Python 中多线程之

_thread模块是python 中多线程操作的一种模块方式，主要的原理是派生出多线程，然后给线程加锁，当线程结束的时候取消锁，然后执行主程序

thread 模块和锁对象的说明
start_new_thred(function,args,kwargs=none)	派生一个新的线程，使用给定的argvs,和可选的kwargs 来执行function
allocate_lock()	分配locktype 锁对象
exit()	给线程退去指令

locktype 锁对象的方法
qcquire(wait=none)	尝试获取锁对象
Locked()	如果获取了锁对象则返回true ，否则false
release()	释放锁

程序的代码

 #!/usr/bin/python

 from  time import  sleep,ctime

 import   _thread

 loops=[4,2]           #定义任务的时间长短

 def   loop(nloop,nsec,lock): # nloop 任务的名称  nesc  任务执行的时间   lock  锁

     print ('loop',nloop,'start at:', ctime())  #输出任务的开始的时间

     sleep(nsec) # 任务的执行时间

     print('loop',nloop, 'done  at:',ctime())#输出任务的结束时间

     lock.release() #释放任务的锁

 def  main():

     print ('starting at:',ctime()) #开始执行任务的当前时间

     locks=[] # 定义一个空的锁列表

     nloops=range(len(loops))  #主要作用是为了下面循环区分具体的任务

     for i  in  nloops:

         lock=_thread.allocate_lock() #给任务加上锁

         lock.acquire()#获取锁对象

         locks.append(lock) #把具体的锁对象加到锁列表里面去

     for i in nloops:#循环时间长短

         _thread.start_new_thread(loop,(i, loops[i],locks[i]))  #派生出两个新的线程  并传递给循环，其中loops[i]传递给 nesc ,locks[i] 传递给   lock

     for i in nloops:# 循环时间长短

         while locks[i].locked():#判断派生的线程有没有锁，，如果有暂停主线程，直到所有的锁都释放了才会执行主线程

             pass

     print ('all doneat:', ctime())        

 if __name__ == '__main__': #执行函数

     main()

     任务执行的结果

关于给任务加锁的说明（第一个for 循环）

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" 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任务执行的结果

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" 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关于程序的思路流程：

导入时间模块

导入 _thread 模块

定义一个任务时间长短列表

执行mian 函数

输出开始执行的时间

定义空的锁列表

第一个循环主要是获取锁对象，给任务加上锁把具体的锁对象加到锁列表里面去

第二个循环主要的作用是派生出两个新的线程。执行,loop函数，传递参数给 loop 函数

。

判断线程有没有锁。如果有暂定主线程，没有的话执行下面代码结束输入

巴特西

Python 中多线程之 _thread

_thread模块是python 中多线程操作的一种模块方式，主要的原理是派生出多线程，然后给线程加锁，当线程结束的时候取消锁，然后执行主程序

程序的代码

关于给任务加锁的说明（第一个for 循环）

任务执行的结果

关于程序的思路流程：

最新文章

热门文章

巴特西

Python 中多线程之 _thread

_thread模块是python 中多线程操作的一种模块方式，主要的原理是派生出多线程，然后给线程加锁，当线程结束的 时候取消锁，然后执行主程序

程序的代码

关于给任务加锁的说明 （第一个for 循环）

任务执行的结果

关于程序的思路流程：

最新文章

热门文章

_thread模块是python 中多线程操作的一种模块方式，主要的原理是派生出多线程，然后给线程加锁，当线程结束的时候取消锁，然后执行主程序

关于给任务加锁的说明（第一个for 循环）