Queues¶

Source code: Lib/asyncio/queues.py

asyncio queues are designed to be similar to classes of the queue module. Although asyncio queues are not thread-safe, they are designed to be used specifically in async/await code.

Note that methods of asyncio queues don’t have a timeout parameter; use asyncio.wait_for() function to do queue operations with a timeout.

Queue¶

class asyncio.Queue(maxsize=0)¶

A first in, first out (FIFO) queue.

If maxsize is less than or equal to zero, the queue size is infinite. If it is an integer greater than 0, then await put() blocks when the queue reaches maxsize until an item is removed by get().

Unlike the standard library threading queue, the size of the queue is always known and can be returned by calling the qsize() method.

This class is not thread safe.

maxsize¶: Number of items allowed in the queue.

empty()¶: Return True if the queue is empty, False otherwise.

full()¶

Return True if there are maxsize items in the queue.

If the queue was initialized with maxsize=0 (the default), then full() never returns True.

coroutine get()¶: Remove and return an item from the queue. If queue is empty, wait until an item is available.

get_nowait()¶: Return an item if one is immediately available, else raise QueueEmpty.

coroutine join()¶

Block until all items in the queue have been received and processed.

The count of unfinished tasks goes up whenever an item is added to the queue. The count goes down whenever a consumer coroutine 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.

coroutine put(item)¶: Put an item into the queue. If the queue is full, wait until a free slot is available before adding the item.

put_nowait(item)¶

Put an item into the queue without blocking.

If no free slot is immediately available, raise QueueFull.

qsize()¶: Return the number of items in the queue.

task_done()¶

Indicate that a formerly enqueued task is complete.

Used by queue consumers. 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 ValueError if called more times than there were items placed in the queue.

Deprecated since version 3.8, removed in version 3.10: The loop parameter. This function has been implicitly getting the current running loop since 3.7. See What’s New in 3.10’s Removed section for more information.

Priority Queue¶

class asyncio.PriorityQueue¶

A variant of Queue; retrieves entries in priority order (lowest first).

Entries are typically tuples of the form (priority_number, data).

LIFO Queue¶

class asyncio.LifoQueue¶: A variant of Queue that retrieves most recently added entries first (last in, first out).

Exceptions¶

exception asyncio.QueueEmpty¶: This exception is raised when the get_nowait() method is called on an empty queue.

exception asyncio.QueueFull¶: Exception raised when the put_nowait() method is called on a queue that has reached its maxsize.

Examples¶

Queues can be used to distribute workload between several concurrent tasks:

import asyncio
import random
import time


async def worker(name, queue):
    while True:
        # Get a "work item" out of the queue.
        sleep_for = await queue.get()

        # Sleep for the "sleep_for" seconds.
        await asyncio.sleep(sleep_for)

        # Notify the queue that the "work item" has been processed.
        queue.task_done()

        print(f'{name} has slept for {sleep_for:.2f} seconds')


async def main():
    # Create a queue that we will use to store our "workload".
    queue = asyncio.Queue()

    # Generate random timings and put them into the queue.
    total_sleep_time = 0
    for _ in range(20):
        sleep_for = random.uniform(0.05, 1.0)
        total_sleep_time += sleep_for
        queue.put_nowait(sleep_for)

    # Create three worker tasks to process the queue concurrently.
    tasks = []
    for i in range(3):
        task = asyncio.create_task(worker(f'worker-{i}', queue))
        tasks.append(task)

    # Wait until the queue is fully processed.
    started_at = time.monotonic()
    await queue.join()
    total_slept_for = time.monotonic() - started_at

    # Cancel our worker tasks.
    for task in tasks:
        task.cancel()
    # Wait until all worker tasks are cancelled.
    await asyncio.gather(*tasks, return_exceptions=True)

    print('====')
    print(f'3 workers slept in parallel for {total_slept_for:.2f} seconds')
    print(f'total expected sleep time: {total_sleep_time:.2f} seconds')


asyncio.run(main())