progress_test.py

import time
from concurrent.futures import ThreadPoolExecutor, as_completed
from concurrent.futures import ProcessPoolExecutor
#多进程编程
#耗cpu的操作，用多进程编程， 对于io操作来说， 使用多线程编程，进程切换代价要高于线程

#1. 对于耗费cpu的操作，多进程由于多线程
# def fib(n):
#     if n<=2:
#         return 1
#     return fib(n-1)+fib(n-2)
#
# if __name__ == "__main__":
#     with ThreadPoolExecutor(3) as executor:
#         all_task = [executor.submit(fib, (num)) for num in range(25,40)]
#         start_time = time.time()
#         for future in as_completed(all_task):
#             data = future.result()
#             print("exe result: {}".format(data))
#
#         print("last time is: {}".format(time.time()-start_time))

#2. 对于io操作来说，多线程优于多进程
def random_sleep(n):
    time.sleep(n)
    return n

if __name__ == "__main__":
    with ProcessPoolExecutor(3) as executor:
        all_task = [executor.submit(random_sleep, (num)) for num in [2]*30]
        start_time = time.time()
        for future in as_completed(all_task):
            data = future.result()
            print("exe result: {}".format(data))

        print("last time is: {}".format(time.time()-start_time))