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= Python Implementation of the Data Access Protocol = ## page was renamed from SummerOfCode
This page coordinates the [[http://code.google.com/soc/|Google "Summer of Code"]] projects involving Python and mentored by the Python Software Foundation (PSF).
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(Roberto Antonio Ferreira De Almeida) Based on previous years, we are expecting a lot of competition so when making your application it is important to note that the PSF is looking for projects that:
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The Data Access Protocol (DAP) is a data transmission protocol
designed specifically for science data. The protocol relies on the
widely used HTTP and MIME standards, and provides data types to
accommodate gridded data, relational data, and time series, as well as
allowing users to define their own data types. The initiative is
funded by NASA, and counts with the support of several
institutions. Hundreds of scientific datasets are available on the
internet through DAP servers, which can be accessed remotely by DAP
clients in a transparent and efficient way. Here I propose to develop
a Python implementation of the protocol based on its latest
specification. The proposed implementation will consist of a client
module that will allow Python applications to access remote datasets,
as well as a server for data stored in a variety of formats commonly
used by the scientific community, including NetCDF and Matlab files.		  * enhance an existing Python project rather than start something complete from scratch;
 * contribute to the Python community rather than are merely written in Python.
 
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== Outcome == The 2007 PSF SoC coordinator is JamesTauber (jtauber at jtauber dot com). Contact him if you have any questions.
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The proposal was completed as stated, and is already in use by some scientists. It can be used together with the Python-based CDAT tool or alone. = Students: How to submit a proposal =
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Mentor: Paul DuBois. Student applications are now open.

[[http://code.google.com/p/google-summer-of-code/wiki/AdviceforStudents|Google's Advice for Students]]

Looking at the list of PSF [[SummerOfCode/Mentors]] can help you craft your proposal to match their interests.

= Tips on participating =

   1. Do not overbook yourself. Working on your project should be your main activity for the entire summer.

   2. You must provide weekly status reports.

   1. Participate in the developer community by joining python-dev, jython-dev, or whatever mailing list is appropriate.

   1. If you get stuck, ask for help instead of silently struggling. You can ask your mentor for help, or post a question to the development mailing list.

   3. You will be expected to learn how to use SVN.
 
= Mentors: How to apply =

The mentor's responsibility is to ensure the student makes progress. This could entail coaching them, providing motivation, making sure they aren't stuck, answering technical questions, or pointing the student to the proper resources.

Mentors should expect to get a weekly status report from their students, and should badger students who are not communicating. The weekly status should be reported to the PSF SoC coordinator.

However, the mentor is not expected to do work for the student.

Mentoring duties are expected to take a couple of hours per week.

See [[http://code.google.com/p/google-summer-of-code/wiki/AdviceforMentors|Google's Advice for Mentors]]

If you are interested in becoming a mentor:

 * Add your name to the mentor list at [[SummerOfCode/Mentors]].
 * join the [[http://mail.python.org/mailman/listinfo/soc2007-mentors|soc2007-mentors mailing list]]
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= Bitten: A Python framework for collecting software metrics from automated builds = == Project ideas ==
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(Christopher Lenz) For 2007, the PSF would like to concentrate on proposals that
advance PSF projects (CPython and its documentation,
Jython and its documentation, the Python web site). That said, projects relating to other Python libraries, applications or implementations (PyPy) that are relevant to the promotion of the Python programming language are also encouraged.
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The goal of this work is to design and implement a distributed system for automated builds and continuous integration that allows the central collection and storage of software metrics generated during the build. The information collected this way needs to be structured and available in a machine-readable format, so that it can be analyzed, aggregated/correlated and presented after the build itself has completed. The following pages list some ideas:
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Mentors: Greg Wilson, Trent Mick.  * [[CodingProjectIdeas/PythonCore]] -- ideas for the CPython interpreter.
 * [[CodingProjectIdeas/StandardLibrary]]
 * https://www.drproject.org/DrProject/wiki/DrProjectSoC2007 -- DrProject ideas
 * http://wiki.python.org/jython/SummerOfCode -- Jython projects.
 * http://codespeak.net/pypy/dist/pypy/doc/project-ideas.html -- Some ideas for PyPy
 * http://code.google.com/p/sympy/wiki/SummerOfCode -- Ideas for SymPy
 * http://code.google.com/p/pyjamas/wiki/SummerOfCode -- Idea for Pyjamas
 * [[http://docutils.sourceforge.net/docs/dev/todo.html|The Docutils to-do list]] contains a wealth of ideas. Important projects are prioritized. Subscribe to the [[https://lists.sourceforge.net/lists/listinfo/docutils-develop|docutils-develop]] list and ask for advice.
 * http://webpy.infogami.com/ideas -- ideas for web.py
 * http://pyblosxom.sourceforge.net/blog/static/soc2007.html -- ideas for PyBlosxom
 * http://code.google.com/p/crunchy/wiki/SummerOfCodeIdeas -- ideas for Crunchy (educational software).
 * http://www.pysoy.org/wiki/SoC2007 -- ideas for PySoy (3d engine)
See also [[SummerOfCode/Mentors]] where potential mentors have mentioned projects they are willing to mentor.
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== Outcome == == Other Organizations using Python ==
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Lots of
good code, very good time management and prioritization, and he's
delivered a working system. (Lots still to be done, of course, but it's
up and running.) See http://bitten.cmlenz.net for details.		 If you can't find a well-suited PSF project, but you still want to do something with Python for SOC 2007, you can also consider the projects offered by:
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 * Bazaar (http://code.google.com/soc/bzr/about.html)
 * Django (http://code.google.com/soc/django/about.html)
 * Kamaelia, BBC Research (http://code.google.com/soc/bbc/about.html and http://kamaelia.sourceforge.net/SummerOfCode2007)
 * MoinMoin (see MoinMoin:GoogleSoc2007 )
 * Open Source Applications Foundation (http://code.google.com/soc/osaf/about.html)
 * Plone Foundation (http://code.google.com/soc/plone/about.html)
 * SCons (http://code.google.com/soc/scons/about.html and http://www.scons.org/wiki/GSoC2007)
 * Subversion (http://code.google.com/soc/svn/about.html)
 * The Space Telescope Science Institute (http://code.google.com/soc/stsci/about.html)
 * wxPython (http://code.google.com/soc/wxpython/about.html)
 * Zope Foundation (http://code.google.com/soc/zope/about.html)
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= OpenExVis - A Program Visualization Tool = All the mentoring organizations are listed here: http://code.google.com/soc/
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(Tero Kuusela) == Previous years ==
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The goal is to write, in Python, a functional program visualization
tool that can visualize Python code. With the visualization tool, one
can write a program and see the execution visualized to help
understanding how the program works. This is especially useful to
assist students learning how to program.

The project website, where you can also find the original proposal sent to
Google, is at http://openexvis.sourceforge.net/ and the progress during
Summer of Code is tracked in Tero's blog at http://www.teroajk.net/blog/ .

Mentor: David Ascher.


== Outcome ==

David says: The project successfully animates several Python program through instrumentation of the low-level hooks inside standard Python interpreters. The demonstration program works, and a screencast is avalable off of the project's home page for people who don't have access to a Linux machine with the required dependencies installed. The project needs more work before it can be useful in an educational context, and there are probably features & bug fixes needed, but the foundational bits seem good!


= Wax =

(Jason Gedge)

This project consists of updating the Wax library for Python. Code
will be updated, or even added, to further develop the Wax
library. Also, a primary focus will be that of documentation, which
Wax currently lacks.

Mentors: Hans Nowak

Result: many additions to Wax were released in these two months, including WaxRF (a system to load forms from XML, much like wxPython's XRC), a documentation viewing/generating tool, and a number of new controls. Some existing issues were also fixed (OverlaySizer, Wizard). More information at http://zephyrfalcon.org/weblog2/arch_e10_00810.html#e817.

= Data Serving/Collection Framework in Python/WSGI =

Ho Chun Wei, blog: http://cwho.blogspot.com/

A framework based on bulk data serving/collection via the
internet. Bulk data are in the form of files that could easily be
several hundred MB (not surveys or simple POST data).

The client has a file repository that it wishes to sync to the server
(a WSGI application). This server should be able to facilitate
transfer via a number of protocols, including HTTP file transfer, HTTP
form upload, FTP, Email.

This project is aimed not at yet another ad-hoc file transfer or p2p
file-sharing program but as a persistent production setup for
transferring data from data collection sites/areas to a server,
possibly via internet through different methods to get through strict
organizational firewalls and web admins.

Mentors: Ian Bicking

== Outcome ==

I'd consider the code a
solid beta. There's probably packaging and documentation work to be
done, but that's the kind of thing that only user experience feedback
will really accomplish well, IMHO. Also it's something where there's No
One Right Way (yet!) to distribute web applications, so it'll evolve in
time.

We changed projects at the start from his original proposal to something
we both found more interesting/useful, a WebDAV server. There were good
generic WebDAV tests already written (acceptance only, but picky
acceptance tests).

= Python Bayesian Network Toolbox =

(Elliot Cohen)

Understanding about Bayesian Belief Networks and use of them is
becoming more and more widespread. As understanding develops and
spreads out of the research community, there is greater and greater
need for a simple to use efficient open source Bayesian Network
Toolbox. Bayesian Networks have been used to study a wide array of
different areas including, ecological systems, medical diagnoses and
financial modeling, among others. Currently, tools to define and use
Bayesian Networks are limited to expensive closed source libraries or
open source libraries designed for too specific a domain. One package
that does support many varieties of Bayesian Networks is Kevin
Murphy's Full BNT, which supports both discrete and continuous
probability distributions in static and dynamic Bayesian Networks.

For (almost) daily updates please see http://elliotpbnt.blogspot.com.

Mentor: James Tauber

== Outcome ==

Elliot Cohen has done a great job with the Python Bayes Network
Toolbox. He will undoubtedly continue working on pbnt after the SoC but I've
encouraged him to get it ready for an initial release to get it out
to a wider audience.

I have high hopes that this package will be useful to people wanting
to do real work on Bayesian Network based inference and learning and
I'm excited that the existence of pbnt means Python becomes a natural
choice for this sort of work.

= Efficiently Analysing Data Polymorphism and Deducing Generics in Shedskin =

(Mark Dufour)

As part of my Master's Thesis, I am working on a Python-to-C++ compilation system, called Shedskin. Currently, it performs static type inference based on two techniques. The Cartesian Product Algorithm is used to handle parametric polymorphism (calling functions with different combinations of argument types); single-level class duplication, or 1CFA, is employed to handle data polymorphism (mostly polymorphic containers, such as list; in 1CFA, each allocation site gets its own class type, so we can analyze these (somewhat) precisely.) Run-time checks such as 'isinstance' are considered during inference. Further, short tuples are analyzed internally, which of course is especially important in case of Python.

Based on the statically determined type information, the compiler currently performs stack- and static pre-allocation (using a simple escape analysis, and the static call graph respectively) and unboxing. Further, it generates polymorphic inline caches or virtual calls when a singleton type set cannot be deduced.
 
Single-level class duplication is imprecise, because it only duplicates class types once for each allocation site, and allocation sites may be duplicated during analysis (as CPA possibly creates many templates for each function.) Extending it to N levels, or NCFA, would make the analysis terribly exponential and still not precise for deep polymorphism. For the summer of code, my main goal will be to efficiently and precisely handle data polymorphism up to arbitrary depths. I am currently looking into an iterative technique developed by John Plevyak. (Tiejun & Wang's technique is incomprehensible, and I don't see how the method used in Starkiller would work.) My other large goal will be to generate generics of appreciable complexity, based on the inferred types, i.e. to determine whether types may be uniformly parameterized, and to generate class and function templates. Finally, I will integrate an existing C++ garbage collector into the run-time system in order to clean up objects that could not be stack- or statically pre-allocated.

'''Result:''' Plevyak's method has been implemented. Function and class templates of arbitrary complexity are generated. The Boehm garbage collector has been integrated. In total about 2000 lines have been added during the SoC. 123 (all) unit tests compile correctly, among which 6 larger non-trivial programs of between 100 and 200 lines. These are analyzed in a few seconds on a fast cpu, and become 10-50 times faster after compilation. Mission accomplished! :)

([http://mail.python.org/pipermail/summerofcode/2005-September/000179.html Announcement of first release])

Mentors: Jeremy Hylton, Brett Cannon

= Mailbox modification =

(Gregory K. Johnson)

Web page: http://gkj.freeshell.org/soc

I intend to rewrite the Python library's mailbox module to support
mailbox modification. I will extend the module's API (e.g., mailboxes
will sport dictionary-like mapping) and enhance certain existing
functionality (e.g., message objects will maintain
mailbox-format-specific attributes). Full backward compatibility will
be maintained.

'''Result:''' The modified version of the mailbox module is in the nondist/ tree
of Python CVS (nondist/sandbox/mailbox). I think it's acceptable for inclusion in the standard library, and is now waiting for a second opinion from some other Python developer, to see if there's any disagreement. I expect this code will get into Python 2.5.

Mentor: Andrew Kuchling

= Interactive Python Notebooks =

Students:
  * Toni Alatalo, [http://an.org/programming], Documnet transformation functionality.
  * Tzanko Matev, graphical user interface.

Further details:
[http://www.scipy.org/wikis/featurerequests/NoteBook]

Original proposal: [http://ipython.scipy.org/google_soc/ipnb_google_soc.pdf].

Mentors: Fernando Perez and Robert Kern

== Outcome after the official work period ==

The students have successfully implemented a prototype of a GUI and the underlying machinery for document transformation. Currently the WXPython-based GUI accepts normal python code and the extended set of ipython commands, normal text (not #comments, but regular text processed as a separate entity) and embedded figures. The document transformation infrastructure (XML based) can render these files into LaTeX, HTML or PDF, including mathematical notation.

The code is still considered alpha quality, but the basics are in place. We are in the process (as of 9/8/05) of cleaning things up to allow early testers to download it and play with it. Those willing to test out of the raw Subversion repository can do so by checking out the nbshell component:

svn co http://ipython.scipy.org/svn/ipython/nbshell/trunk nbshell

which includes instructions on the other pieces needed.

Those interested in the following the development can do so either on the ipython-dev maling list, or by browsing the Trac pages for IPython at:

http://projects.scipy.org/ipython/ipython


= Porting _sre.c and arraymodule.c to Python =

(Niklaus Haldimann, Blog: http://ubique.ch/soc)

I would like to create a port of the standard library modules "_sre" and "array" to pure Python. This will benefit alternative Python implementations like PyPy, Jython and IronPython. These projects all have to provide their own implementations of standard library modules written in C if they're not available in pure Python.

Mentors: Armin Rigo, Samuele Pedroni

== Outcome ==

Niklaus Haldimann has done everything planned and more on writing a pure
Python implementation of the _sre (core of regular expressions) and
array modules (http://codespeak.net/svn/user/nik). In addition to the
base work, he made regular releases of the _sre module (three so far).
This is a drop-in replacement for the equivalent C modules; for example,
_sre.py could be used in projects that need to run on top of Python 2.3
or earlier, while using regexps that require the recursion-less approach
introduced in 2.4 and supported by _sre.py.

He has also integrated the modules with PyPy (he was present at two PyPy
sprints); in the case of the _sre module, he ported it to
"interpreter-level", which means that in addition to integration, he
made sure that the code is static enough to be automatically
translatable to good C code, like the rest of PyPy. This should give an
excellent write-once, translate-to-anything regular expression engine
that might also be used as the basis for a Jython or IronPython module
(or even back to a C extension module for CPython).


= Object-Oriented File System Virtualisation =

(Adam Kerz)

Create an object oriented model of a file system in Python that can be used to interface many different resource types (with appropriate implementations).

Mentor: Trent Mick.

= Wax GUI for Python =

(Abhishek Reddy)


Wax requires work on four broad fronts. Firstly, support for several
basic controls need to be added, some of which are listed
above. Secondly, the design of the whole module has to be reviewed,
particularly focusing on the initialisation. Thirdly, there are
teething problems with passing data between Wax and wxPython that must
be looked at. Fourthly, documentation, presently lacking, needs to be
written.

Mentor: Hans Nowak

Result: In spite of the promising proposal, no work (code or documentation) was delivered. After the first initial contact, I have not heard from this student, for reasons still unknown. (Mentor list and Chris DiBona were notified.)

= PyTrails =

(Jennifer Dozar)

I'm working on an extensible opensource engine for implementing
trail-style games such as [http://www.gamespot.com/gamespot/features/all/greatestgames/p-34.html Oregon Trail] or Amazon Trail. The primary
goal is to produce a quality edutainment title that can be used free
of cost. The secondary goal is to make it easy for other edutainment
trail games to be created. PyTrails will be Python based and uses
PyGame. The engine will allow following a branching map including
making stops to rest, hunt, or trade. Additional choices such as
shopping and fording rivers may be available at special points. Each
of these activities will be replacable in other trail games as to
allow for maximum flexibility.

Mentors: Cameron Laird, Andrew Kuchling

= mmpy -- A garbage collection tool kit in Python =

(Carl Friedrich Bolz)

The project aims at producing a framework for writing and
evaluating garbage collectors in Python. The interfaces to
the low level memory and to the object model will be general
enough to make it usable for a wide range of projects in
need for garbage collection as well as for teaching and
research purposes. It will be designed with flexibility and
modularity in mind to encourage component reuse. It aims a
being directly useful for the PyPy project and translatable
by its translation tools.


Mentors: Samuele Pedroni, Armin Rigo


= Memory Profiler =

(Nick Smallbone, blog: http://starship.python.net/crew/mwh/blog/nb.cgi/portal/nickblog)

I would like to apply to work over the summer on a Python memory
profiler, as listed at CodingProjectIdeas.

To see how much work is involved in this, I've put together a
prototype, which tries to enumerate all objects from a root,
calculating the size of each object it finds.

Mentors: Michael Hudson, Jeremy Hylton


= asyncIO =

(Vladimir Sukhoy)

The proposed goal is to bring cross-platform proactive I/O
capabilities to Python. That will enable whole new style of
application development with Python in cases when I/O is a bottleneck.

Library releases available from: http://developer.berlios.de/project/showfiles.php?group_id=4124

Mentor: Mark Hammond


= Profile Replacement =

(Floris Bruynooghe http://bruynooghe.blogspot.com)

[Original idea from ProfileReplacementProject page.]

The current profiler is not free according to the Debian Free Software Guidelines (http://bugs.debian.org/293932) and has been taken out of the main Debian distribution. This affects many users as the profiler is integrated into other programs such as ipython who lose functionality withouth the profiling available.

The aim is to write a wrapper for hotshot that will act as a drop in replacement for the profile module. hotshot was chosen as base since it is much better tested then any newly written code would be. Secondly an independed stats module will be written for hotshot so that loading of the data will be much faster. This module will then also have a 100% pstats compatible wrapper.

When this all gets completed and time is left over one of the things to investigate is weather it is possible to make hotshot thread aware.

The project is registered as pyprof on savannah.nongnu.org: http://savannah.nongnu.org/projects/pyprof

Mentor: Brett Cannon

= PythonModulePackaging =
(Vincenzo Di Massa)
'''(an ubuntu python SoC project)'''

See: http://udu.wiki.ubuntu.com/PythonModulePackaging

Create a mechanism for fully automated packaging of python modules based on an upstream release. Support different Python implementations and different versions of CPython (needed, when not all software can run with the latest/default python version when an Ubuntu release is going to happen).

Mentor:
Matthias Klose

Note: if a project is listed as having two mentors, the first mentor listed is the ''primary'' mentor, and the second one is the ''back-up'' mentor.		  * [[SummerOfCode/2005]]
 * [[SummerOfCode/2006]]

This page coordinates the Google "Summer of Code" projects involving Python and mentored by the Python Software Foundation (PSF).

Based on previous years, we are expecting a lot of competition so when making your application it is important to note that the PSF is looking for projects that:

  • enhance an existing Python project rather than start something complete from scratch;
  • contribute to the Python community rather than are merely written in Python.

The 2007 PSF SoC coordinator is JamesTauber (jtauber at jtauber dot com). Contact him if you have any questions.

Students: How to submit a proposal

Student applications are now open.

Google's Advice for Students

Looking at the list of PSF SummerOfCode/Mentors can help you craft your proposal to match their interests.

Tips on participating

  1. Do not overbook yourself. Working on your project should be your main activity for the entire summer.
  2. You must provide weekly status reports.
  3. Participate in the developer community by joining python-dev, jython-dev, or whatever mailing list is appropriate.
  4. If you get stuck, ask for help instead of silently struggling. You can ask your mentor for help, or post a question to the development mailing list.
  5. You will be expected to learn how to use SVN.

Mentors: How to apply

The mentor's responsibility is to ensure the student makes progress. This could entail coaching them, providing motivation, making sure they aren't stuck, answering technical questions, or pointing the student to the proper resources.

Mentors should expect to get a weekly status report from their students, and should badger students who are not communicating. The weekly status should be reported to the PSF SoC coordinator.

However, the mentor is not expected to do work for the student.

Mentoring duties are expected to take a couple of hours per week.

See Google's Advice for Mentors

If you are interested in becoming a mentor:

Project ideas

For 2007, the PSF would like to concentrate on proposals that advance PSF projects (CPython and its documentation, Jython and its documentation, the Python web site). That said, projects relating to other Python libraries, applications or implementations (PyPy) that are relevant to the promotion of the Python programming language are also encouraged.

The following pages list some ideas:

See also SummerOfCode/Mentors where potential mentors have mentioned projects they are willing to mentor.

Other Organizations using Python

If you can't find a well-suited PSF project, but you still want to do something with Python for SOC 2007, you can also consider the projects offered by:

All the mentoring organizations are listed here: http://code.google.com/soc/

Previous years

SummerOfCode/2007 (last edited 2008-11-15 14:00:01 by localhost)

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