python 多线程, 多进程, ProcessPoolExecutor. 有关GIL锁的问题实验.

import time
import threading
from multiprocessing import Process
from concurrent.futures import ProcessPoolExecutor

def time_decorator(func):

    def wrapper(*args, **kwargs):
        now = time.time()
        func(*args, **kwargs)
        print(time.time() - now)
    return wrapper


def add():
    for i in range(100000000):
        pass

@time_decorator
def multi_threading():

    t_list = []
    for i in range(10):
        t = threading.Thread(target=add)
        t_list.append(t)

    for t in t_list:
        t.start()

    for t in t_list:
        t.join()

@time_decorator
def multi_processing():

    t_list = []
    for i in range(10):
        t = Process(target=add)
        t_list.append(t)

    for t in t_list:
        t.start()

    for t in t_list:
        t.join()

@time_decorator
def future_multi_processing():
    """
    父子进程, 平行运行多个GIL解释器.
    父子进程, 通信通过Pickle序列化及本地套接字(local socket), 序列化和反序列化, 开销较大.
    没有任何附加信息进程间通信
    """
    r_list = []
    pool = ProcessPoolExecutor(max_workers=10)
    for i in range(10):
        t = pool.submit(add)
        r_list.append(t)
    pool.shutdown()


@time_decorator
def add_total():
    for i in range(100000000 * 10):
        pass

if __name__ == "__main__":

    multi_threading()
    multi_processing()
    future_multi_processing()
    add_total()

29.84246516227722 # 多线程
14.255790710449219 # 多进程
13.782246112823486 # futures.ProcessPoolExecutor
父子进程, 平行运行多个GIL解释器.
父子进程, 通信通过Pickle序列化及本地套接字(local socket), 序列化和反序列化, 开销较大.
没有任何附加信息进程间通信
26.558323860168457 # 正常执行