Yesterday I attended a biweekly meeting of an informal a UC Berkeley group devoted to Python in science (Py4Science), organized by Fernando Perez. The format (in honor of my visit) was a series of 4-minute lightning talks about various projects using Python in the scientific world (at Berkeley and elsewhere) followed by an hourlong Q&A session. This meant I didn't have to do a presentation and still got to interact with the audience for an hour -- my ideal format.
I was blown away by the wide variety of Python use for scientific work. It looks like Python (with extensions like numpy) is becoming a standard tool for many sciences that need to process large amounts of data, from neuroimaging to astronomy.
Here is a list of the topics presented. All these describing Python software; I've added names insofar they were present on the slides. Most projects are easily found by Googling for them, so I have not included hyperlinks except in some cases where the slides emphasized them.
Fernando gave an overview of the core Python software used throughout scientific comput