关于下列python多线程代码输出效果的疑问?
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PHP中文网 2017-04-18 09:17:00
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下面代码是《python核心编程》关于多线程编程一章中的一个例子:

#!/usr/bin/env python

import threading
from time import sleep, ctime

loops = [ 4, 2 ]

class MyThread(threading.Thread):
    def __init__(self, func, args, name=''):
        threading.Thread.__init__(self)
        self.name = name
        self.func = func
        self.args = args

    def run(self):
        apply(self.func, self.args)

def loop(nloop, nsec):
    print 'start loop', nloop, 'at:', ctime()
    sleep(nsec)
    print 'loop', nloop, 'done at:', ctime()

def main():
    print 'starting at:', ctime()
    threads = []
    nloops = range(len(loops))

    for i in nloops:
        t = MyThread(loop, (i, loops[i]),
        loop.__name__)
        threads.append(t)

    for i in nloops:
        threads[i].start()

    for i in nloops:
        threads[i].join()

    print 'all DONE at:', ctime()

if __name__ == '__main__':
    main()

书上显示的输出结果是这样的

我自己打了一遍,输出结果是这样的

可以看到,我的loop0和loop1的显示内容混合到一起了,这样是对的吗?为什么会这样?

PHP中文网
PHP中文网

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巴扎黑

You need to lock it here. The standard output is a shared resource. Everyone can write to the screen at the same time, so it may be confusing.
You need to add a mutex lock here to tell other threads that I want to write now, so don’t write it yet. Then when you finish writing, tell other threads that I have finished writing, and you can apply to write.

The

loop function is written as:

import threading
#创建锁
mutex = threading.Lock()

def loop(nloop, nsec):
    #锁定
    mutex.acquire()
    print 'start loop', nloop, 'at:', ctime()
    sleep(nsec)
    print 'loop', nloop, 'done at:', ctime()
    #释放
    mutex.release()
    

All codes are:

#!/usr/bin/env python
# encoding: utf-8


import threading
from time import sleep, ctime

loops = [ 4, 2 ]

class MyThread(threading.Thread):
    def __init__(self, func, args, name=''):
        threading.Thread.__init__(self)
        self.name = name
        self.func = func
        self.args = args

    def run(self):
        apply(self.func, self.args)

# 创建锁
mutex = threading.Lock()

def loop(nloop, nsec):
    # 锁定
    mutex.acquire()
    print 'start loop', nloop, 'at:', ctime()
    sleep(nsec)
    print 'loop', nloop, 'done at:', ctime()
    # 释放
    mutex.release()

def main():
    print 'starting at:', ctime()
    threads = []
    nloops = range(len(loops))

    for i in nloops:
        t = MyThread(loop, (i, loops[i]),
        loop.__name__)
        threads.append(t)

    for i in nloops:
        threads[i].start()

    for i in nloops:
        threads[i].join()

    print 'all DONE at:', ctime()

if __name__ == '__main__':
    main()
PHPzhong

Three knowledge points are involved here

  1. Python thread scheduling strategy
    Python threads are actually native threads supported by the operating system. Python's multi-threading mechanism is based on the native thread mechanism of the operating system. Different operating systems have different implementations

  2. window/linux python thread scheduling strategy
    Search for "window thread scheduling strategy" or "linux thread scheduling strategy"

  3. python GIL lock - PYTHON single process without parallelism

Then you will understand

巴扎黑

You can understand after running it a few times

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