time_eval.py

import multiprocessing.dummy as mul
from time import time, sleep
from joblib import Parallel, delayed

def f(x):
    sleep(.01)
    return x*x


if __name__ == '__main__':
    print "-------- testing multiprocessing on ",mul.cpu_count(),"cores----------"
    print ""

    elements = 10000

    t0 = time()
    res_for = [f(x) for x in range(elements)]
    t00 = time()
    pool = mul.Pool(processes=8)
    t1 = time()
    res_par = pool.map(f, range(elements))
    t2 = time()
    res_seq = map(f, range(elements))
    t3 = time()
    res_app = [pool.apply_async(f,(x,)) for x in range(elements)]
    res_app = [result.get() for result in res_app]
    t4 = time()
    res_job = Parallel(n_jobs=8, backend='threading')(delayed(f)(x) for x in range(elements))
    t5 = time()

    print len(res_for),"elements","for() time",(t00-t0),"s"
    print len(res_seq),"elements","map() time",(t3-t2),"s"
    print len(res_par),"elements","pool.map() time",(t2-t1),"s"
    print len(res_app),"elements","pool.apply_async() time", (t4-t3),"s"
    print len(res_job),"elements","joblib.Parallel time", (t5-t4),"s"