通常在我们进行多进程应用开发的过程中，不可避免的会遇到多个进程访问同一个资源（临界资源）的状况，这时候必须通过加一个全局性的锁，来实现资源的同步访问（即：同一时间里只能有一个进程访问资源）。
举个例子如下：
假设我们用mysql来实现一个任务队列，实现的过程如下：
1. 在Mysql中创建Job表，用于储存队列任务，如下：
create table jobs( id auto_increment not null primary key, message text not null, job_status not null default 0 );
message 用来存储任务信息，job_status用来标识任务状态，假设只有两种状态，0：在队列中， 1：已出队列
2. 有一个生产者进程，往job表中放新的数据，进行排队：
insert into jobs(message) values('msg1');
3.假设有多个消费者进程，从job表中取排队信息，要做的操作如下：
select * from jobs where job_status=0 order by id asc limit 1; update jobs set job_status=1 where id = "htmlcode">#!/usr/bin/env python2.7 # # -*- coding:utf-8 -*- # # Desc : # import logging, time import MySQLdb class Glock: def __init__(self, db): self.db = db def _execute(self, sql): cursor = self.db.cursor() try: ret = None cursor.execute(sql) if cursor.rowcount != 1: logging.error("Multiple rows returned in mysql lock function.") ret = None else: ret = cursor.fetchone() cursor.close() return ret except Exception, ex: logging.error("Execute sql \"%s\" failed! Exception: %s", sql, str(ex)) cursor.close() return None def lock(self, lockstr, timeout): sql = "SELECT GET_LOCK('%s', %s)" % (lockstr, timeout) ret = self._execute(sql) if ret[0] == 0: logging.debug("Another client has previously locked '%s'.", lockstr) return False elif ret[0] == 1: logging.debug("The lock '%s' was obtained successfully.", lockstr) return True else: logging.error("Error occurred!") return None def unlock(self, lockstr): sql = "SELECT RELEASE_LOCK('%s')" % (lockstr) ret = self._execute(sql) if ret[0] == 0: logging.debug("The lock '%s' the lock is not released(the lock was not established by this thread).", lockstr) return False elif ret[0] == 1: logging.debug("The lock '%s' the lock was released.", lockstr) return True else: logging.error("The lock '%s' did not exist.", lockstr) return None #Init logging def init_logging(): sh = logging.StreamHandler() logger = logging.getLogger() logger.setLevel(logging.DEBUG) formatter = logging.Formatter('%(asctime)s -%(module)s:%(filename)s-L%(lineno)d-%(levelname)s: %(message)s') sh.setFormatter(formatter) logger.addHandler(sh) logging.info("Current log level is : %s",logging.getLevelName(logger.getEffectiveLevel())) def main(): init_logging() db = MySQLdb.connect(host='localhost', user='root', passwd='') lock_name = 'queue' l = Glock(db) ret = l.lock(lock_name, 10) if ret != True: logging.error("Can't get lock! exit!") quit() time.sleep(10) logging.info("You can do some synchronization work across processes!") ##TODO ## you can do something in here ## l.unlock(lock_name) if __name__ == "__main__": main()在main函数里：
l.lock(lock_name, 10) 中，10是表示timeout的时间是10秒，如果10秒还获取不了锁，就返回，执行后面的操作。
在这个demo中，在标记TODO的地方，可以将消费者从job表中取消息的逻辑放在这里。即分割线以上的.2.假设有多个消费者进程，从job表中取排队信息，要做的操作如下：
select * from jobs where job_status=0 order by id asc limit 1; update jobs set job_status=1 where id = "htmlcode">[@tj-10-47 test]# ./glock.py 2014-03-14 17:08:40,277 -glock:glock.py-L70-INFO: Current log level is : DEBUG 2014-03-14 17:08:40,299 -glock:glock.py-L43-DEBUG: The lock 'queue' was obtained successfully. 2014-03-14 17:08:50,299 -glock:glock.py-L81-INFO: You can do some synchronization work across processes! 2014-03-14 17:08:50,299 -glock:glock.py-L56-DEBUG: The lock 'queue' the lock was released.可以看到第一个glock.py是 17:08:50解锁的，下面的glock.py是在17:08:50获取锁的，可以证实这样是完全可行的。
[@tj-10-47 test]# ./glock.py 2014-03-14 17:08:46,873 -glock:glock.py-L70-INFO: Current log level is : DEBUG 2014-03-14 17:08:50,299 -glock:glock.py-L43-DEBUG: The lock 'queue' was obtained successfully. 2014-03-14 17:09:00,299 -glock:glock.py-L81-INFO: You can do some synchronization work across processes! 2014-03-14 17:09:00,300 -glock:glock.py-L56-DEBUG: The lock 'queue' the lock was released. [@tj-10-47 test]#