asyncio
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.
See also the Examples section below.
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 <asyncio-multithreading>
.
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
.
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
.
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.
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 ~Queue.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 ~Queue.put
into the queue).
Raises ValueError
if called more times than there were items placed in the queue.
3.8 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 <whatsnew310-removed>
for more information.
A variant of Queue
; retrieves entries in priority order (lowest first).
Entries are typically tuples of the form (priority_number, data)
.
A variant of Queue
that retrieves most recently added entries first (last in, first out).
QueueEmpty
This exception is raised when the ~Queue.get_nowait
method is called on an empty queue.
QueueFull
Exception raised when the ~Queue.put_nowait
method is called on a queue that has reached its maxsize.
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())