# Copyright 2015 The Tornado Authors # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. """Asynchronous queues for coroutines. These classes are very similar to those provided in the standard library's `asyncio package `_. .. warning:: Unlike the standard library's `queue` module, the classes defined here are *not* thread-safe. To use these queues from another thread, use `.IOLoop.add_callback` to transfer control to the `.IOLoop` thread before calling any queue methods. """ import collections import datetime import heapq from tornado import gen, ioloop from tornado.concurrent import Future, future_set_result_unless_cancelled from tornado.locks import Event from typing import Union, TypeVar, Generic, Awaitable, Optional import typing if typing.TYPE_CHECKING: from typing import Deque, Tuple, Any # noqa: F401 _T = TypeVar("_T") __all__ = ["Queue", "PriorityQueue", "LifoQueue", "QueueFull", "QueueEmpty"] class QueueEmpty(Exception): """Raised by `.Queue.get_nowait` when the queue has no items.""" pass class QueueFull(Exception): """Raised by `.Queue.put_nowait` when a queue is at its maximum size.""" pass def _set_timeout( future: Future, timeout: Union[None, float, datetime.timedelta] ) -> None: if timeout: def on_timeout() -> None: if not future.done(): future.set_exception(gen.TimeoutError()) io_loop = ioloop.IOLoop.current() timeout_handle = io_loop.add_timeout(timeout, on_timeout) future.add_done_callback(lambda _: io_loop.remove_timeout(timeout_handle)) class _QueueIterator(Generic[_T]): def __init__(self, q: "Queue[_T]") -> None: self.q = q def __anext__(self) -> Awaitable[_T]: return self.q.get() class Queue(Generic[_T]): """Coordinate producer and consumer coroutines. If maxsize is 0 (the default) the queue size is unbounded. .. testcode:: import asyncio from tornado.ioloop import IOLoop from tornado.queues import Queue q = Queue(maxsize=2) async def consumer(): async for item in q: try: print('Doing work on %s' % item) await asyncio.sleep(0.01) finally: q.task_done() async def producer(): for item in range(5): await q.put(item) print('Put %s' % item) async def main(): # Start consumer without waiting (since it never finishes). IOLoop.current().spawn_callback(consumer) await producer() # Wait for producer to put all tasks. await q.join() # Wait for consumer to finish all tasks. print('Done') asyncio.run(main()) .. testoutput:: Put 0 Put 1 Doing work on 0 Put 2 Doing work on 1 Put 3 Doing work on 2 Put 4 Doing work on 3 Doing work on 4 Done In versions of Python without native coroutines (before 3.5), ``consumer()`` could be written as:: @gen.coroutine def consumer(): while True: item = yield q.get() try: print('Doing work on %s' % item) yield gen.sleep(0.01) finally: q.task_done() .. versionchanged:: 4.3 Added ``async for`` support in Python 3.5. """ # Exact type depends on subclass. Could be another generic # parameter and use protocols to be more precise here. _queue = None # type: Any def __init__(self, maxsize: int = 0) -> None: if maxsize is None: raise TypeError("maxsize can't be None") if maxsize < 0: raise ValueError("maxsize can't be negative") self._maxsize = maxsize self._init() self._getters = collections.deque([]) # type: Deque[Future[_T]] self._putters = collections.deque([]) # type: Deque[Tuple[_T, Future[None]]] self._unfinished_tasks = 0 self._finished = Event() self._finished.set() @property def maxsize(self) -> int: """Number of items allowed in the queue.""" return self._maxsize def qsize(self) -> int: """Number of items in the queue.""" return len(self._queue) def empty(self) -> bool: return not self._queue def full(self) -> bool: if self.maxsize == 0: return False else: return self.qsize() >= self.maxsize def put( self, item: _T, timeout: Optional[Union[float, datetime.timedelta]] = None ) -> "Future[None]": """Put an item into the queue, perhaps waiting until there is room. Returns a Future, which raises `tornado.util.TimeoutError` after a timeout. ``timeout`` may be a number denoting a time (on the same scale as `tornado.ioloop.IOLoop.time`, normally `time.time`), or a `datetime.timedelta` object for a deadline relative to the current time. """ future = Future() # type: Future[None] try: self.put_nowait(item) except QueueFull: self._putters.append((item, future)) _set_timeout(future, timeout) else: future.set_result(None) return future def put_nowait(self, item: _T) -> None: """Put an item into the queue without blocking. If no free slot is immediately available, raise `QueueFull`. """ self._consume_expired() if self._getters: assert self.empty(), "queue non-empty, why are getters waiting?" getter = self._getters.popleft() self.__put_internal(item) future_set_result_unless_cancelled(getter, self._get()) elif self.full(): raise QueueFull else: self.__put_internal(item) def get( self, timeout: Optional[Union[float, datetime.timedelta]] = None ) -> Awaitable[_T]: """Remove and return an item from the queue. Returns an awaitable which resolves once an item is available, or raises `tornado.util.TimeoutError` after a timeout. ``timeout`` may be a number denoting a time (on the same scale as `tornado.ioloop.IOLoop.time`, normally `time.time`), or a `datetime.timedelta` object for a deadline relative to the current time. .. note:: The ``timeout`` argument of this method differs from that of the standard library's `queue.Queue.get`. That method interprets numeric values as relative timeouts; this one interprets them as absolute deadlines and requires ``timedelta`` objects for relative timeouts (consistent with other timeouts in Tornado). """ future = Future() # type: Future[_T] try: future.set_result(self.get_nowait()) except QueueEmpty: self._getters.append(future) _set_timeout(future, timeout) return future def get_nowait(self) -> _T: """Remove and return an item from the queue without blocking. Return an item if one is immediately available, else raise `QueueEmpty`. """ self._consume_expired() if self._putters: assert self.full(), "queue not full, why are putters waiting?" item, putter = self._putters.popleft() self.__put_internal(item) future_set_result_unless_cancelled(putter, None) return self._get() elif self.qsize(): return self._get() else: raise QueueEmpty def task_done(self) -> None: """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 blocking, it resumes when all items have been processed; that is, when every `.put` is matched by a `.task_done`. Raises `ValueError` if called more times than `.put`. """ if self._unfinished_tasks <= 0: raise ValueError("task_done() called too many times") self._unfinished_tasks -= 1 if self._unfinished_tasks == 0: self._finished.set() def join( self, timeout: Optional[Union[float, datetime.timedelta]] = None ) -> Awaitable[None]: """Block until all items in the queue are processed. Returns an awaitable, which raises `tornado.util.TimeoutError` after a timeout. """ return self._finished.wait(timeout) def __aiter__(self) -> _QueueIterator[_T]: return _QueueIterator(self) # These three are overridable in subclasses. def _init(self) -> None: self._queue = collections.deque() def _get(self) -> _T: return self._queue.popleft() def _put(self, item: _T) -> None: self._queue.append(item) # End of the overridable methods. def __put_internal(self, item: _T) -> None: self._unfinished_tasks += 1 self._finished.clear() self._put(item) def _consume_expired(self) -> None: # Remove timed-out waiters. while self._putters and self._putters[0][1].done(): self._putters.popleft() while self._getters and self._getters[0].done(): self._getters.popleft() def __repr__(self) -> str: return "<%s at %s %s>" % (type(self).__name__, hex(id(self)), self._format()) def __str__(self) -> str: return "<%s %s>" % (type(self).__name__, self._format()) def _format(self) -> str: result = "maxsize=%r" % (self.maxsize,) if getattr(self, "_queue", None): result += " queue=%r" % self._queue if self._getters: result += " getters[%s]" % len(self._getters) if self._putters: result += " putters[%s]" % len(self._putters) if self._unfinished_tasks: result += " tasks=%s" % self._unfinished_tasks return result class PriorityQueue(Queue): """A `.Queue` that retrieves entries in priority order, lowest first. Entries are typically tuples like ``(priority number, data)``. .. testcode:: import asyncio from tornado.queues import PriorityQueue async def main(): q = PriorityQueue() q.put((1, 'medium-priority item')) q.put((0, 'high-priority item')) q.put((10, 'low-priority item')) print(await q.get()) print(await q.get()) print(await q.get()) asyncio.run(main()) .. testoutput:: (0, 'high-priority item') (1, 'medium-priority item') (10, 'low-priority item') """ def _init(self) -> None: self._queue = [] def _put(self, item: _T) -> None: heapq.heappush(self._queue, item) def _get(self) -> _T: return heapq.heappop(self._queue) class LifoQueue(Queue): """A `.Queue` that retrieves the most recently put items first. .. testcode:: import asyncio from tornado.queues import LifoQueue async def main(): q = LifoQueue() q.put(3) q.put(2) q.put(1) print(await q.get()) print(await q.get()) print(await q.get()) asyncio.run(main()) .. testoutput:: 1 2 3 """ def _init(self) -> None: self._queue = [] def _put(self, item: _T) -> None: self._queue.append(item) def _get(self) -> _T: return self._queue.pop()