Parallelism in Python

Question

What are the options for achieving parallelism in Python? I want to perform a bunch of CPU bound calculations over some very large rasters, and would like to parallelise th

Answer 1

The new (2.6) multiprocessing module is the way to go. It uses subprocesses, which gets around the GIL problem. It also abstracts away some of the local/remote issues, so the choice of running your code locally or spread out over a cluster can be made later. The documentation I've linked above is a fair bit to chew on, but should provide a good basis to get started.