I have spent most of today writing a response to the various reviewers about our extension to the NDG activities.

One of the reviewers asked: “Why python? Outside the computer science community, how well known is the language?”. These are actually common questions for me, as python isn’t really well established in the environmental sciences.

My answers are simple:

Why Python?:

  • Python is ridiculously easy to learn,
  • the code is easily maintainable
  • the code can be written very quickly …
  • we can self-train staff (rather than use expensive external courses, and/or hire expensive programmers without environmental science backgrounds)
  • has an enormous range of additional libraries,
  • is easy to extend using Pyfort/swig etc, to use our favourite high level codes.
  • has great cross-platform support
  • is free
  • there are already excellent toolkits out there like
    • http://esg.llnl.gov/cdat/CDAT: The Climate Data Analysis Tools
    • Scientific Python
    • matplotlib a python reproduction of matlab plotting capability.
  • Numarray and Numeric provide excellent support for doing real calculations

Not to mention the “good programming aspects” that plenty of others can comment on better than me.

Is it used outside of Computer Science?

  • Astronomy (e.g. the space telescope science institute and PYRAF)
  • High Energy Physics (e.g. SLAC)
  • Quantum Chemistry (e.g. pyquante)
  • Computational Biochemistry (e.g. biopython)

For all of these reasons, within NCAS, we at BADC have decided to try and support the wider community with free python tools, so that they can make the best use of data products from our scientific research.