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StatPy: Statistical Computing with Python Welcome to StatPy, a collection of resources to help you do statistical computing with Python, with a special emphasis on astrostatistics (statistics in astronomy). This web site is brand-spanking-new, and still very much under construction; please be patient with our "dust" and check back again frequently as building continues.

Epydoc is a tool for generating API documentation for Python modules, based on their docstrings. For an example of epydoc's output, see the API documentation for epydoc itself (html, pdf). A lightweight markup language called epytext can be used to format docstrings, and to add information about specific fields, such as parameters and instance variables. Epydoc also understands docstrings written in reStructuredText, Javadoc, and plaintext. For a more extensive example of epydoc's output, see the API documentation for Python 2.5.

Sometimes you get an Excel spreadsheet (say, from the marketing departement) and you want to read tabular data from it (i.e. a line with column headers and lines of data). There are many ways to do this (including ODBC + mxODBC), but the easiest way I've found is this one : provide a file name and a sheet name, and read the data !

Pyro is short for PYthon Remote Objects. It is an advanced and powerful Distributed Object Technology system written entirely in Python, that is designed to be very easy to use. Never worry about writing network communication code again, when using Pyro you just write your Python objects like you would normally. With only a few lines of extra code, Pyro takes care of the network communication between your objects once you split them over different machines on the network. All the gory socket programming details are taken care of, you just call a method on a remote object as if it were a local object!