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There are two applications that require using the NumPy array type in C extension modules: Access to numerical libraries: Extension modules can be used to make numerical libraries written in C (or languages linkable to C, such as Fortran) accessible to Python programs. The NumPy array type has the advantage of using the same data layout as arrays in C and Fortran. Mixed-language numerical code: In most numerical applications, only a small part of the total code is CPU time intensive. Only this part should thus be written in C, the rest can be written in Python. NumPy arrays are important for the interface between these two parts, because they provide equally simple access to their contents from Python and from C. This document is a tutorial for using NumPy arrays in C extensions.

""" 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:

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.

Generating Excel 97+ files with Python 2.4+ (need decorators), importing Excel 95+ files, support for UNICODE in Excel files, using variety of formatting features and printing options, Excel files and OLE2 compound files dumper. No need in Windows/COM

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