Mailman 3 February 2015 - Python-announce-list

ANN: Bokeh 0.8.1 released
by Damian Avila 23 Feb '15

23 Feb '15

Hi all, We are excited to announce the release of version 0.8.1 of Bokeh, an interactive web plotting library for Python... and other languages! This minor release includes many bug fixes and docs improvements: * Fixed HoverTool * Fixed Abstract Rendering implementation and docs * Fixed Charts gallery and docs * Removed leftovers from the old plotting API implementation * Some other minor docs fixes See the CHANGELOG for full details. If you are using Anaconda/minoconda, you can install with conda: conda install bokeh Alternatively, you can install with pip: pip install bokeh Developer builds are also now made available to get features in the hands of interested users more quickly. See the Developer Builds <http://bokeh.pydata.org/en/latest/docs/installation.html#developer-builds> section in the documentation for more details. BokehJS is also available by CDN for use in standalone Javascript applications: * http://cdn.pydata.org/bokeh/release/bokeh-0.8.1.min.js * http://cdn.pydata.org/bokeh/release/bokeh-0.8.1.min.css Finally, BokehJS is also installable with the Node Package Manager at https://www.npmjs.com/package/bokehjs Issues, enhancement requests, and pull requests can be made on the Bokeh Github page: https://github.com/bokeh/bokeh Questions can be directed to the Bokeh mailing list: bokeh(a)continuum.io Cheers! -- *Damián Avila* *Continuum Analytics* *damian.avila(a)continuum.io <damian.avila(a)continuum.io>*

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ANN Nanpy 0.9.3 released
by Andrea Stagi 21 Feb '15

21 Feb '15

Hi, Nanpy 0.9.3 is out! https://pypi.python.org/pypi/nanpy/0.9.3. This release includes a new firmware (fragmentation memory problem is now history, yay! ) and lot of bug fixing on the python side! Arduino module is deprecated in favour of ArduinoApi. Nanpy is an open source project, you can follow our work at https://github.com/nanpy With Nanpy you can use your Arduino board with Python from any device, Raspberry Pi included! a = ArduinoApi() a.pinMode(13, a.OUTPUT) a.digitalWrite(13, a.HIGH) We support OneWire, Lcd, Stepper, Servo, DallasTemperature and many more… Let’s try to connect our 16x2 lcd screen on pins 7, 8, 9, 10, 11, 12 and show your first “Hello world”! from nanpy import Lcd lcd = Lcd([7, 8, 9, 10, 11, 12], [16, 2]) lcd.printString('Hello World!') -- Andrea Stagi (@4stagi) - Develover @Nephila Job profile: http://linkedin.com/in/andreastagi Website: http://4spills.blogspot.it/ Github: http://github.com/astagi

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ANN: SciPy Latin América 2015 - Call for Proposals
by Damián Avila 20 Feb '15

20 Feb '15

*Call for Proposals* *SciPy Latin América 2015*, the third annual Scientific Computing with Python Conference, will be held this *May 20-22* in *Posadas, Misiones, Argentina*. SciPy is a community dedicated to the advancement of scientific computing through open source Python software for mathematics, science, and engineering. The annual SciPy Conferences allows participants from academic, commercial, and governmental organizations to showcase their latest projects, learn from skilled users and developers, and collaborate on code development. *Proposals are now being accepted for SciPy Latin América 2015*. Presentation content can be at a novice, intermediate or advanced level. Talks will run 30-40 min and hands-on tutorials will run 100-120 min. We also receive proposal for posters. For more information about the different types of proposal, see below the "*Different types of Communication*" section. *How to Submit?* 1. Register for an account on http://conf.scipyla.org/user/register 2. Submit your proposal at http://conf.scipyla.org/activity/propose *Important Dates* - *April 6th*: Talks, poster, tutorial submission deadline. - *April 20th*: Notification Talks / Posters / Tutorial accepted. - *May 20th-22nd*: SciPy Latin América 2015. *Different types of Communication* *Talks*: These are the traditional talk sessions given during the main conference days. They're mostly 30 minutes long with 5 min for questions. If you think you have a topic but aren't sure how to propose it, contact our program committee and we'll work with you. We'd love to help you come up with a great proposal. *Tutorials*: We are looking for tutorials that can grow this community at any level. We aim for tutorials that will advance Scientific Python, advance this community, and shape the future. They're are 100-120 minutes long, but if you think you need more than one slot, you can split the content and submit two self-contained proposals. *Posters*: The poster session provides a more interactive, attendee-driven presentation than the speaker-driven conference talks. Poster presentations have fostered extensive discussions on the topics, with many that have gone on much longer than the actual "session" called for. The idea is to present your topic on poster board and as attendees mingle through the rows, they find your topic, read through what you've written, then strike up a discussion on it. It's as simple as that. You could be doing Q&A in the first minute of the session with a group of 10 people. *Lightning Talks*: Want to give a talk, but do not have enough material for a full talk? These talks are, at max, 5 minute talks done in quick succession in the main hall. No need to fill the whole slot, though! -- *The SciPy LA 2015 Program **Committee*

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ANN: SciPy Latin América 2015 - Call for Proposals
by Damián Avila 20 Feb '15

20 Feb '15

*Call for Proposals* *SciPy Latin América 2015*, the third annual Scientific Computing with Python Conference, will be held this *May 20-22* in *Posadas, Misiones, Argentina*. SciPy is a community dedicated to the advancement of scientific computing through open source Python software for mathematics, science, and engineering. The annual SciPy Conferences allows participants from academic, commercial, and governmental organizations to showcase their latest projects, learn from skilled users and developers, and collaborate on code development. *Proposals are now being accepted for SciPy Latin América 2015*. Presentation content can be at a novice, intermediate or advanced level. Talks will run 30-40 min and hands-on tutorials will run 100-120 min. We also receive proposal for posters. For more information about the different types of proposal, see below the "*Different types of Communication*" section. *How to Submit?* 1. Register for an account on http://conf.scipyla.org/user/register 2. Submit your proposal at http://conf.scipyla.org/activity/propose *Important Dates* - *April 6th*: Talks, poster, tutorial submission deadline. - *April 20th*: Notification Talks / Posters / Tutorial accepted. - *May 20th-22nd*: SciPy Latin América 2015. *Different types of Communication* *Talks*: These are the traditional talk sessions given during the main conference days. They're mostly 30 minutes long with 5 min for questions. If you think you have a topic but aren't sure how to propose it, contact our program committee and we'll work with you. We'd love to help you come up with a great proposal. *Tutorials*: We are looking for tutorials that can grow this community at any level. We aim for tutorials that will advance Scientific Python, advance this community, and shape the future. They're are 100-120 minutes long, but if you think you need more than one slot, you can split the content and submit two self-contained proposals. *Posters*: The poster session provides a more interactive, attendee-driven presentation than the speaker-driven conference talks. Poster presentations have fostered extensive discussions on the topics, with many that have gone on much longer than the actual "session" called for. The idea is to present your topic on poster board and as attendees mingle through the rows, they find your topic, read through what you've written, then strike up a discussion on it. It's as simple as that. You could be doing Q&A in the first minute of the session with a group of 10 people. *Lightning Talks*: Want to give a talk, but do not have enough material for a full talk? These talks are, at max, 5 minute talks done in quick succession in the main hall. No need to fill the whole slot, though! -- *The SciPy LA 2015 Program **Committee*

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ANN: Astropy v1.0 released
by Thomas Robitaille 19 Feb '15

19 Feb '15

Dear colleagues, We are very happy to announce the fourth major public release (v1.0) of the astropy package, a core Python package for Astronomy: http://www.astropy.org Astropy is a community-driven Python package intended to contain much of the core functionality and common tools needed for astronomy and astrophysics. New and improved major functionality in this release includes: * Support for Altitude/Azimuth and Galactocentric coordinates in astropy.coordinates * A new astropy.visualization sub-package * A new astropy.analytic_functions sub-package * Compound models in astropy.modeling may now be created using arithmetic expressions, and the resulting models support fitting. * Significantly faster C-based readers/writers for astropy.io.ascii * Support for a new enhanced CSV ASCII table format * A refactored Table class with improved performance when adding/removing columns * Support for using Time, Quantity, or SkyCoord arrays as Table columns In addition, hundreds of smaller improvements and fixes have been made. An overview of the changes is provided at: http://docs.astropy.org/en/stable/whatsnew/1.0.html Astropy v1.0 is a special release that we are denoting a Long Term Support (LTS) release, which means that we will be supporting it with bug fixes for the next two years, rather than the usual six months. More information about this can be found at the link above. Instructions for installing Astropy are provided on our website, and extensive documentation can be found at: http://docs.astropy.org In particular, if you use the Anaconda Python Distribution, you can update to v1.0 with: conda update astropy Whereas if you usually use pip, you can do: pip install astropy --upgrade Please report any issues, or request new features via our GitHub repository: https://github.com/astropy/astropy/issues Over 122 developers have contributed code to Astropy so far, and you can find out more about the team behind Astropy here: http://www.astropy.org/team.html If you use Astropy directly for your work, or as a dependency to another package, please remember to include the following acknowledgment at the end of papers: """ This research made use of Astropy, a community-developed core Python package for Astronomy (Astropy Collaboration, 2013). """ where (Astropy Collaboration, 2013) is a reference to the Astropy paper: http://dx.doi.org/10.1051/0004-6361/201322068 Please feel free to forward this announcement to anyone you think might be interested in this release. We hope that you enjoy using Astropy as much as we enjoyed developing it! Thomas Robitaille, Erik Tollerud, and Perry Greenfield on behalf of The Astropy Collaboration

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ANN: Bokeh 0.8 released
by Bryan Van de Ven 17 Feb '15

17 Feb '15

Hi all, We are excited to announce the release of version 0.8 of Bokeh, an interactive web plotting library for Python... and other languages! This release includes many major new features: * New and updated language bindings: R, JavaScript, Julia, Scala, and Lua now available * More bokeh-server features geared towards production deployments * Live gallery of server examples and apps! * Simpler, more easily extensible design for charts API, plus new Horizon chart * New build automation and substantial documentation improvements * Shaded grid bands, configurable hover tool, and pan/zoom for categorical plots * Improved and more robust crossfilter application * AjaxDataSource for clients to stream data without a Bokeh server In addition, many smaller bugfixes and features, both old and new---over 100 issues---were closed for this release! See the CHANGELOG for full details. Perhaps the biggest news of this release is the long awaited arrival of rbokeh (https://github.com/bokeh/rbokeh), which brings native bindings for Bokeh to the R language. You see more details and examples about the release at: http://continuum.io/blog/bokeh-0.8 If you are using Anaconda, you can install with conda: conda install bokeh Alternatively, you can install with pip: pip install bokeh Developer builds are also now made available to get features in the hands of interested users more quickly. See the Developer Builds section in the documentation for more details. BokehJS is also available by CDN for use in standalone Javascript applications: * http://cdn.pydata.org/bokeh/release/bokeh-0.8.0.min.js * http://cdn.pydata.org/bokeh/release/bokeh-0.8.0.min.css Please note that the file layout on CDN has changed slightly (however all older releases will always be available at their original locations). Finally, BokehJS is also installable with the Node Package Manager Issues, enhancement requests, and pull requests can be made on the Bokeh Github page: https://github.com/bokeh/bokeh Questions can be directed to the Bokeh mailing list: bokeh(a)continuum.io Thank you for your attention! Bryan Van de Ven Continuum Analytics bryanv(a)continuum.io

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Wiring 0.2.0 - Dependency Injection and Interfaces for Python
by Mikołaj Siedlarek 17 Feb '15

17 Feb '15

I'd like to announce Wiring 0.2.0, the very first public release of the library, which is meant to be a modern alternative to the Zope stack. What is Wiring? --------------- Wiring provides architectural foundation for Python applications, featuring: * dependency injection * interface definition and validation * modular component configuration * small, extremely pedantic codebase Wiring is supported and tested on Python 2.7, Python 3.3, Python 3.4, PyPy and PyPy 3. Read more and see some code at: http://wiring.readthedocs.org/ Links ----- * Documentation: http://wiring.readthedocs.org/ * Repository: https://github.com/msiedlarek/wiring * PyPi: https://pypi.python.org/pypi/wiring -- Mikolaj Siedlarek mikolaj(a)siedlarek.pl

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[ANN] jsonrpclib-pelix 0.2.4
by Thomas Calmant 17 Feb '15

17 Feb '15

====================== jsonrpclib-pelix 0.2.4 ====================== jsonrpclib-pelix 0.2.4 has just been released ! What is it ? ------------ This library is an implementation of the JSON-RPC specification, for Python 2.6+ and 3.x. It supports both the original 1.0 specification, as well as the 2.0 specification, which includes batch submission, keyword arguments, etc. It is licensed under the Apache Software License 2.0 ( http://www.apache.org/licenses/LICENSE-2.0.html). The source code is available on Github: https://github.com/tcalmant/jsonrpclib This library can be installed using pip or easy_install: pip install --upgrade jsonrpclib-pelix easy_install -U jsonrpclib-pelix What's new in 0.2.4 ? --------------------- This version: * Corrects the handling of reused request sockets on the server side. * Corrects the additional_header feature: now supports different headers for different proxies * Adds support for a custom "data" field in error responses. Enjoy!

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ffnet-0.8.0 released
by Marek Wojciechowski 16 Feb '15

16 Feb '15

ffnet-0.8.0 has been released. ffnet is a fast and easy-to-use feed-forward neural network training solution for python This version supports python 3. Look at ffnet website: http://ffnet.sourceforge.net for installation instructions and documentation. Regards, -- Marek Wojciechowski --- Politechnika Łódzka Lodz University of Technology Treść tej wiadomości zawiera informacje przeznaczone tylko dla adresata. Jeżeli nie jesteście Państwo jej adresatem, bądź otrzymaliście ją przez pomyłkę prosimy o powiadomienie o tym nadawcy oraz trwałe jej usunięcie. This email contains information intended solely for the use of the individual to whom it is addressed. If you are not the intended recipient or if you have received this message in error, please notify the sender and delete it from your system.

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apipkg 1.3 released
by Ronny Pfannschmidt 15 Feb '15

15 Feb '15

Hello, i pleased to annouce the release of apipkg 1.3. Welcome to apipkg! ------------------------ With apipkg you can control the exported namespace of a python package and greatly reduce the number of imports for your users. It is a `small pure python module`_ that works on virtually all Python versions, including CPython2.3 to Python3.1, Jython and PyPy. It co-operates well with Python's ``help()`` system, custom importers (PEP302) and common command line completion tools. Usage is very simple: you can require 'apipkg' as a dependency or you can copy paste the <200 Lines of code into your project. As extra it will automatically set package.__version__ to your distribution version. Tutorial example ------------------- Here is a simple ``mypkg`` package that specifies one namespace and exports two objects imported from different modules:: # mypkg/__init__.py import apipkg apipkg.initpkg(__name__, { 'path': { 'Class1': "_mypkg.somemodule:Class1", 'clsattr': "_mypkg.othermodule:Class2.attr", } } The package is initialized with a dictionary as namespace. You need to create a ``_mypkg`` package with a ``somemodule.py`` and ``othermodule.py`` containing the respective classes. The ``_mypkg`` is not special - it's a completely regular python package. Namespace dictionaries contain ``name: value`` mappings where the value may be another namespace dictionary or a string specifying an import location. On accessing an namespace attribute an import will be performed:: >>> import mypkg >>> mypkg.path <ApiModule 'mypkg.path'> >>> mypkg.path.Class1 # '_mypkg.somemodule' gets imported now <class _mypkg.somemodule.Class1 at 0xb7d428fc> >>> mypkg.path.clsattr # '_mypkg.othermodule' gets imported now 4 # the value of _mypkg.othermodule.Class2.attr The ``mypkg.path`` namespace and its two entries are loaded when they are accessed. This means: * lazy loading - only what is actually needed is ever loaded * only the root "mypkg" ever needs to be imported to get access to the complete functionality. * the underlying modules are also accessible, for example:: from mypkg.sub import Class1 Including apipkg in your package -------------------------------------- If you don't want to add an ``apipkg`` dependency to your package you can copy the `apipkg.py`_ file somewhere to your own package, for example ``_mypkg/apipkg.py`` in the above example. You then import the ``initpkg`` function from that new place and are good to go. .. _`small pure python module`: .. _`apipkg.py`: http://bitbucket.org/hpk42/apipkg/src/tip/apipkg.py Feedback? ----------------------- If you have questions you are welcome to * join the #pylib channel on irc.freenode.net * subscribe to the http://codespeak.net/mailman/listinfo/py-dev list. * create an issue on http://bitbucket.org/hpk42/apipkg/issues 1.3 ---------------------------------------- - fix issue2 - adapt tests on Jython - handle jython __pkgpath__ missabstraction when running python from jar files - alias modules pointing to unimportable modules will return None for all their attributes instead of raising ImportError. This addresses python3.4 where any call to getframeinfo() can choke on sys.modules contents if pytest is not installed (because py.test.* imports it). - introduce apipkg.distribution_version(name) as helper to obtain the current version number of a package from install metadata its used by default with the package name - add an eagerloading option and eagerload automatically if bpython is used (workaround for their monkeypatching) -- Ronny

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