Parallel processing of dictionary

multi.py

from multiprocessing import Pool, cpu_count
import time
import random
import logging
from pprint import pprint

logging.basicConfig(level=logging.DEBUG,
                    format='(%(threadName)-10s) %(message)s',
)

logger = logging.getLogger(__name__)


def foo(keeper):
    seconds = random.random()

    # Simulate cpu usage
    start_time = time.time()

    while True:
        now_time = time.time()
        if (now_time - start_time) > seconds:
            break

        x = 10005000 * 10005000
        x = x * 10005000

    keeper.value = seconds
    return keeper


class Keeper(object):
    def __init__(self, key, date):
        self.key = key
        self.date = date
        self.value = None


def main():
    initial_dict = {}
    keys = ["1", "2", "3", "4"]
    days = range(10)
    for key in keys:
        d = {}
        initial_dict[key] = d
        for day in days:
            d[day] = []

    t1 = time.time()

    pool = Pool()
    keepers = []
    for key in keys:
        for day in days:
            keepers.append(Keeper(key, day))

    keepers = pool.map(foo, keepers)
    for k in keepers:
        initial_dict[k.key][k.date].append(k.value)

    t2 = time.time()
    logger.debug ("ASYNC VERSION: %s" % (t2 - t1))
    t2 = time.time()

    for key in keys:
        for day in days:
            foo(Keeper(key, day))

    t3 = time.time()
    logger.debug ("SYNC VERSION: %s" % (t3 - t2))


if __name__ == '__main__':
    logger.debug("CPU COUNT: %d" % cpu_count())
    main()
    # you can test me here: http://www.tutorialspoint.com/execute_python_online.php