I was more productive at the end of the first day using Python to parse SAX than I was after 5 years as being senior dev using C++Anyway, he has a blog post about his talk, with the slides and links to further material. The source is at github: get it by doing
git clone git://github.com/ianozsvald/HighPerformancePython_PyCon2012.gitThe first sort of case review he gives is converting old Fortran Xray diffraction code to Python/Cython, and then optimizing the Python in the first day getting an order of magnitude speedup. Further optimization was done using other tools, getting to a final speedup of 300 on the pure Python numpy code.
As with all performance tuning, the key is profiling the code to understand exactly where the code spends its time.