I am an avid user and fan of the Python programming language, which is modern, open-source, object oriented, well documented, powerful, and with elegant syntax. I use the iPython environment and rely on the numpy, scipy, matplotlib, and netcdf4-python modules to analyze climate model data via the free educational version of the Enthought Canopy Python distribution.
I highly recommend Python to anybody in science and intend to provide additional helpful Python resources here in the future.
aospy Python module
My classmates and I often lament how much time we spend messing with computer code in order to output data or figures. Also, lacking sufficient metadata to describe what they actually do/are, scripts/plots quickly become outdated and untrustworthy (e. g. "Did I remember to change the output variable in the script when I made this plot?"). In addition, creating plots one by one can be impractical when dozens of plots are needed (e.g. DJF, JJA, SON, MAM, and annual mean plots of multiple variables from multiple experimental runs and/or multiple models and/or multiple ensemble members).
This frustrating inefficiency has led me to create a Python module that automate these tasks. Dubbed "aospy", it's aim is to, given some dataset, perform all frequently used calculations, create plots, and store all results and metadata conveniently. And do this all with minimal input by the user.
Eventually I would like to place it on Github for free use by anybody. Until that day comes, please contact me if you'd like to hear more or see some of the code.