• Python程序中的线程操作-线程队列


    Python程序中的线程操作-线程队列

    一、线程队列

    queue队列:使用import queue,用法与进程Queue一样

    queue is especially useful in threaded programming when information must be exchanged safely between multiple threads.

    二、先进先出

    class queue.Queue(maxsize=0)
    
    
    import queue
    
    q=queue.Queue()
    q.put('first')
    q.put('second')
    q.put('third')
    
    print(q.get())
    print(q.get())
    print(q.get())
    '''
    结果(先进先出):
    first
    second
    third
    '''
    

    三、后进先出

    class queue.LifoQueue(maxsize=0)
    
    
    import queue
    
    q=queue.LifoQueue()
    q.put('first')
    q.put('second')
    q.put('third')
    
    print(q.get())
    print(q.get())
    print(q.get())
    '''
    结果(后进先出):
    third
    second
    first
    '''
    

    四、存储数据时可设置优先级的队列

    class queue.PriorityQueue(maxsize=0)
    

    4.1 优先级队列

    import queue
    
    q=queue.PriorityQueue()
    #put进入一个元组,元组的第一个元素是优先级(通常是数字,也可以是非数字之间的比较),数字越小优先级越高
    q.put((20,'a'))
    q.put((10,'b'))
    q.put((30,'c'))
    
    print(q.get())
    print(q.get())
    print(q.get())
    '''
    结果(数字越小优先级越高,优先级高的优先出队):
    (10, 'b')
    (20, 'a')
    (30, 'c')
    '''
    

    定时器

    from threading import Timer
    import time
    
    
    def task():
        print("线程执行")
        time.sleep(2)
        print("线程结束")
    
    
    # 过了3s后开启了一个线程
    t = Timer(4, task)
    t.start()
    
    print(3)
    

    4.2 更多方法说明

    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).

    exception queue.Empty: Exception raised when non-blocking get() (or get_nowait()) is called on a Queue object which is empty.

    exception queue.Full: Exception raised when non-blocking put() (or put_nowait()) is called on a Queue object which is full.

    Queue.qsize()
    

    Queue.empty(): return True if empty

    Queue.full(): return True if full

    Queue.put(item, block=True, timeout=None): 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).

    Queue.put_nowait(item): Equivalent to put(item, False).

    Queue.get(block=True, timeout=None): 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).

    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.

    Queue.join(): block直到queue被消费完毕。

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  • 原文地址:https://www.cnblogs.com/randysun/p/12258396.html
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