Comparison between multiprocessing Pool and ProcessPoolExecutor from concurrent.futures.

pool_futures.py

def hard_work(n):
    """ A naive factorization method. Take integer 'n', return list of
        factors.
    """
    # Do some CPU bond work here
    if n < 2:
        return []
    factors = []
    p = 2

    while True:
        if n == 1:
            return factors

        r = n % p
        if r == 0:
            factors.append(p)
            n = n // p
        elif p * p >= n:
            factors.append(n)
            return factors
        elif p > 2:
            # Advance in steps of 2 over odd numbers
            p += 2
        else:
            # If p == 2, get to 3
            p += 1
    assert False, "unreachable"


if __name__ == '__main__':
    from concurrent.futures import ProcessPoolExecutor, wait
    from multiprocessing import cpu_count
    try:
        workers = cpu_count()
    except NotImplementedError:
        workers = 1
    pool = ProcessPoolExecutor(max_workers=workers)
    result = pool.map(hard_work, range(100, 10000))

pool_multiprocessing.py

def hard_work(n):
    """ A naive factorization method. Take integer 'n', return list of
        factors.
    """
    # Do some CPU bond work here
    if n < 2:
        return []
    factors = []
    p = 2

    while True:
        if n == 1:
            return factors

        r = n % p
        if r == 0:
            factors.append(p)
            n = n // p
        elif p * p >= n:
            factors.append(n)
            return factors
        elif p > 2:
            # Advance in steps of 2 over odd numbers
            p += 2
        else:
            # If p == 2, get to 3
            p += 1
    assert False, "unreachable"


if __name__ == '__main__':
    from multiprocessing import Pool, cpu_count
    try:
        workers = cpu_count()
    except NotImplementedError:
        workers = 1
    pool = Pool(processes=workers)
    result = pool.map(hard_work, range(100, 10000))