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Links to useful Python info, such as tutorials¶

General Python tutorials / skills¶

Good intoductory tutorials for learning Python.

  • Basic tutorial: http://docs.python.org/tutorial/
  • The archived Python mailing list
  • General (computational) programming tutes, focused around Python:
    • Rur-Ple: - An interactive tutorial about Python, based around programming a simple robot - looks fun!
    • Alan Gauld’s quick programming tutorial - http://www.freenetpages.co.uk/hp/alan.gauld/
  • Software Carpentry: http://software-carpentry.org/ (A good all-round intro to Software for scientists & engineers, but with a particular focus on Python)
  • S Lott’s Building Skills in Python - looks really good.
    • Includes a section on writing CSV, XML and other file formats.
  • Michael Foord’s Python Articles page - includes good articles on eg Testing, and Duck Typing in Python.
  • The book Python for Software Design - how to think like a Computer Scientist, (direct html link) has some good examples couched in general programmer skill training.

Tutorials particularly from the perspective of those with experience in Perl scripting, and Bash scripting:

  • Python and Perl tutorial: http://xahlee.org/perl-python/index.html - showing examples of how to do common tasks in both languages.
  • Red Hat Magazine’s “Python for Bash Scripters - a well-kept secret”

Tutorials more for the appropriate ‘software engineering’ in Python¶

  • Tutorial on making & managing distributable packages: http://guide.python-distribute.org/

Python libraries of interest for scientific analysis¶

Regarding these libraries, there is potential for their future integration into the standard CREDO toolbox - but for now users are free to download and experiment with them.

  • HDF5 analysis in Python: http://h5py.alfven.org/

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Table Of Contents

  • Links to useful Python info, such as tutorials
    • General Python tutorials / skills
    • Tutorials more for the appropriate ‘software engineering’ in Python
    • Python libraries of interest for scientific analysis

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