用Python的线程来解决生产者消费问题的示例

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我们将使用Python线程来解决Python中的生产者―消费者问题。这个问题完全不像他们在学校中说的那么难。

如果你对生产者―消费者问题有了解,看这篇博客会更有意义。

为什么要关心生产者―消费者问题:

当我们在使用线程时,你可以学习以下的线程概念:

我假设你已经有这些基本概念:线程、竞态条件,以及如何解决静态条件(例如使用lock)。否则的话,你建议你去看我上一篇文章basics of Threads

引用维基百科:

生产者的工作是产生一块数据,放到buffer中,如此循环。与此同时,消费者在消耗这些数据(例如从buffer中把它们移除),每次一块。

这里的关键词是"同时"。所以生产者和消费者是并发运行的,我们需要对生产者和消费者做线程分离。


    from threading import Thread

    class ProducerThread(Thread):
      def run(self):
        pass

    class ConsumerThread(Thread):
      def run(self):
        pass

再次引用维基百科:

这个为描述了两个共享固定大小缓冲队列的进程,即生产者和消费者。

假设我们有一个全局变量,可以被生产者和消费者线程修改。生产者产生数据并把它加入到队列。消费者消耗这些数据(例如把它移出)。

queue = []

在刚开始,我们不会设置固定大小的条件,而在实际运行时加入(指下述例子)。

一开始带bug的程序:


    from threading import Thread, Lock
    import time
    import random

    queue = []
    lock = Lock()

    class ProducerThread(Thread):
      def run(self):
        nums = range(5) #Will create the list [0, 1, 2, 3, 4]
        global queue
        while True:
          num = random.choice(nums) #Selects a random number from list [0, 1, 2, 3, 4]
          lock.acquire()
          queue.append(num)
          print "Produced", num
          lock.release()
          time.sleep(random.random())

    class ConsumerThread(Thread):
      def run(self):
        global queue
        while True:
          lock.acquire()
          if not queue:
            print "Nothing in queue, but consumer will try to consume"
          num = queue.pop(0)
          print "Consumed", num
          lock.release()
          time.sleep(random.random())

    ProducerThread().start()
    ConsumerThread().start()

运行几次并留意一下结果。如果程序在IndexError异常后并没有自动结束,用Ctrl+Z结束运行。

样例输出:


    Produced 3
    Consumed 3
    Produced 4
    Consumed 4
    Produced 1
    Consumed 1
    Nothing in queue, but consumer will try to consume
    Exception in thread Thread-2:
    Traceback (most recent call last):
     File "/usr/lib/python2.7/threading.py", line 551, in __bootstrap_inner
      self.run()
     File "producer_consumer.py", line 31, in run
      num = queue.pop(0)
    IndexError: pop from empty list

解释:

我们把这个实现作为错误行为(wrong behavior)。

什么是正确行为?

当队列中没有任何数据的时候,消费者应该停止运行并等待(wait),而不是继续尝试进行消耗。而当生产者在队列中加入数据之后,应该有一个渠道去告诉(notify)消费者。然后消费者可以再次从队列中进行消耗,而IndexError不再出现。

关于条件

条件(condition)可以让一个或多个线程进入wait,直到被其他线程notify。参考:?http://docs.python.org/2/library/threading.html#condition-objects

这就是我们所需要的。我们希望消费者在队列为空的时候wait,只有在被生产者notify后恢复。生产者只有在往队列中加入数据后进行notify。因此在生产者notify后,可以确保队列非空,因此消费者消费时不会出现异常。

condition的acquire()和release()方法内部调用了lock的acquire()和release()。所以我们可以用condiction实例取代lock实例,但lock的行为不会改变。
生产者和消费者需要使用同一个condition实例, 保证wait和notify正常工作。

重写消费者代码:


    from threading import Condition

    condition = Condition()

    class ConsumerThread(Thread):
      def run(self):
        global queue
        while True:
          condition.acquire()
          if not queue:
            print "Nothing in queue, consumer is waiting"
            condition.wait()
            print "Producer added something to queue and notified the consumer"
          num = queue.pop(0)
          print "Consumed", num
          condition.release()
          time.sleep(random.random())

重写生产者代码:


    class ProducerThread(Thread):
      def run(self):
        nums = range(5)
        global queue
        while True:
          condition.acquire()
          num = random.choice(nums)
          queue.append(num)
          print "Produced", num
          condition.notify()
          condition.release()
          time.sleep(random.random())

样例输出:


    Produced 3
    Consumed 3
    Produced 1
    Consumed 1
    Produced 4
    Consumed 4
    Produced 3
    Consumed 3
    Nothing in queue, consumer is waiting
    Produced 2
    Producer added something to queue and notified the consumer
    Consumed 2
    Nothing in queue, consumer is waiting
    Produced 2
    Producer added something to queue and notified the consumer
    Consumed 2
    Nothing in queue, consumer is waiting
    Produced 3
    Producer added something to queue and notified the consumer
    Consumed 3
    Produced 4
    Consumed 4
    Produced 1
    Consumed 1

解释:

为队列增加大小限制

生产者不能向一个满队列继续加入数据。

它可以用以下方式来实现:

最终程序如下:


    from threading import Thread, Condition
    import time
    import random

    queue = []
    MAX_NUM = 10
    condition = Condition()

    class ProducerThread(Thread):
      def run(self):
        nums = range(5)
        global queue
        while True:
          condition.acquire()
          if len(queue) == MAX_NUM:
            print "Queue full, producer is waiting"
            condition.wait()
            print "Space in queue, Consumer notified the producer"
          num = random.choice(nums)
          queue.append(num)
          print "Produced", num
          condition.notify()
          condition.release()
          time.sleep(random.random())

    class ConsumerThread(Thread):
      def run(self):
        global queue
        while True:
          condition.acquire()
          if not queue:
            print "Nothing in queue, consumer is waiting"
            condition.wait()
            print "Producer added something to queue and notified the consumer"
          num = queue.pop(0)
          print "Consumed", num
          condition.notify()
          condition.release()
          time.sleep(random.random())

    ProducerThread().start()
    ConsumerThread().start()

样例输出:


    Produced 0
    Consumed 0
    Produced 0
    Produced 4
    Consumed 0
    Consumed 4
    Nothing in queue, consumer is waiting
    Produced 4
    Producer added something to queue and notified the consumer
    Consumed 4
    Produced 3
    Produced 2
    Consumed 3

更新:
很多网友建议我在lock和condition下使用Queue来代替使用list。我同意这种做法,但我的目的是展示Condition,wait()和notify()如何工作,所以使用了list。

以下用Queue来更新一下代码。

Queue封装了Condition的行为,如wait(),notify(),acquire()。

现在不失为一个好机会读一下Queue的文档(http://docs.python.org/2/library/queue.html)。

更新程序:


    from threading import Thread
    import time
    import random
    from Queue import Queue

    queue = Queue(10)

    class ProducerThread(Thread):
      def run(self):
        nums = range(5)
        global queue
        while True:
          num = random.choice(nums)
          queue.put(num)
          print "Produced", num
          time.sleep(random.random())

    class ConsumerThread(Thread):
      def run(self):
        global queue
        while True:
          num = queue.get()
          queue.task_done()
          print "Consumed", num
          time.sleep(random.random())

    ProducerThread().start()
    ConsumerThread().start()

解释:

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