In Python 3.x, you can use concurrent.futures.ThreadPoolExecutor to do this, rather than rolling your own.
Python 2.x actually has a built-in thread pool you can use as well, its just not well documented:
from multiprocessing.pool import ThreadPool
def foo(word, number):
print (word * number)
r[(word,number)] = number
return number
words = ['hello', 'world', 'test', 'word', 'another test']
numbers = [1,2,3,4,5]
pool = ThreadPool(5)
results = []
for i in range(0, len(words)):
results.append(pool.apply_async(foo, args=(words[i], numbers[i])))
pool.close()
pool.join()
results = [r.get() for r in results]
print results
Or (using map instead of apply_async):
from multiprocessing.pool import ThreadPool
def foo(word, number):
print word*number
return number
def starfoo(args):
"""
We need this because map only supports calling functions with one arg.
We need to pass two args, so we use this little wrapper function to
expand a zipped list of all our arguments.
"""
return foo(*args)
words = ['hello', 'world', 'test', 'word', 'another test']
numbers = [1,2,3,4,5]
pool = ThreadPool(5)
# We need to zip together the two lists because map only supports calling functions
# with one argument. In Python 3.3+, you can use starmap instead.
results = pool.map(starfoo, zip(words, numbers))
print results
pool.close()
pool.join()