# 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
<https://docs.python.org/3/library/asyncio-queue.html>`_.

.. 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::

        from tornado import gen
        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 gen.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')

        IOLoop.current().run_sync(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::

        from tornado.queues import PriorityQueue

        q = PriorityQueue()
        q.put((1, 'medium-priority item'))
        q.put((0, 'high-priority item'))
        q.put((10, 'low-priority item'))

        print(q.get_nowait())
        print(q.get_nowait())
        print(q.get_nowait())

    .. 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::

        from tornado.queues import LifoQueue

        q = LifoQueue()
        q.put(3)
        q.put(2)
        q.put(1)

        print(q.get_nowait())
        print(q.get_nowait())
        print(q.get_nowait())

    .. 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()
