python多线程编程以及join,setDaemon，线程锁的用法

来源：互联网发布：球球霸屏软件编辑：程序博客网时间：2024/05/20 14:19

Python threading的简单用法-实例说明

1、如何开启一个线程：代码如下

#!/usr/bin/python

#coding = utf-8

import threading

import time

def handle():

for item in["hello","threading","bye-bye"]:

printitem

def run():

t =threading.Thread(target=handle)

t.start()

if __name__ == '__main__':

print"main thread starting..."

run()

print "main thread finished..."

结果为：

[root@localhost test_del]# python testtheading.py

main thread starting...

hello

threading

bye-bye

main thread finished...

但是多运行几次，会出现这样的结果：

[root@localhost test_del]# python testtheading.py

main thread starting...

main thread finished...

hello

threading

bye-bye

为什么会出现不同的结果呢？

注意：在python中，默认情况下主线程运行结束后会一直等待工作线程运行完成，整个程序才算运行结束。这和c/c++中的线程运行是不同的，在c/c++中，当主线程运行完成，会主动杀死所有工作线程。

2、如何设置线程为后台线程—等同于c/c++线程的运行情况

程序如下：

#!/usr/bin/python

#coding = utf-8

import threading

import time

def handle():

for item in["hello","threading","bye-bye"]:

printitem

def run():

t =threading.Thread(target=handle)

t.setDaemon(True)

t.start()

if __name__ == '__main__':

print"main thread starting..."

run()

print"main thread finished..."

多运行几次，会出现如下情况：

[root@localhost test_del]# python testtheading.py

main thread starting...

main thread finished...

这就表明工作线程还没有开始运行就被kill掉了。

如何保证工作线程运行完后，主线程才能结束呢？

3、线程阻塞—threading.join()

程序如下：

#!/usr/bin/python

#coding = utf-8

import threading

import time

def handle():

for item in["hello","threading","bye-bye"]:

printitem

def run():

t =threading.Thread(target=handle)

t.setDaemon(True)

t.start()

t.join()

if __name__ == '__main__':

print"main thread starting..."

run()

print"main thread finished..."

threading.join()语句使得主线程会一直等待工作线程运行，直到工作线程运行完成，才开始继续执行主线程。无论运行多少次，其结果都为：

[root@localhost test_del]# python testtheading.py

main thread starting...

hello

threading

bye-bye

main thread finished...

4、如何给线程加锁和解锁—互斥锁

语法：共三行

Mutex = threading.Lock() --创建锁

Mutex.acquire([timeout]) --加锁，有个可选参数timeout，用于设定加锁时间

Mutex.release() --解锁

程序如下：未使用线程锁程序代码

#!/usr/bin/python

#coding = utf-8

import threading

import time

num = 0

def handle(i):

global num

while True:

time.sleep(2)

num += 1

print"thread %d:" %i,num

def run():

for i inrange(10):

t = threading.Thread(target=handle,args=(i,))

t.start()

if __name__ == '__main__':

print"main thread starting..."

run()

print"main thread finished..."

程序结果如下：

thread 9: 201

thread 8: 202

thread 4: 203

thread 5: 204

thread 1: 205

thread 2: 207

thread 6: 208

thread 3: 208

thread 0: 209

thread 7: 210

分析程序运行结果，会发现出现了多个线程的重复计算，这显然是不对的。

对上面的程序代码进行加锁，如下所示：

#!/usr/bin/python

#coding = utf-8

import threading

import time

num = 0

mutex =threading.Lock()

def handle(i):

global num

global mutex

while True:

time.sleep(2)

if mutex.acquire():

num += 1

print "thread %d:" %i,num

mutex.release()

def run():

for i inrange(10):

t =threading.Thread(target=handle, args=(i,))

t.start()

if __name__ == '__main__':

print"main thread starting..."

run()

print "main thread finished..."

程序结果如下：

[root@localhost test_del]# pythontesttheading.py

main thread starting...

main thread finished...

thread 0: 1

thread 1: 2

thread 2: 3

thread 3: 4

thread 4: 5

thread 5: 6

thread 6: 7

thread 8: 8

thread 7: 9

thread 9: 10

thread 0: 11

thread 1: 12

thread 2: 13

thread 3: 14

没有任何问题。

小结：以上介绍了python中多线程编程的基本使用，包括join, setDaemon和线程锁等。

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