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