#练习：测试单进程和多进程执行效率

import multiprocessing

import time

def m1(x):

    time.sleep(0.01)

    return x * x

if __name__ == '__main__':

    #并行并发

    pool = multiprocessing.Pool(multiprocessing.cpu_count()) #获取CPU的核数，表示进程池的最大进程数

    print type(pool)

    i_list = range(1000)

    time1=time.time()

    pool.map(m1, i_list)

    time2=time.time()

    print 'time elapse:',time2-time1

    #串行

    time1=time.time()

    map(m1, i_list)

    time2=time.time()

    print 'time elapse:',time2-time1

#练习：异步进程

import time

from multiprocessing import Pool

def f(x,y):

    return x * y

if __name__ == '__main__':

    pool = Pool(processes = 4)      # start 4 worker processes #固定写法，也可以写成pool = Pool(4)

    #result = pool.apply_async(f, [10])

    # evaluate "f(10)" asynchronously，这里是用异步的方式，这里一行表示起的一个进程

    result1 = pool.apply_async(f, args=(10,20))

    result2 = pool.apply_async(f, args=(10,30))

    result3 = pool.apply_async(f, args=(10,40))

    #print result.get(timeout = 1)

    print result1.get(timeout = 0.001)

    print result2.get(timeout = 0.01)

    print result3.get(timeout = 1)

    #print pool.map(f,range(10))    # prints "[0, 1, 4,..., 81]"