coreit

Helper function to throw code on cores that can be run in parallel.

If you have code like

for i in xrange(start, stop): ... slow_function(i)

You can speed it up on a 4-core machine by running it like so:

functions = [slow_function for i in xrange(start, stop)] args = [(i,) for i in xrange(start, stop)] coreit(functions, args, 4)

Note that

p = multiprocessing.Pool(4) p.map(slow_function, xrange(start, stop))

is built in and does the equivalent.

As such, this code is somewhat obsolete, but has a distinction: if you have different functions that you want to run concurrently, coreit will do it. Pool.map won't.

Requirements

• multiprocessing (python 2.6 or http://code.google.com/p/python-multiprocessing/)

Todo

• ?

Licensed under PSF license Copyright (c) 2010 Matt Harrison ([email protected])