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  • Python多线程

    Python使用多线程有两种方式:
      函数或者用类来包装线程对象

      函数式:调用thread模块中的start_new_thread()函数来产生新线程
        thread.start_new_thread(function, args[, kwargs])

          function:线程函数
          args:线程参数,必须是tuple类型
          kwargs:可选参数

      线程模块:
        Python提供两个标准库thread和threading对线程的支持
        thread提供了低级别、原始的线程以及一个简单的锁
        threading模块提供的其他方法:
          threading.currentThread():
          threading.enumerate():
          threading.activeCount():

          线程模块Thread类也可以处理线程,提供方法:
            run():
            start():
            join([time]):
            isAlive():
            getName():
            setName():

    线程锁:
      使用Thread对象的Lock和Rlock可以实现简单的线程同步
      这两个对象都有acquire方法和release方法,

    实例:

    #!/usr/bin/python
    # -*- coding: UTF-8 -*-
     
    import threading
    import time
     
    class myThread (threading.Thread):
        def __init__(self, threadID, name, counter):
            threading.Thread.__init__(self)
            self.threadID = threadID
            self.name = name
            self.counter = counter
        def run(self):
            print "Starting " + self.name
           # 获得锁,成功获得锁定后返回True
           # 可选的timeout参数不填时将一直阻塞直到获得锁定
           # 否则超时后将返回False
            threadLock.acquire()
            print_time(self.name, self.counter, 3)
            # 释放锁
            threadLock.release()
     
    def print_time(threadName, delay, counter):
        while counter:
            time.sleep(delay)
            print "%s: %s" % (threadName, time.ctime(time.time()))
            counter -= 1
     
    threadLock = threading.Lock()
    threads = []
     
    # 创建新线程
    thread1 = myThread(1, "Thread-1", 1)
    thread2 = myThread(2, "Thread-2", 2)
     
    # 开启新线程
    thread1.start()
    thread2.start()
     
    # 添加线程到线程列表
    threads.append(thread1)
    threads.append(thread2)
     
    # 等待所有线程完成
    for t in threads:
        t.join()
    print "Exiting Main Thread"




    线程优先级队列Queue
      Queue模块提供了同步的、线程安全的队列类
        实现了锁,能够在多线程中直接使用,可以使用队列来实现线程间同步

    Queue模块中的常用方法:

    • Queue.qsize() 返回队列的大小
    • Queue.empty() 如果队列为空,返回True,反之False
    • Queue.full() 如果队列满了,返回True,反之False
    • Queue.full 与 maxsize 大小对应
    • Queue.get([block[, timeout]])获取队列,timeout等待时间
    • Queue.get_nowait() 相当Queue.get(False)
    • Queue.put(item) 写入队列,timeout等待时间
    • Queue.put_nowait(item) 相当Queue.put(item, False)
    • Queue.task_done() 在完成一项工作之后,Queue.task_done()函数向任务已经完成的队列发送一个信号
    • Queue.join() 实际上意味着等到队列为空,再执行别的操作

    实例:

    #!/usr/bin/python
    # -*- coding: UTF-8 -*-
     
    import Queue
    import threading
    import time
     
    exitFlag = 0
     
    class myThread (threading.Thread):
        def __init__(self, threadID, name, q):
            threading.Thread.__init__(self)
            self.threadID = threadID
            self.name = name
            self.q = q
        def run(self):
            print "Starting " + self.name
            process_data(self.name, self.q)
            print "Exiting " + self.name
     
    def 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
     
    # 创建新线程
    for tName in threadList:
        thread = myThread(threadID, tName, workQueue)
        thread.start()
        threads.append(thread)
        threadID += 1
     
    # 填充队列
    queueLock.acquire()
    for word in nameList:
        workQueue.put(word)
    queueLock.release()
     
    # 等待队列清空
    while not workQueue.empty():
        pass
     
    # 通知线程是时候退出
    exitFlag = 1
     
    # 等待所有线程完成
    for t in threads:
        t.join()
    print "Exiting Main Thread"
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  • 原文地址:https://www.cnblogs.com/djoker/p/9438308.html
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