queue — A synchronized queue class — Python 3.13.3 documentation
Description: Source code: Lib/queue.py The queue module implements multi-producer, multi-consumer queues. It is especially useful in threaded programming when information must be exchanged safely between multip...

# `queue` — A synchronized queue class

Source code: Lib/queue.py

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.

The module implements three types of queue, which differ only in the order in which 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.

Internally, those three types of queues use locks to temporarily block competing threads; however, they are not designed to handle reentrancy within a thread.

In addition, the module implements a “simple” FIFO queue type, `SimpleQueue`, whose specific implementation provides additional guarantees in exchange for the smaller functionality.

The `queue` module defines the following classes and exceptions:

class queue.Queue(maxsize=0)

  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=0)

  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.

class queue.PriorityQueue(maxsize=0)

  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 that would be returned by `min(entries)`). A typical pattern for entries is a tuple in the form: `(priority_number, data)`.

  If the data elements are not comparable, the data can be wrapped in a class that ignores the data item and only compares the priority number:

      from dataclasses import dataclass, field
      from typing import Any

      @dataclass(order=True)
      class PrioritizedItem:
          priority: int
          item: Any=field(compare=False)

class queue.SimpleQueue

  Constructor for an unbounded FIFO queue. Simple queues lack advanced functionality such as task tracking.

  Added in version 3.7.

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.

exception queue.ShutDown

  Exception raised when `put()` or `get()` is called on a `Queue` object which has been shut down.

  Added in version 3.13.

## 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=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).

  Raises `ShutDown` if the queue has been shut down.

Queue.put_nowait(item)

  Equivalent to `put(item, block=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).

  Prior to 3.0 on POSIX systems, and for all versions on Windows, if block is true and timeout is `None`, this operation goes into an uninterruptible wait on an underlying lock. This means that no exceptions can occur, and in particular a SIGINT will not trigger a `KeyboardInterrupt`.

  Raises `ShutDown` if the queue has been shut down and is empty, or if the queue has been shut down immediately.

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).

  `shutdown(immediate=True)` calls `task_done()` for each remaining item in the queue.

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

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.

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

    import threading
    import queue

    q = queue.Queue()

    def worker():
        while True:
            item = q.get()
            print(f'Working on {item}')
            print(f'Finished {item}')
            q.task_done()

    # Turn-on the worker thread.
    threading.Thread(target=worker, daemon=True).start()

    # Send thirty task requests to the worker.
    for item in range(30):
        q.put(item)

    # Block until all tasks are done.
    q.join()
    print('All work completed')

### Terminating queues

`Queue` objects can be made to prevent further interaction by shutting them down.

Queue.shutdown(immediate=False)

  Shut down the queue, making `get()` and `put()` raise `ShutDown`.

  By default, `get()` on a shut down queue will only raise once the queue is empty. Set immediate to true to make `get()` raise immediately instead.

  All blocked callers of `put()` and `get()` will be unblocked. If immediate is true, a task will be marked as done for each remaining item in the queue, which may unblock callers of `join()`.

  Added in version 3.13.

## SimpleQueue Objects

`SimpleQueue` objects provide the public methods described below.

SimpleQueue.qsize()

  Return the approximate size of the queue. Note, qsize() > 0 doesn’t guarantee that a subsequent get() will not block.

SimpleQueue.empty()

  Return `True` if the queue is empty, `False` otherwise. If empty() returns `False` it doesn’t guarantee that a subsequent call to get() will not block.

SimpleQueue.put(item, block=True, timeout=None)

  Put item into the queue. The method never blocks and always succeeds (except for potential low-level errors such as failure to allocate memory). The optional args block and timeout are ignored and only provided for compatibility with `Queue.put()`.

  CPython implementation detail: This method has a C implementation which is reentrant. That is, a `put()` or `get()` call can be interrupted by another `put()` call in the same thread without deadlocking or corrupting internal state inside the queue. This makes it appropriate for use in destructors such as `__del__` methods or `weakref` callbacks.

SimpleQueue.put_nowait(item)

  Equivalent to `put(item, block=False)`, provided for compatibility with `Queue.put_nowait()`.

SimpleQueue.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).

SimpleQueue.get_nowait()

  Equivalent to `get(False)`.

See also

Class `multiprocessing.Queue`

  A queue class for use in a multi-processing (rather than multi-threading) context.

`collections.deque` is an alternative implementation of unbounded queues with fast atomic `append()` and `popleft()` operations that do not require locking and also support indexing.