Python GIL 系列之通过实例认识Python的GIL

最新推荐文章于 2025-10-14 14:24:22 发布

原创

最新推荐文章于 2025-10-14 14:24:22 发布 · 8.9k 阅读

10 ·

CC 4.0 BY-SA版权

文章标签：

#Python #GIL

本文通过实例展示了Python的全局解释器锁（GIL）如何影响多线程性能，尤其是在多核CPU上的表现。尽管Python3.2后GIL有所改进，但仍然对I/O操作的响应速度造成影响。建议在面临多线程和数据共享挑战时，考虑使用Process代替Thread。了解更多关于GIL的知识，可以参考David Beazley的PyCon 2010演讲。

1. 请看下面的例子：

import time

from threading import Thread

from multiprocessing import Process

from timeit import Timer

def countdown(n):

    while n > 0:

        n -= 1

def t1():

    COUNT=100000000

    thread1 = Thread(target=countdown,args=(COUNT,))

    thread1.start()

    thread1.join()

#    COUNT = 100000000 # 100 million

#    countdown(COUNT)

def t2():

    COUNT=100000000

    thread1 = Thread(target=countdown,args=(COUNT//2,))

    thread2 = Thread(target=countdown,args=(COUNT//2,))

    thread1.start(); thread2.start()

    thread1.join(); thread2.join()

def t3():

    COUNT=100000000

    p1 = Process(target=countdown,args=(COUNT//2,))

    p2 = Process(target=countdown,args=(COUNT//2,))

    p1.start(); p2.start()

    p1.join(); p2.join()

if __name__ == '__main__':

    

    t = Timer(t1)

    print 'countdown in one thread:',t.timeit(1)

    

    t = Timer(t2)

    print 'countdown use two thread:',t.timeit(1)