Python – How to use multiprocessing with multiple arguments


In the Python multiprocessing library, is there a variant of which supports multiple arguments?

text = "test"
def harvester(text, case):
    X = case[0]
    text+ str(X)

if __name__ == '__main__':
    pool = multiprocessing.Pool(processes=6)
    case = RAW_DATASET,case),case, 1)

Best Solution

is there a variant of which support multiple arguments?

Python 3.3 includes pool.starmap() method:

#!/usr/bin/env python3
from functools import partial
from itertools import repeat
from multiprocessing import Pool, freeze_support

def func(a, b):
    return a + b

def main():
    a_args = [1,2,3]
    second_arg = 1
    with Pool() as pool:
        L = pool.starmap(func, [(1, 1), (2, 1), (3, 1)])
        M = pool.starmap(func, zip(a_args, repeat(second_arg)))
        N =, b=second_arg), a_args)
        assert L == M == N

if __name__=="__main__":

For older versions:

#!/usr/bin/env python2
import itertools
from multiprocessing import Pool, freeze_support

def func(a, b):
    print a, b

def func_star(a_b):
    """Convert `f([1,2])` to `f(1,2)` call."""
    return func(*a_b)

def main():
    pool = Pool()
    a_args = [1,2,3]
    second_arg = 1, itertools.izip(a_args, itertools.repeat(second_arg)))

if __name__=="__main__":


1 1
2 1
3 1

Notice how itertools.izip() and itertools.repeat() are used here.

Due to the bug mentioned by @unutbu you can't use functools.partial() or similar capabilities on Python 2.6, so the simple wrapper function func_star() should be defined explicitly. See also the workaround suggested by uptimebox.