Threads in Python

One thing to remember before spending time and effort in writing a multi-threaded Python application is that there is a Global Interpreter Lock (GIL), so you won't actually be running more than one thread at a time.

This makes threading unsuitable for trying to take advantage of multiple cores or CPUs. You may get some speedup from multiplexing other resources (network, disk, ...), but it's never been particularly noticeable in my experience.

In general, I only use threads when there are several logically separate tasks happening at once, and yet I want them all in the same VM. A thread pulling data from the web and putting it on a Queue, while another thread pops from the Queue and writes to a database, something like that.

With Python 2.6, there is the new multiprocessing module which is pretty cool - it's got a very similar interface to the threading module, but actually spawns new OS processes, sidestepping the GIL.

There is a fantastic pdf, Tutorial on Threads Programming with Python by Norman Matloff and Francis Hsu, of University of California, Davis.

Threads should be avoided whenever possible. They add much in complexity, synchronization issues and hard to debug issues. However some problems require them (i.e. GUI programming), but I would encourage you to look for a single-threaded solution if you can.

There are several tutorials here.