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Python in Maya Done RightPymel makes python scripting with Maya work the way it should. Maya's command module is a direct translation of mel commands into python commands. The result is a very awkward and unpythonic syntax which does not take advantage of python's strengths -- particulary, a flexible, object-oriented design. Pymel builds on the cmds module by organizing many of its commands into a class hierarchy, and by customizing them to operate in a more succinct and intuitive way. Powerful new classes

The pyparsing module is an alternative approach to creating and executing simple grammars, vs. the traditional lex/yacc approach, or the use of regular expressions. The pyparsing module provides a library of classes that client code uses to construct the grammar directly in Python code.

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which have been the predominant medium for software documentation from Microsoft during the past several years, having superceded the previously used .hlp file format.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.

sychotic is an innovative optimizing compiler for Python code. It has unique features, the most important of which is that it breaks through the ConstantTimeBarrier. It is very easy to use and has an interface similar to that of the popular Psyco project. Below, you can see a usage example. You can also learn about HowItWorks, the ProjectHistory and KnownIssues. You can also browse the easy-to-understand source especially the alysis.py analyzer module and the dingo.py runtime bootstrap. There is an introductory screencast available (less than 5 minutes long). Usage

ProfitPy is a set of libraries and tools for the development, testing, and execution of automated stock trading systems Specifically, ProfitPy is a collection of Python packages, modules, and scripts that work together to help you implement an automated stock trading program (or programs). The package features: A library with classes for accounts, orders, tickers, and more A GUI program for executing and plotting trades in real-time A GUI tool to collect ticker data for off-line use A CLI tool to back-test trading strategies Dozens of technical indicators and plotting widgets to display them An X11 keystroke tool for automating the TWS application

PyACTS- http://www.pyacts.org -- PyACTS is a collection of Python Modules that are very useful to Parallel Computing in a High Performance Computing environment. This packages incorporates several modules like PyBLACS (allows communication data for Linear Algebra), PyPBLAS (distributed Matrix Operations) and PyScaLAPACK (solve linear systems and get the eigenvalue problems). These libraries are part of PyACTS project that provide interfaces to the ACTS Collection. Also is provided a parrallel interpreter for using this package that implements message-based parallel programming using MPI.

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.

""" a class for generating permutations from an array # choose 2 letters from 'abcd' c = Chooser(['a', 'b', 'c', 'd'], 2) while c.hasMoreElements(): print c.next() """ import time, copy class NoMoreChoices(StandardError): pass class Chooser:

In short: run your existing Python software much faster, with no change in your source. Think of Psyco as a kind of just-in-time (JIT) compiler, a little bit like what exists for other languages, that emit machine code on the fly instead of interpreting your Python program step by step. The difference with the traditional approach to JIT compilers is that Psyco writes several version of the same blocks (a block is a bit of a function), which are optimized by being specialized to some kinds of variables (a "kind" can mean a type, but it is more general). The result is that your unmodified Python programs run faster. Benefits 2x to 100x speed-ups, typically 4x, with an unmodified Python interpreter and unmodified source code, just a dynamically loadable C extension module. Drawbacks Psyco currently uses a lot of memory. It only runs on Intel 386-compatible processors (under any OS) right now. There are some subtle semantic differences (i.e. bugs) with the way Python works; they should not be apparent in most programs.

Python library for arbitrary-precision floating-point arithmetic

aspects.py library provides means to intercept function calls. Functions and methods (also in Python standard library and third party code) can be wrapped so that when they are called, the wrap is invoked first. Depending on the wrap, the execution of the original function can be omitted, or the function can be called arbitrarily many times. Wraps are able to modify the arguments and the return value of the original function. In the terminology of aspect-oriented programming, the library allows applying advices (wraps) to call join points of methods and functions in around fashion.