python中使用threading.condition交替打印两个字符的程序。
这个程序涉及到两个线程的的协调问题,两个线程为了能够相互协调运行,必须持有一个共同的状态,通过这个状态来维护两个线程的执行,通过使用threading.condition对象就能够完成两个线程之间的这种协调工作。
threading.condition默认情况下会通过持有一个reentrantlock来协调线程之间的工作,所谓可重入锁,是只一个可以由一个线程递归获取的锁,此锁对象会维护当前锁的所有者(线程)和当前所有者递归获取锁的次数(本文在逻辑上和可重入锁没有任何关系,完全可以用一个普通锁替代)。
python文档中给出的描述是:它是一个与某个锁相联系的变量。同时它实现了上下文管理协议。其对象中除了acquire和release方法之外,其它方法的调用的前提是,当前线程必须是这个锁的所有者。
通过代码和其中的注释,能够非常明白地弄清楚condition的原理是怎样的:
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import threading import time import functools def worker(cond, name): """worker running in different thread""" with cond: # 通过__enter__方法,获取cond对象中的锁,默认是一个reentrantlock对象 print ( '...{}-{}-{}' . format (name, threading.current_thread().getname(), cond._is_owned())) cond.wait() # 创建一个新的锁newlock,调用acquire将newlock获取,然后将newlock放入等待列表中,\ # 释放cond._lock锁(_release_save),最后再次调用acquire让newlock阻塞 print ( 'wait returned in {}' . format (name)) if __name__ = = '__main__' : condition = threading.condition() t1 = threading.thread(target = functools.partial(worker, condition, 't1' )) t2 = threading.thread(target = functools.partial(worker, condition, 't2' )) t2.start() # 启动线程2 t1.start() # 启动线程1 time.sleep( 2 ) with condition: condition.notify( 1 ) # 按照fifo顺序(wait调用顺序),释放一个锁,并将其从等待列表中删除 time.sleep( 2 ) with condition: condition.notify( 1 ) # 按照fifo顺序(wait调用顺序),释放另一个锁,并将其从等待队列中删除 t1.join() # 主线程等待子线程结束 t2.join() # 主线程等待子线程结束 print ( 'all done' ) |
其输出为:
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...t2 - thread - 2 - true ...t1 - thread - 1 - true wait returned in t2 wait returned in t1 all done |
其中wait方法要求获取到threading.condition对象中的锁(如果没有提供,默认使用一个可重入锁),然后自己创建一个新的普通锁(newlock),并获取这个newlock;之后调用_release_save方法释放threading.condition对象中的锁,让其它线程能够获取到;最后再次调用newlock上的acquire方法,由于在创建时已经acquire过,所以此线程会阻塞在此。而wait想要继续执行,必须等待其它线程将产生阻塞的这个newlock给release掉,当然,这就是notify方法的责任了。
notify方法接收一个数字n,从等待列表中取出相应数量的等待对象(让wait方法阻塞的锁对象),调用其release方法,让对应的wait方法能够返回。而notify_all方法仅仅就是将n设置为等待列表的总长度而已。
在理解了threading.condition对象中wait和notify的工作原理之后,我们就可以利用它们来实现两个线程交替打印字符的功能了:
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import threading import functools import time def print_a(state): while true: if state.closed: print ( 'close a' ) return print ( 'a' ) time.sleep( 2 ) state.set_current_is_a(true) state.wait_for_b() def print_b(state): while true: if state.closed: print ( 'close b' ) return state.wait_for_a() print ( 'b' ) time.sleep( 2 ) state.set_current_is_a(false) if __name__ = = '__main__' : class state( object ): """state used to coordinate multiple(two here) threads""" def __init__( self ): self .condition = threading.condition() self .current_is_a = false self .closed = false def wait_for_a( self ): with self .condition: while not self .current_is_a: self .condition.wait() def wait_for_b( self ): with self .condition: while self .current_is_a: self .condition.wait() def set_current_is_a( self , flag): self .current_is_a = flag with self .condition: self .condition.notify_all() state = state() t1 = threading.thread(target = functools.partial(print_a, state)) t2 = threading.thread(target = functools.partial(print_b, state)) try : t1.start() t2.start() t1.join() t2.join() except keyboardinterrupt: state.closed = true print ( 'closed' ) |
可以看到有两种类型的任务,一个用于打印字符a,一个用于打印字符b,我们的实现种让a先于b打印,所以在print_a中,先打印a,再设置当前字符状态并释放等待列表中的所有锁(set_current_is_a),如果没有这一步,current_is_a将一直是false,wait_for_b能够返回,而wait_for_a却永远不会返回,最终效果就是每隔两秒就打印一个字符a,而b永远不会打印。另一个副作用是如果wait_for_a永远不会返回,那print_b所在线程的关闭逻辑也就无法执行,最终会成为僵尸线程(这里的关闭逻辑只用作示例,生产环境需要更加完善的关闭机制)。
考虑另一种情况,print_a种将set_current_is_a和wait_for_b交换一下位置会怎么样。从观察到的输出我们看到,程序首先输出了一个字符a,以后,每隔2秒钟,就会同时输出a和b,而不是交替输出。原因在于,由于current_is_a还是false,我们先调用的wait_for_b其会立即返回,之后调用set_current_is_a,将current_is_a设置为true,并释放所有的阻塞wait的锁(notify_all),这个过程中没有阻塞,print_a紧接着进入了下一个打印循环;与此同时,print_b中的wait_for_a也返回了,进入到b的打印循环,故最终我们看到a和b总是一起打印。
可见对于threading.condition的使用需要多加小心,要注意逻辑上的严谨性。
附一个队列版本:
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import threading import functools import time from queue import queue def print_a(q_a, q_b): while true: char_a = q_a.get() if char_a = = 'closed' : return print (char_a) time.sleep( 2 ) q_b.put( 'b' ) def print_b(q_a, q_b): while true: char_b = q_b.get() if char_b = = 'closed' : return print (char_b) time.sleep( 2 ) q_a.put( 'a' ) if __name__ = = '__main__' : q_a = queue() q_b = queue() t1 = threading.thread(target = functools.partial(print_a, q_a, q_b)) t2 = threading.thread(target = functools.partial(print_b, q_a, q_b)) try : t1.start() t2.start() q_a.put( 'a' ) t1.join() t2.join() except keyboardinterrupt: q_a.put( 'closed' ) q_b.put( 'closed' ) print ( 'done' ) |
队列版本逻辑更清晰,更不容易出错,实际应用中应该选用队列。
附一个协程版本(python 3.5+):
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import time import asyncio async def print_a(): while true: print ( 'a' ) time.sleep( 2 ) # simulate the cpu block time await asyncio.sleep( 0 ) # release control to event loop async def print_b(): while true: print ( 'b' ) time.sleep( 2 ) # simulate the cpu block time await asyncio.sleep( 0 ) # release control to event loop async def main(): await asyncio.wait([print_a(), print_b()]) if __name__ = = '__main__' : loop = asyncio.get_event_loop() loop.run_until_complete(main()) |
协程的运行需要依附于一个事件循环(select/poll/epoll/kqueue),通过async def将一个函数定义为协程,通过await主动让渡控制权,通过相互让渡控制权完成交替打印字符。整个程序运行于一个线程中,这样就没有线程间协调的工作,仅仅是控制权的让渡逻辑。对于io密集型操作,而没有明显的cpu阻塞(计算复杂,以致出现明显的延时,比如复杂加解密算法)的情况下非常合适。
附一个java版本:
printmain类,用于管理和协调打印a和打印b的两个线程:
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package com.cuttyfox.tests. self .version1; import java.util.concurrent.executorservice; import java.util.concurrent.executors; import java.util.concurrent.timeunit; public class printmain { private boolean currentisa = false; public synchronized void waitingforprintinga() throws interruptedexception { while (this.currentisa = = false) { wait(); } } public synchronized void waitingforprintingb() throws interruptedexception { while (this.currentisa = = true) { wait(); } } public synchronized void setcurrentisa(boolean flag) { this.currentisa = flag; notifyall(); } public static void main(string[] args) throws exception { printmain state = new printmain(); executorservice executorservice = executors.newcachedthreadpool(); executorservice.execute(new printb(state)); executorservice.execute(new printa(state)); executorservice.shutdown(); executorservice.awaittermination( 10 , timeunit.seconds); system.out.println( "done" ); system.exit( 0 ); } } |
打印a的线程(首先打印a):
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package com.cuttyfox.tests. self .version1; import java.util.concurrent.timeunit; public class printa implements runnable{ private printmain state; public printa(printmain state) { this.state = state; } public void run() { try { while (!thread.interrupted()){ system.out.println( "print a" ); timeunit.seconds.sleep( 1 ); this.state.setcurrentisa(true); this.state.waitingforprintingb(); } } catch (interruptedexception e) { system.out.println( "exit through interrupting." ); } } } |
打印b的线程:
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package com.cuttyfox.tests. self .version1; import java.util.concurrent.timeunit; public class printb implements runnable{ private printmain state; public printb(printmain state) { this.state = state; } public void run() { try { while (!thread.interrupted()) { this.state.waitingforprintinga(); system.out.println( "print b" ); timeunit.seconds.sleep( 1 ); this.state.setcurrentisa(false); } } catch (interruptedexception e) { system.out.println( "exit through interrupting." ); } } } |
java对象本身有对象锁,故这里没有像python中那样需要显式通过创建一个condition对象来得到一把锁。
使用python实现交替打印abcdef的过程:
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import threading import time import functools from collections import deque letters = [ chr (code) for code in range ( 97 , 97 + 6 )] length = len (letters) class state( object ): def __init__( self ): self .condition = threading.condition() self .index_value = 0 def set_next_index( self , index): with self .condition: self .index_value = index self .condition.notify_all() def wait_for( self , index_value): with self .condition: while not self .index_value = = index_value: self .condition.wait() def print_letter(state: state, wait_ident: int ): print ( 'got: {}!' . format (wait_ident)) while true: state.wait_for(wait_ident) time.sleep( 2 ) print (letters[state.index_value]) print ( 'print: {} and set next: {}' . format (state.index_value, (state.index_value + 1 ) % length )) state.set_next_index((state.index_value + 1 ) % length) state = state() d = deque() d.extend( range (length)) d.rotate( 1 ) print (d) threads = [] for wait_ident in d: t = threading.thread(target = functools.partial(print_letter, state, wait_ident)) threads.append(t) for thread in threads: thread.start() for thread in threads: thread.join() |
以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持服务器之家。
原文链接:https://blog.csdn.net/cnweike/article/details/80939225