I enjoy python because of its scripty-ness, lightweight status in the terminal, and ease with regular expressions.
To illustrate my familiarity with Python, I've chosen two examples of my work. The first is a group project parsing unstructured text files containing the text of New York Times recipe columns from the 1980s. The second is an introduction to interacting with APIs through python that I presented to a class learning about data and the media arts.
This is a project from Mark Hansen's Statistics Programming course. The goal was to create a python script that would strip ingredients and instructions out of a series of relatively unstructured .sgml files containing the raw text of five years worth of New York Times recipe columns.
This was a group project, so not everything contained is my own original work. However, I helped to write the basic framework of the code, put together a lot of the distinct pieces, and did the bulk of debugging. Finally, wrote the code to save the output files and converted the entire script to an executable, rather than code that had to be copy-pasted every time.
It should be noted that this was such a hard problem that when Mark actually needed parsed recipe files, he turned to Amazon's Mechanical Turk for a human solution, rather than writing a script such as the one we tried to create.
For another of Mark's courses, Data and the Media Arts, I was tasked with introducing the class into the use of APIs through python using the examples of Twitter and Facebook. This code snippet is essentially my presentation, a getting-started introduction to installing the appropriate modules and doing the initial playing around that could lead to inspiration.