queue — A synchronized queue class
Note
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.
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.
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.
The Queue module defines the following classes and exceptions:
-
class Queue.Queue(maxsize)
- 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.
-
class Queue.LifoQueue(maxsize)
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.
New in version 2.6.
-
class Queue.PriorityQueue(maxsize)
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).
New in version 2.6.
-
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 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.setDaemon(True)
t.start()
for item in source():
q.put(item)
q.join() # block until all tasks are done