Simple Parallelization in Python with Pools

pools.py

# Given a function, func(var), the map() function will apply func() to every
# element of a list and return a list of equal size.

def func(var):
    return var**2
    
numbers = [1,2,3,4]
squares = map(func, numbers) # [1,4,9,16]

# The multiprocessing module contains various objects for performing parallel
# tasks in Python. The "Pool" object allows you to perform a map()-like
# operation but over several processors / cores.

import multiprocessing
from multiprocessing import Pool

pool = Pool(processes=4) # set the number of processes you want to spawn

squares_parallel = pool.map(func, numbers) # [1,4,9,16]