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Pypar does not require the Python interpreter to be modified or recompiled: Parallel python programs use the standard Python and need merely import the pypar module. This means for example that you can upgrade Python independently of your parallel codes.

Pypar is an efficient but easy-to-use module that allows programs/scripts written in the Python programming language to run in parallel on multiple processors and communicate using message passing. Pypar provides bindings to an important subset of the message passing interface standard MPI. Other Python MPI bindings available from other developers include: PyMPI, Scientific Python and pythonMPI.

PyCHM - Python bindings for CHMLIB PyCHM is a package that provides bindings for Jed Wing's CHMLIB library. The chm package contains four modules, namely chm.chm, chm.chmlib, chm.extra and chm._chmlib. chm.chmlib is a low level wrapper module around the API provided by the C library chmlib. Quoted from Jed's README: chmlib is a small library designed for accessing MS ITSS files. The ITSS file format is used for Microsoft Html Help files (.chm), which have been the predominant medium for software documentation from Microsoft during the past several years, having superceded the previously used .hlp file format. chm.chm provides some high level functionality over chm.chmlib, such as access to the .chm file contents tree. chm.extra contains extra functionality to allow detection encodings in the CHM archives and to support full-text search.

What is Py++? Definition: Py++ is an object-oriented framework for creating a code generator for Boost.Python library. Py++ uses few different programming paradigms to help you to expose C++ declarations to Python. This code generator will not stand on your way. It will guide you through the whole process. It will raise warnings in the case you are doing something wrong with a link to the explanation. And the most important it will save your time - you will not have to update code generator script every time source code is changed.

GUESS is an exploratory data analysis and visualization tool for graphs and networks. The system contains a domain-specific embedded language called Gython (an extension of Python, or more specifically Jython) which supports the operators and syntactic sugar necessary for working on graph structures in an intuitive manner. An interactive interpreter binds the text that you type in the interpreter to the objects being visualized for more useful integration. GUESS also offers a visualization front end that supports the export of static images and dynamic movies

What idioms should I use to make my code easier to read? Read "The Python Cookbook", especially the first few chapters. It's a great source of well-written Python code examples.

Use function factories to create utility functions. Often, especially if you're using map and filter a lot, you need utility functions that convert other functions or methods to taking a single parameter. In particular, you often want to bind some data to the function once, and then apply it repeatedly to different objects. In the above example, we needed a function that multiplied a particular field of an object by 3, but what we really want is a factory that's able to return for any field name and amount a multiplier function in that family:

Use zip and dict to map fields to names. zip turns a pair of sequences into a list of tuples containing the first, second, etc. values from each sequence. For example, zip('abc', [1,2,3]) == [('a',1),('b',2),('c',3)]. You can use this to save a lot of typing when you have fields in a known order that you want to map to names: