme Committee Chair

1 0

numba 0.6.0
by mark florisson Feb. 5, 2013

Feb. 5, 2013

On behalf of the numba team I am pleased to announce a new version of Numba, 0.6. The release includes faster numerical codes, better type inference support, faster autojit dispatch, python 2.6 support and more. Download: http://pypi.python.org/pypi/numba/0.6.0 Documentation: http://numba.pydata.org/numba-doc/0.6/ Github: https://github.com/numba/numba Numba will be part of the next anaconda CE release 1.3.1, to be released tomorrow. Numba ====== Numba is an just-in-time specializing compiler for Python and NumPy code to LLVM for annotated functions (through decorators). It's goal is to seamlessly integrate with the Python scientific software stack and provide optimized native code and integration with native foreign languages. Dependencies: ============ * llvmpy 0.10.0 * meta (optional) * cython * numpy * LLVM 3.2 (3.1 might work but is not officially supported) Release notes: ============ * Python 2.6 support * Programmable typing * Allow users to add type inference for external code * Better NumPy type inference * outer, inner, dot, vdot, tensordot, nonzero, where, binary ufuncs + methods (reduce, accumulate, reduceat, outer) * Type based alias analysis * Support for strict aliasing * Much faster autojit dispatch when calling from Python * Faster numerical loops through data and stride pre-loading * Integral overflow and underflow checking for conversions from objects * Make Meta dependency optional Many thanks to everyone who contributed to this release! Dan Christensen Ilan Schnell Jon Riehl Lars Buitinck Mark Florisson Phillip Cloud Siu Kwan Lam Travis E. Oliphant Timo

1 0

[ANN] Python Ireland February Meetup
by Diarmuid Bourke Feb. 5, 2013

Feb. 5, 2013

Hi All, When: Wednesday Feb 13th @ 7pm Where: Engine Yard, 2nd Floor, 35 Barrow St, Dublin 4. http://goo.gl/maps/ySSGi Price: FREE! What's on: Michael Twomey, "A 30 minute quick start guide to monitoring and metrics" Level: Mostly beginner Description: - What is monitoring? What are metrics? Why do I care? - What quick and dirty things can you do now to improve your life? - What could you be aiming for long term? - A quick summary of a bunch of tools: - Graphite (and of course hostedgraphite.com) - OpenTSDB - New Relic - Pingdom - Tracelytics - Datadog - Log scraping Jakub Jarosz, "MongoDB, MongoKit & Python for data driven integration testing." Level: beginner Description: I will cover few use cases of using MongoDB in the integration testing process and show how we simplified tests using pytest and JenkinsCI. Darren Fitzpatrick, Lightning talk on "How to try to make a audio game with no knowledge of python what so ever". Looking forward to seeing everyone on the night. Hopefully there will be some new faces there too. Note: Remember to go up the outside fire-escape stairwell in order to get into the building. -- Diarmuid Bourke / diarmuidbourke(a)gmail.com ZenDoc / CTO dbourke(a)getzendoc.com Python Ireland / Chairperson diarmuid(a)python.ie

1 0

[ANN] Launcherposta 0.9
by Facundo Batista Feb. 3, 2013

Feb. 3, 2013

LauncherPosta is a launcher. A real launcher. One that lets you launch programs. This program puts an icon in the systray where you can have a fully configurable menu to launch the programs that you most use, only two clicks away, anytime. http://launcherposta.taniquetil.com.ar/imgs/title.png Page: http://launcherposta.taniquetil.com.ar/ Changes for this release: - Have a easy way to find installed applications when adding a new entry in the menu - Better error message when fail to start something - A man page is now provided - Other small improvements Easiest way to install it, the .deb: http://launchpad.net/launcherposta/trunk/0.9/+download/launcherposta-0.9.deb To be automatically updated, install the PPA: sudo add-apt-repository ppa:facundo/launcherposta sudo apt-get update sudo apt-get install launcherposta Also, you have the tarball: http://launchpad.net/launcherposta/trunk/0.9/+download/launcherposta-0.9.ta… Finally, for the same price, you can get it from PyPI: sudo easy_install launcherposta Enjoy it. -- . Facundo Blog: http://www.taniquetil.com.ar/plog/ PyAr: http://www.python.org/ar/ Twitter: @facundobatista

1 0

Pygments 1.6 released
by Georg Brandl Feb. 3, 2013

Feb. 3, 2013

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'm happy to announce the release of Pygments 1.6. Pygments is a generic syntax highlighter written in Python. Pygments 1.6 is another large release, with over 30 new languages or markups supported. Heavy thanks go to all the contributors of these lexers, and to all those who reported bugs and waited patiently for this release, and to Tim Hatch for his continuing contributions. Download it from <http://pypi.python.org/pypi/Pygments>, or look at the demonstration at <http://pygments.org/demo>. Enjoy, Georg -----BEGIN PGP SIGNATURE----- Version: GnuPG v2.0.19 (GNU/Linux) iEYEARECAAYFAlEOMPMACgkQN9GcIYhpnLBaLwCfT8Ucu+vQWpk346f0NRjN5ynI YPcAn2wahrIIhU/dkT5cdqHbbkvp+XBm =TFYm -----END PGP SIGNATURE-----

1 0