Python多线程
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Python多线程
线程有时称为轻量级进程,他们并不需要多大的内存开销,他们关心的不是过程便宜.
一个线程都有一个开始,执行顺序,并得出结论。它有一个指令指针,保持它的上下文内正在运行的跟踪.
它可以是抢占(中断)
它可以暂时搁置(又称睡眠),而其他线程正在运行 - 这被称为产量yielding.
启动一个新线程:
如要产生另一个线程,你需要调用线程模块,可用下面的方法:
thread.start_new_thread ( function, args[, kwargs] )
调用此方法实现了快速和有效的方式,在Linux和Windows中创建新的线程.
方法调用立即返回,并在子线程开始,并调用与传递agrs的列表函数。当函数返回时,线程终止.
这里的args是一个参数的元组;使用一个空的元组没有传递任何参数的函数调用。 kwargs是一个可选关键字参数字典.
例子:
#!/usr/bin/pythonimport threadimport time# Define a function for the threaddef print_time( threadName, delay): count = 0 while count < 5: time.sleep(delay) count += 1 print "%s: %s" % ( threadName, time.ctime(time.time()) )# Create two threads as followstry: thread.start_new_thread( print_time, ("Thread-1", 2, ) ) thread.start_new_thread( print_time, ("Thread-2", 4, ) )except: print "Error: unable to start thread"while 1: pass
This would produce following result:
Thread-1: Thu Jan 22 15:42:17 2009Thread-1: Thu Jan 22 15:42:19 2009Thread-2: Thu Jan 22 15:42:19 2009Thread-1: Thu Jan 22 15:42:21 2009Thread-2: Thu Jan 22 15:42:23 2009Thread-1: Thu Jan 22 15:42:23 2009Thread-1: Thu Jan 22 15:42:25 2009Thread-2: Thu Jan 22 15:42:27 2009Thread-2: Thu Jan 22 15:42:31 2009Thread-2: Thu Jan 22 15:42:35 2009
虽然它是非常有效的为低级别的线程,但线程模块是非常有限的相比,新的线程模块.
Threading 模块:
Python 2.4中包含的新的线程模块提供更强大,比线程的线程模块高层的支持,在上一节讨论.
threading模块暴露所有的线程模块的方法,并提供一些额外的方法:
threading.activeCount():返回线程对象的数量处于活动状态的。.
threading.currentThread(): 返回调用者的线程控制线程对象的数量.
threading.enumerate(): 返回一个所有当前处于活动状态线程对象的名单.
在另外的方法,线程模块实现线程Thread类。 Thread类提供的方法如下:
run(): run()方法是一个线程的入口点.
start(): start()方法启动一个线程调用run方法.
join([time]): join() 等待线程终止.
isAlive(): isAlive()方法检查是否仍在执行一个线程.
getName(): getName()方法返回一个线程的名称.
setName(): setName()方法设置一个线程的名称.
创建线程使用线程模块:
为了实现一个新的线程使用线程模块,你必须做到以下几点:
定义一个新的Thread类的子类.
覆盖 __init__(self [,args])方法来添加额外的参数.
然后重写方法来实现的线程应该做的,什么时候开始 run(self [,args]) .
一旦你创建新的线程子类,你可以创建它的一个实例,然后启动一个新的线程调用的start()或run()方法.
例子:
#!/usr/bin/pythonimport threadingimport timeexitFlag = 0class myThread (threading.Thread): def __init__(self, threadID, name, counter): self.threadID = threadID self.name = name self.counter = counter threading.Thread.__init__(self) def run(self): print "Starting " + self.name print_time(self.name, self.counter, 5) print "Exiting " + self.namedef print_time(threadName, delay, counter): while counter: if exitFlag: thread.exit() time.sleep(delay) print "%s: %s" % (threadName, time.ctime(time.time())) counter -= 1# Create new threadsthread1 = myThread(1, "Thread-1", 1)thread2 = myThread(2, "Thread-2", 2)# Start new Threadsthread1.start()thread2.run()while thread2.isAlive(): if not thread1.isAlive(): exitFlag = 1 passprint "Exiting Main Thread"
这将产生以下结果:
Starting Thread-2Starting Thread-1Thread-1: Thu Jan 22 15:53:05 2009Thread-2: Thu Jan 22 15:53:06 2009Thread-1: Thu Jan 22 15:53:06 2009Thread-1: Thu Jan 22 15:53:07 2009Thread-2: Thu Jan 22 15:53:08 2009Thread-1: Thu Jan 22 15:53:08 2009Thread-1: Thu Jan 22 15:53:09 2009Exiting Thread-1Thread-2: Thu Jan 22 15:53:10 2009Thread-2: Thu Jan 22 15:53:12 2009Thread-2: Thu Jan 22 15:53:14 2009Exiting Thread-2Exiting Main Thread
同步线程:
与Python提供的线程模块,包括一个简单的实现锁定机制,将允许您同步线程。创建一个新的锁被调用的lock()方法,返回新锁.
获得(阻塞)新的锁定对象的方法将被用于迫使线程同步运行。阻塞的可选参数,使您能够控制是否线程将等待获得锁.
如果阻塞设置为0时,该线程将返回0值立即如果锁不能获得,1,如果锁被获得。如果阻塞设置为1时,该线程将被阻塞,等待被释放的锁.
新锁对象的release()方法将被用于它不再需要时释放锁.
例子:
#!/usr/bin/pythonimport threadingimport timeclass myThread (threading.Thread): def __init__(self, threadID, name, counter): self.threadID = threadID self.name = name self.counter = counter threading.Thread.__init__(self) def run(self): print "Starting " + self.name # Get lock to synchronize threads threadLock.acquire() print_time(self.name, self.counter, 3) # Free lock to release next thread threadLock.release()def print_time(threadName, delay, counter): while counter: time.sleep(delay) print "%s: %s" % (threadName, time.ctime(time.time())) counter -= 1threadLock = threading.Lock()threads = []# Create new threadsthread1 = myThread(1, "Thread-1", 1)thread2 = myThread(2, "Thread-2", 2)# Start new Threadsthread1.start()thread2.start()# Add threads to thread listthreads.append(thread1)threads.append(thread2)# Wait for all threads to completefor t in threads: t.join()print "Exiting Main Thread"
这将产生以下结果:
Starting Thread-1Starting Thread-2Thread01: Thu Jan 22 16:04:38 2009Thread01: Thu Jan 22 16:04:39 2009Thread01: Thu Jan 22 16:04:40 2009Thread02: Thu Jan 22 16:04:42 2009Thread02: Thu Jan 22 16:04:44 2009Thread02: Thu Jan 22 16:04:46 2009Exiting Main Thread
多线程优先级队列:
队列模块允许你创建一个新的队列对象,可容纳一个项目的具体数量。有以下方法来控制队列:
get(): get()移除并返回从队列中的一个项目。.
put(): put()把一个项目添加到队列中.
qsize() : qsize()返回当前队列中的项目数.
empty(): empty()返回True,如果队列为空,否则为false.
full(): full()返回True,如果队列已满,否则为false.
Example:
#!/usr/bin/pythonimport Queueimport threadingimport timeexitFlag = 0class myThread (threading.Thread): def __init__(self, threadID, name, q): self.threadID = threadID self.name = name self.q = q threading.Thread.__init__(self) def run(self): print "Starting " + self.name process_data(self.name, self.q) print "Exiting " + self.namedef process_data(threadName, q): while not exitFlag: queueLock.acquire() if not workQueue.empty(): data = q.get() queueLock.release() print "%s processing %s" % (threadName, data) else: queueLock.release() time.sleep(1)threadList = ["Thread-1", "Thread-2", "Thread-3"]nameList = ["One", "Two", "Three", "Four", "Five"]queueLock = threading.Lock()workQueue = Queue.Queue(10)threads = []threadID = 1# Create new threadsfor tName in threadList: thread = myThread(threadID, tName, workQueue) thread.start() threads.append(thread) threadID += 1# Fill the queuequeueLock.acquire()for word in nameList: workQueue.put(word)queueLock.release()# Wait for queue to emptywhile not workQueue.empty(): pass# Notify threads it's time to exitexitFlag = 1# Wait for all threads to completefor t in threads: t.join()print "Exiting Main Thread"
This would produce following result:
Starting Thread-2Starting Thread-1Starting Thread-3Thread-2 processing OneThread-1 processing TwoThread-3 processing ThreeThread-2 processing FourThread-1 processing FiveExiting Thread-3Exiting Thread-2Exiting Thread-1Exiting Main Thread
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