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• The starting point for all things Python is: http://python.org
• There are a large number of instructional videos available, follow this link for an example.
• A discussion of ways to write data objects to files

Packages for Python

In addition to a truly dizzying number of individual add-on libraries for Python, there are a few distributions of sets of python libraries that try to eliminate the hassle of pulling together lots of libraries. We should investigate these! 

Generally useful stuff

• NumPy is a really important add-on for Python. It provide low-level functions for handling arrays.
• SciPy is another really important add-on for Python. It's built on top of NumPy and provides higher-level (i.e., more user-friendly) functionality.
  • SciPy has a handy Cookbook of worked examples of common tasks
• Python is distributed with a large standard library of modules that support various tasks, but many more are available online. An extensive collection of pre-compiled libraries are available in this collection posted by Christoph Gohlke. Key libraries of interest to scientific computing include NumPy, SciPy, matplotlib, and netCDF4.

In addition to a truly dizzying number of individual add-on libraries for Python, there are a few distributions of sets of python libraries that try to eliminate the hassle of pulling together lots of libraries. We should investigate these!

• Enthought Python Distribution (EPD)
• UC-Irvine (unofficial) Windows-compiled libraries for Python - lots of hard-core computing options as individual libraries. Also offers a version of EPD.
• A version of the GDAL and OGR libraries is now available in Python, in a package called pypi.

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