0.目录

2. threading.Lock() 的必要性
3.观察block
4.threading.RLock() 的应用场景

1.参考

Thread Synchronization Mechanisms in Python

count += 1 不是原子操作，三步操作可能被中断，通过lock将三步操作“封装”为一步操作，要么执行，要么不执行。

counter = 0

def process_item(item):

    global counter

    ... do something with item ...

    counter += 1

# The reason for this is that the increment operation is actually executed in three steps;

#first, the interpreter fetches the current value of the counter,

# then it calculates the new value,

# and finally, it writes the new value back to the variable.

Atomic Operations #

The simplest way to synchronize access to shared variables or other resources is to rely on atomic operations in the interpreter.

An atomic operation is an operation that is carried out in a single execution step, without any chance that another thread gets control.

What kinds of global value mutation are thread-safe?

python的原子操作

A global interpreter lock (GIL) is used internally to ensure that only one thread runs in the Python VM at a time. In general, Python offers to switch among threads only between bytecode instructions; how frequently it switches can be set via sys.setcheckinterval(). Each bytecode instruction and therefore all the C implementation code reached from each instruction is therefore atomic from the point of view of a Python program.

In theory, this means an exact accounting requires an exact understanding of the PVM bytecode implementation. In practice, it means that operations on shared variables of built-in data types (ints, lists, dicts, etc) that “look atomic” really are.

For example, the following operations are all atomic (L, L1, L2 are lists, D, D1, D2 are dicts, x, y are objects, i, j are ints):

L.append(x)

L1.extend(L2)

x = L[i]

x = L.pop()

L1[i:j] = L2

L.sort()

x = y

x.field = y

D[x] = y

D1.update(D2)

D.keys()

These aren’t:

i = i+1

L.append(L[-1])

L[i] = L[j]

D[x] = D[x] + 1

Operations that replace other objects may invoke those other objects’ __del__() method when their reference count reaches zero, and that can affect things. This is especially true for the mass updates to dictionaries and lists. When in doubt, use a mutex!

2. threading.Lock()  的必要性

#!usr/bin/env python

#coding:utf-8

import sys

import time

import random

import logging

import threading

import Queue

lock = threading.Lock()     #'function-call ownership'

rlock = threading.RLock()   #thread ownership

logging.basicConfig(level=logging.DEBUG,

                    format = '%(asctime)s - %(threadName)-10s - %(levelname)s - %(message)s')

logger = logging.getLogger()

count = 0

class MyThread(threading.Thread):

    def __init__(self):

        threading.Thread.__init__(self)

    def run(self):

        global count

        for i in range(100):

            count += 1

        logger.debug('{} finished, count is {}'.format(self.name, count))     

def main():

    logger.debug('initial count: {}'.format(count))

    thread_list = [MyThread() for i in range(2)]

    for t in thread_list:

        t.start()

    for t in thread_list:

        t.join()   

    logger.debug('final count: {}'.format(count))

if __name__ == '__main__':

    main()

修改run函数代码的不同输出：

    def run(self):

        global count

        for i in range(100):

            count += 1

        logger.debug('{} finished, count is {}'.format(self.name, count))

# 在切换线程之前，某一线程已经完成，两个线程顺序完成，结果几乎不会有误

# 2017-08-20 12:19:30,857 - MainThread - DEBUG - initial count: 0

# 2017-08-20 12:19:30,858 - Thread-1   - DEBUG - Thread-1 finished, count is 100

# 2017-08-20 12:19:30,858 - Thread-2   - DEBUG - Thread-2 finished, count is 200

# 2017-08-20 12:19:30,858 - MainThread - DEBUG - final count: 200        

        time.sleep(0.001)

        for i in range(100):

            count += 1

        logger.debug('{} finished, count is {}'.format(self.name, count))

# 开头sleep导致两个线程几乎同时启动，结果可能有误

# 2017-08-20 12:24:59,046 - MainThread - DEBUG - initial count: 0

# 2017-08-20 12:24:59,048 - Thread-2   - DEBUG - Thread-2 finished, count is 124

# 2017-08-20 12:24:59,048 - Thread-1   - DEBUG - Thread-1 finished, count is 153

# 2017-08-20 12:24:59,048 - MainThread - DEBUG - final count: 153

        for i in range(10000):

            count += 1

        logger.debug('{} finished, count is {}'.format(self.name, count))

# bytecodes足够导致两个线程交替运行，结果大概率有误

# 2017-08-20 12:20:17,719 - MainThread - DEBUG - initial count: 0

# 2017-08-20 12:20:17,723 - Thread-1   - DEBUG - Thread-1 finished, count is 12438

# 2017-08-20 12:20:17,723 - Thread-2   - DEBUG - Thread-2 finished, count is 12616

# 2017-08-20 12:20:17,723 - MainThread - DEBUG - final count: 12616        

        with lock:

            for i in range(10000):

                count += 1

        logger.debug('{} finished, count is {}'.format(self.name, count))

# lock直到某一线程完成，结果正确

# 2017-08-20 12:20:37,630 - MainThread - DEBUG - initial count: 0

# 2017-08-20 12:20:37,631 - Thread-1   - DEBUG - Thread-1 finished, count is 10000

# 2017-08-20 12:20:37,632 - Thread-2   - DEBUG - Thread-2 finished, count is 20000

# 2017-08-20 12:20:37,634 - MainThread - DEBUG - final count: 20000

        for i in range(10000):

            with lock:

                count += 1

        logger.debug('{} finished, count is {}'.format(self.name, count))

# 两个线程交替lock，结果正确

# 2017-08-20 12:21:03,921 - MainThread - DEBUG - initial count: 0

# 2017-08-20 12:21:03,973 - Thread-1   - DEBUG - Thread-1 finished, count is 19979

# 2017-08-20 12:21:03,973 - Thread-2   - DEBUG - Thread-2 finished, count is 20000

# 2017-08-20 12:21:03,973 - MainThread - DEBUG - final count: 20000

3.观察block

    def run(self):

        global count

        all = range(10000)  #确保每个线程 +1 的次数

        while all != []:

            if not lock.acquire(False):  #假设没有参数会导致block，则马上返回false当不block；否则返回true且acquire

                logger.debug('{} wait...{}'.format(self.name, len(all)))

            else:

                try:

                    count += 1

                    all.pop()

                except Exception as err:

                    logger.debug('{} err, count is {}'.format(self.name, count))

                finally:

                    # logger.debug('{} release {} {}'.format(self.name, count, len(all)))  #导致两个线程顺序执行？？？

                    lock.release()

        logger.debug('{} finished, count is {}'.format(self.name, count))

输出：

2017-08-20 12:32:55,204 - MainThread - DEBUG - initial count: 0

2017-08-20 12:32:55,210 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,210 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,210 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,210 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,210 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,210 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,210 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,211 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,213 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,213 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,213 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,213 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,214 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,214 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,214 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,214 - Thread-1   - DEBUG - Thread-1 wait...9925

2017-08-20 12:32:55,216 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,216 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,216 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,216 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,216 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,217 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,217 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,217 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,217 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,217 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,217 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,217 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,217 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,217 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,219 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,219 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,219 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,219 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,219 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,220 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,220 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,220 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,220 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,220 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,220 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,220 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,220 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,220 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,220 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,221 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,221 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,221 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,221 - Thread-2   - DEBUG - Thread-2 wait...6036

2017-08-20 12:32:55,226 - Thread-1   - DEBUG - Thread-1 finished, count is 13964

2017-08-20 12:32:55,236 - Thread-2   - DEBUG - Thread-2 finished, count is 20000

2017-08-20 12:32:55,236 - MainThread - DEBUG - final count: 20000

4.threading.RLock() 的应用场景

Problems with Simple Locking

lock = threading.Lock()

def get_first_part():

    with lock: # any thread that attempts to acquire the lock will block, even if the same thread is already holding the lock.

        ... fetch data for first part from shared object

    return data    

def get_second_part():

    with lock:

        ... fetch data for second part from shared object

    return data  

def get_both_parts():

    with lock:  # other thread may modify the resource between the two calls

        first = get_first_part()

        # between the two calls

        second = get_second_part()

    return first, second    

# While simple locks will block if the same thread attempts to acquire the same lock twice,

# a re-entrant lock only blocks if another thread currently holds the lock.

rlock = threading.RLock()

python之多线程 threading.Lock() 和 threading.RLock()的更多相关文章

  1. python的threading的使用（join方法，多线程，锁threading.Lock和threading.Condition

    一.开启多线程方法一 import threading,time def write1(): for i in range(1,5): print('1') time.sleep(1) def wri ...

  2. python爬虫——多线程+协程（threading+gevent）

    上一篇博客中我介绍了如何将爬虫改造为多进程爬虫,但是这种方法对爬虫效率的提升不是非常明显,而且占用电脑cpu较高,不是非常适用于爬虫.这篇博客中,我将介绍在爬虫中广泛运用的多线程+协程的解决方案,亲测 ...

  3. 基于Python的多线程模块Threading小结

    步入正题前,先准备下基本知识,线程与进程的概念. 相信作为一个测试人员,如果从理论概念上来说其两者的概念或者区别,估计只会一脸蒙蔽,这里就举个例子来说明下其中的相关概念. 平安夜刚过,你是吃到了苹果还 ...

  4. Python：多线程编程

    1.IO编程 IO(input/output).凡是用到数据交换的地方,都会涉及io编程,例如磁盘,网络的数据传输.在IO编程中,stream(流)是一种重要的概念,分为输入流(input strea ...

  5. 孤荷凌寒自学python第三十九天python 的线程锁Lock

    孤荷凌寒自学python第三十九天python的线程锁Lock (完整学习过程屏幕记录视频地址在文末,手写笔记在文末) 当多个线程同时操作一个文件等需要同时操作某一对象的情况发生时,很有可能发生冲突, ...

  6. Day12- Python基础12 线程、GIL、Lock锁、RLock锁、Semaphore锁、同步条件event

    http://www.cnblogs.com/yuanchenqi/articles/6248025.html  博客地址 本节内容: 1:进程和线程的说明 2:线程的两种调用方式 3:threadi ...

  7. python中多线程相关

    基础知识 进程:进程就是一个程序在一个数据集上的一次动态执行过程 数据集:程序执行过程中需要的资源 进程控制块:完成状态保存的单元 线程:线程是寄托在进程之上,为了提高系统的并发性 线程是进程的实体 ...

  8. python网络-多线程(22)

    一.什么是线程 线程(英语:thread)是操作系统能够进行运算调度的最小单位.它被包含在进程之中,是进程中的实际运作单位.同一进程中的多条线程将共享该进程中的全部系统资源,一个进程可以有很多线程,每 ...

  9. python 使用多线程进行并发编程/互斥锁的使用

    import threading import time """ python的thread模块是比较底层的模块,python的threading模块是对thread做了 ...

随机推荐

  1. 【转】C++标准转换运算符const_cast

    const_cast转换符是用来移除变量的const或volatile限定符. 对于const变量,我们不能修改它的值,这是这个限定符最直接的表现.但是我们就是想违背它的限定希望修改其内容怎么办呢? ...

  2. [转载]Maximum Flow: Augmenting Path Algorithms Comparison

    https://www.topcoder.com/community/data-science/data-science-tutorials/maximum-flow-augmenting-path- ...

  3. C#委托delegate、Action、Func、predicate 对比用法

    委托是一个类,它定义了方法的类型,使得可以将方法当作另一个方法的参数来进行传递.事件是一种特殊的委托. 一.委托的声明   (1) delegate delegate我们常用到的一种声明 Delega ...

  4. 通过flask实现web页面简单的增删改查

    通过flask实现web页面简单的增删改查 # 1.后台程序falsk_web01.py #coding:utf-8 from flask import Flask,render_template,r ...

  5. 通过zabbix自带api进行主机的批量添加操作

    通过zabbix自带api进行批量添加主机 我们需要监控一台服务器的时候,当客户端装好zabbix-agent端并正确配置以后,需要在zabbix-server的web gui界面进行添加zabbix ...

  6. Ex3_28 在2SAT问题中,给定一个字句的集合..._第十二次作业

    参考答案 ----------------------------------------------------------------------------------------------- ...

  7. ACM-ICPC 2018 焦作赛区网络预赛 I Save the Room

    Bob is a sorcerer. He lives in a cuboid room which has a length of AAA, a width of BBB and a height ...

  8. 快速开发android，离不开这10个优秀的开源项目

    作为一名菜鸡Android,时常瞻仰大佬们的开源项目是非常必要的.这里我为大家收集整理了10个优秀的开源项目,方便我们日常开发中学习! 作者:ListenToCode博客:https://www.ji ...

  9. Confluence 6 配置一个 Confluence 环境

    本部分对你 Confluence 的外部设置进行描述.包括有如何配置 Web 服务器,应用服务器,目录和文件等信息—— Confluence 运行所需要的所有环境.有关在服务器内部对配置进行修改的内容 ...

  10. ionic3 启动白屏处理

    重点就就三点 1.设置不自动隐藏splashscreen页面,设置最多延迟10s再关闭,这样可以不显示启动前的白画面 <preference name="AutoHideSplashS ...