python线程锁_对python多线程中Lock()与RLock()锁详解

资源总是有限的&＃xff0c;程序运行如果对同一个对象进行操作&＃xff0c;则有可能造成资源的争用&＃xff0c;甚至导致死锁

也可能导致读写混乱

锁提供如下方法&＃xff1a;

1.Lock.acquire([blocking])

2.Lock.release()

3.threading.Lock() 加载线程的锁对象&＃xff0c;是一个基本的锁对象&＃xff0c;一次只能一个锁定&＃xff0c;其余锁请求&＃xff0c;需等待锁释放后才能获取

4.threading.RLock() 多重锁&＃xff0c;在同一线程中可用被多次acquire。如果使用RLock&＃xff0c;那么acquire和release必须成对出现&＃xff0c;

调用了n次acquire锁请求&＃xff0c;则必须调用n次的release才能在线程中释放锁对象

例如&＃xff1a;

无锁&＃xff1a;

#coding&＃61;utf8

import threading

import time

num &＃61; 0

def sum_num(i):

global num

time.sleep(1)

num &＃43;&＃61;i

print num

print &＃39;%s thread start!&＃39;%(time.ctime())

try:

for i in range(6):

t &＃61;threading.Thread(target&＃61;sum_num,args&＃61;(i,))

t.start()

except KeyboardInterrupt,e:

print "you stop the threading"

print &＃39;%s thread end!&＃39;%(time.ctime())

输出&＃xff1a;

Sun May 28 20:54:59 2017 thread start!

Sun May 28 20:54:59 2017 thread end!

01

3

710

15

结果显示混乱

引入锁&＃xff1a;

#coding&＃61;utf8

import threading

import time

num &＃61; 0

def sum_num(i):

lock.acquire()

global num

time.sleep(1)

num &＃43;&＃61;i

print num

lock.release()

print &＃39;%s thread start!&＃39;%(time.ctime())

try:

lock&＃61;threading.Lock()

list &＃61; []

for i in range(6):

t &＃61;threading.Thread(target&＃61;sum_num,args&＃61;(i,))

list.append(t)

t.start()

for threadinglist in list:

threadinglist.join()

except KeyboardInterrupt,e:

print "you stop the threading"

print &＃39;%s thread end!&＃39;%(time.ctime())

结果&＃xff1a;

Sun May 28 21:15:37 2017 thread start!

0

1

3

6

10

15

Sun May 28 21:15:43 2017 thread end!

其中&＃xff1a;

lock&＃61;threading.Lock()加载锁的方法也可以换成lock&＃61;threading.RLock()

如果将上面的sum_num修改为&＃xff1a;

lock.acquire()

global num

lock.acquire()

time.sleep(1)

num &＃43;&＃61;i

lock.release()

print num

lock.release()

那么&＃xff1a;

lock&＃61;threading.Lock() 加载的锁&＃xff0c;则一直处于等待中&＃xff0c;锁等待

而lock&＃61;threading.RLock() 运行正常

以上这篇对python多线程中Lock()与RLock()锁详解就是小编分享给大家的全部内容了&＃xff0c;希望能给大家一个参考&＃xff0c;也希望大家多多支持我们。

本文标题: 对python多线程中Lock()与RLock()锁详解

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