"""
Adapted from
https://github.com/maxfischer2781/asyncstdlib/blob/master/asyncstdlib/itertools.py
MIT License
"""

from collections import deque
from typing import (
    Any,
    AsyncGenerator,
    AsyncIterator,
    Awaitable,
    Callable,
    Deque,
    Generic,
    Iterator,
    List,
    Tuple,
    TypeVar,
    Union,
    cast,
    overload,
)

T = TypeVar("T")

_no_default = object()


# https://github.com/python/cpython/blob/main/Lib/test/test_asyncgen.py#L54
# before 3.10, the builtin anext() was not available
def py_anext(
    iterator: AsyncIterator[T], default: Union[T, Any] = _no_default
) -> Awaitable[Union[T, None, Any]]:
    """Pure-Python implementation of anext() for testing purposes.

    Closely matches the builtin anext() C implementation.
    Can be used to compare the built-in implementation of the inner
    coroutines machinery to C-implementation of __anext__() and send()
    or throw() on the returned generator.
    """

    try:
        __anext__ = cast(
            Callable[[AsyncIterator[T]], Awaitable[T]], type(iterator).__anext__
        )
    except AttributeError:
        raise TypeError(f"{iterator!r} is not an async iterator")

    if default is _no_default:
        return __anext__(iterator)

    async def anext_impl() -> Union[T, Any]:
        try:
            # The C code is way more low-level than this, as it implements
            # all methods of the iterator protocol. In this implementation
            # we're relying on higher-level coroutine concepts, but that's
            # exactly what we want -- crosstest pure-Python high-level
            # implementation and low-level C anext() iterators.
            return await __anext__(iterator)
        except StopAsyncIteration:
            return default

    return anext_impl()


async def tee_peer(
    iterator: AsyncIterator[T],
    # the buffer specific to this peer
    buffer: Deque[T],
    # the buffers of all peers, including our own
    peers: List[Deque[T]],
) -> AsyncGenerator[T, None]:
    """An individual iterator of a :py:func:`~.tee`"""
    try:
        while True:
            if not buffer:
                # Another peer produced an item while we were waiting for the lock.
                # Proceed with the next loop iteration to yield the item.
                if buffer:
                    continue
                try:
                    item = await iterator.__anext__()
                except StopAsyncIteration:
                    break
                else:
                    # Append to all buffers, including our own. We'll fetch our
                    # item from the buffer again, instead of yielding it directly.
                    # This ensures the proper item ordering if any of our peers
                    # are fetching items concurrently. They may have buffered their
                    # item already.
                    for peer_buffer in peers:
                        peer_buffer.append(item)
            yield buffer.popleft()
    finally:
        # this peer is done – remove its buffer
        for idx, peer_buffer in enumerate(peers):  # pragma: no branch
            if peer_buffer is buffer:
                peers.pop(idx)
                break
        # if we are the last peer, try and close the iterator
        if not peers and hasattr(iterator, "aclose"):
            await iterator.aclose()


class Tee(Generic[T]):
    """
    Create ``n`` separate asynchronous iterators over ``iterable``

    This splits a single ``iterable`` into multiple iterators, each providing
    the same items in the same order.
    All child iterators may advance separately but share the same items
    from ``iterable`` -- when the most advanced iterator retrieves an item,
    it is buffered until the least advanced iterator has yielded it as well.
    A ``tee`` works lazily and can handle an infinite ``iterable``, provided
    that all iterators advance.

    .. code-block:: python3

        async def derivative(sensor_data):
            previous, current = a.tee(sensor_data, n=2)
            await a.anext(previous)  # advance one iterator
            return a.map(operator.sub, previous, current)

    Unlike :py:func:`itertools.tee`, :py:func:`~.tee` returns a custom type instead
    of a :py:class:`tuple`. Like a tuple, it can be indexed, iterated and unpacked
    to get the child iterators. In addition, its :py:meth:`~.tee.aclose` method
    immediately closes all children, and it can be used in an ``async with`` context
    for the same effect.

    If ``iterable`` is an iterator and read elsewhere, ``tee`` will *not*
    provide these items. Also, ``tee`` must internally buffer each item until the
    last iterator has yielded it; if the most and least advanced iterator differ
    by most data, using a :py:class:`list` is more efficient (but not lazy).

    If the underlying iterable is concurrency safe (``anext`` may be awaited
    concurrently) the resulting iterators are concurrency safe as well. Otherwise,
    the iterators are safe if there is only ever one single "most advanced" iterator.
    To enforce sequential use of ``anext``, provide a ``lock``
    - e.g. an :py:class:`asyncio.Lock` instance in an :py:mod:`asyncio` application -
    and access is automatically synchronised.
    """

    def __init__(
        self,
        iterable: AsyncIterator[T],
        n: int = 2,
    ):
        self._iterator = iterable.__aiter__()  # before 3.10 aiter() doesn't exist
        self._buffers: List[Deque[T]] = [deque() for _ in range(n)]
        self._children = tuple(
            tee_peer(
                iterator=self._iterator,
                buffer=buffer,
                peers=self._buffers,
            )
            for buffer in self._buffers
        )

    def __len__(self) -> int:
        return len(self._children)

    @overload
    def __getitem__(self, item: int) -> AsyncIterator[T]:
        ...

    @overload
    def __getitem__(self, item: slice) -> Tuple[AsyncIterator[T], ...]:
        ...

    def __getitem__(
        self, item: Union[int, slice]
    ) -> Union[AsyncIterator[T], Tuple[AsyncIterator[T], ...]]:
        return self._children[item]

    def __iter__(self) -> Iterator[AsyncIterator[T]]:
        yield from self._children

    async def __aenter__(self) -> "Tee[T]":
        return self

    async def __aexit__(self, exc_type: Any, exc_val: Any, exc_tb: Any) -> bool:
        await self.aclose()
        return False

    async def aclose(self) -> None:
        for child in self._children:
            await child.aclose()


atee = Tee
