asyncio 队列的设计类似于类在
queue
模块。尽管 asyncio 队列不是线程安全的，但它们是为用于 async/await 代码专门设计的。
注意，asyncio 队列的方法没有
timeout
参数；使用
asyncio.wait_for()
函数采用超时做队列操作。
另请参阅 范例 以下章节。
FIFO (先进先出) 队列。
若
maxsize
is less than or equal to zero, the queue size is infinite. If it is an integer greater than
0
，那么
await put()
blocks when the queue reaches
maxsize
until an item is removed by
get()
.
不像标准库线程化
queue
, the size of the queue is always known and can be returned by calling the
qsize()
方法。
3.10 版改变： 移除 loop 参数。
此类是 非线程安全 .
队列中允许的项数。
返回
True
若队列为空，
False
否则。
Remove and return an item from the queue. If queue is empty, wait until an item is available.
返回项若立即可用，否则引发
QueueEmpty
.
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 an item into the queue. If the queue is full, wait until a free slot is available before adding the item.
返回队列中的项数。
Indicate that a formerly enqueued task is complete.
Used by queue consumers. For each
get()
用于抓取任务，后续调用
task_done()
tells the queue that the processing on the task is complete.
若
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).
引发
ValueError
if called more times than there were items placed in the queue.
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).
此异常被引发当
get_nowait()
方法被空队列所调用。
异常被引发当
put_nowait()
method is called on a queue that has reached its
maxsize
.
Queue 可以用于在几个并发任务之间分发工作量：
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())
