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queue — A synchronized queue cla

queue — A synchronized queue cla

作者: rebirth_2017 | 来源:发表于2017-05-24 16:41 被阅读48次

    1 队列简介

    The Queue module has been renamed to queue in Python 3.0. The 2to3 tool will automatically adapt imports when converting your sources to 3.0.

    队列模块(Queue module)实现了多生产者,消费者队列。在多线程编程中,多线程需要信息交互时,特别有用!它内部还对需要的锁进行了实现。

    **The Queue module implements multi-producer, multi-consumer queues. It is especially useful in threaded programming when information must be exchanged safely between multiple threads. **The Queue class in this module implements all the required locking semantics. It depends on the availability of thread support in Python; see the threading module.

    队列有三种形式,分别为:FIFO,LIFO和优先队列。

    Implements three types of queue whose only difference is the order that the entries are retrieved. In a FIFO queue, the first tasks added are the first retrieved. In a LIFO queue, the most recently added entry is the first retrieved (operating like a stack). With a priority queue, the entries are kept sorted (using the heapq module) and the lowest valued entry is retrieved first.

    2 Queue模块中的主要类和异常处理

    The Queue module defines the following classes and exceptions:

    2.1 class Queue.Queue(maxsize=0)

    生成FIFO队列。maxsize为队列空间的上限,为空则队列空间无限大。

    Constructor for a FIFO queue. maxsize is an integer that sets the upperbound limit on the number of items that can be placed in the queue. Insertion will block once this size has been reached, until queue items are consumed. If maxsize is less than or equal to zero, the queue size is infinite.

    2.2 class Queue.LifoQueue(maxsize=0)

    生成LIFO队列。其他与Queue.Queue相同。

    Constructor for a LIFO queue. maxsize is an integer that sets the upperbound limit on the number of items that can be placed in the queue. Insertion will block once this size has been reached, until queue items are consumed. If maxsize is less than or equal to zero, the queue size is infinite.

    2.3 class Queue.PriorityQueue(maxsize=0)

    生成priority优先队列。其他与Queue.Queue相同。

    Constructor for a priority queue. maxsize is an integer that sets the upperbound limit on the number of items that can be placed in the queue. Insertion will block once this size has been reached, until queue items are consumed. If maxsize is less than or equal to zero, the queue size is infinite.

    The lowest valued entries are retrieved first (the lowest valued entry is the one returned by sorted(list(entries))[0]). A typical pattern for entries is a tuple in the form: (priority_number, data).

    2.4 异常exception

    • ** exception Queue.Empty ** 读空队列异常。
      Exception raised when non-blocking get() (or get_nowait()) is called on a Queue object which is empty.

    • **exception Queue.Full ** 写满队列异常。
      Exception raised when non-blocking put() (or put_nowait()) is called on a Queue object which is full.

    3 Queue Objects

    Queue objects (Queue, LifoQueue, or PriorityQueue) provide the public methods described below.

    Queue.qsize()
    Return the approximate size of the queue. Note, qsize() > 0 doesn’t guarantee that a subsequent get() will not block, nor will qsize() < maxsize guarantee that put() will not block.
    Queue.empty()
    Return True if the queue is empty, False otherwise. If empty() returns True it doesn’t guarantee that a subsequent call to put() will not block. Similarly, if empty() returns False it doesn’t guarantee that a subsequent call to get() will not block.
    Queue.full()
    Return True if the queue is full, False otherwise. If full() returns True it doesn’t guarantee that a subsequent call to get() will not block. Similarly, if full() returns False it doesn’t guarantee that a subsequent call to put() will not block.
    Queue.put(item[, block[, timeout]])
    Put item into the queue. If optional args block is true and timeout is None (the default), block if necessary until a free slot is available. If timeout is a positive number, it blocks at most timeout seconds and raises the Full exception if no free slot was available within that time. Otherwise (block is false), put an item on the queue if a free slot is immediately available, else raise the Full exception (timeout is ignored in that case).

    New in version 2.3: The timeout parameter.

    Queue.put_nowait(item)
    Equivalent to put(item, False).
    Queue.get([block[, timeout]])
    Remove and return an item from the queue. If optional args block is true and timeout is None (the default), block if necessary until an item is available. If timeout is a positive number, it blocks at most timeout seconds and raises the Empty exception if no item was available within that time. Otherwise (block is false), return an item if one is immediately available, else raise the Empty exception (timeout is ignored in that case).

    New in version 2.3: The timeout parameter.

    Queue.get_nowait()
    Equivalent to get(False).
    Two methods are offered to support tracking whether enqueued tasks have been fully processed by daemon consumer threads.

    Queue.task_done()
    Indicate that a formerly enqueued task is complete. Used by queue consumer threads. For each get() used to fetch a task, a subsequent call to task_done() tells the queue that the processing on the task is complete.

    If a join() is currently blocking, it will resume when all items have been processed (meaning that a task_done() call was received for every item that had been put() into the queue).

    Raises a ValueError if called more times than there were items placed in the queue.

    New in version 2.5.

    Queue.join()
    Blocks until all items in the queue have been gotten and processed.

    The count of unfinished tasks goes up whenever an item is added to the queue. The count goes down whenever a consumer thread calls task_done() to indicate that the item was retrieved and all work on it is complete. When the count of unfinished tasks drops to zero, join() unblocks.

    New in version 2.5.

    Example of how to wait for enqueued tasks to be completed:

    def worker():
    while True:
    item = q.get()
    do_work(item)
    q.task_done()

    q = Queue()
    for i in range(num_worker_threads):
    t = Thread(target=worker)
    t.daemon = True
    t.start()

    for item in source():
    q.put(item)

    q.join() # block until all tasks are done

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