Python is quick and easy to code, but can be slow when doing intensive numerical operations. Translating code to Cython can be helpful, but in most cases requires a bit of trial and error to achieve the optimal result. Cython's tutorials contain a lot of information, but for iterative workflows like optimization with Cython, it's often useful to see it done "live".

For that reason, I decided to record some screencasts showing this iterative optimization process, using an Ising Model, as an example application.