queue — A synchronized queue class¶
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)
Constructor for an unbounded FIFO queue. Simple queues lack advanced functionality such as task tracking.
Exception raised when non-blocking get() (or get_nowait() ) is called on a Queue object which is empty.
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.
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.
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.
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).
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 .
Two methods are offered to support tracking whether enqueued tasks have been fully processed by daemon consumer threads.
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.
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')
SimpleQueue Objects¶
SimpleQueue objects provide the public methods described below.
Return the approximate size of the queue. Note, qsize() > 0 doesn’t guarantee that a subsequent get() will not block.
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.
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).
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.
Queues¶
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.
Queue¶
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.
Changed in version 3.10: Removed the loop parameter.
Number of items allowed in the queue.
Return True if the queue is empty, False otherwise.
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 .
Remove and return an item from the queue. If queue is empty, wait until an item is available.
Return an item if one is immediately available, else raise 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.
Put an item into the queue without blocking.
If no free slot is immediately available, raise QueueFull .
Return the number of items in the queue.
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.
Priority Queue¶
A variant of Queue ; retrieves entries in priority order (lowest first).
Entries are typically tuples of the form (priority_number, data) .
LIFO Queue¶
A variant of Queue that retrieves most recently added entries first (last in, first out).
Exceptions¶
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())