# Copyright (C) 2022-2023 Exaloop Inc. <https://exaloop.io>

from internal.types.optional import unwrap

# Infinite iterators

@inline
def count(start: T = 0, step: T = 1, T: type) -> Generator[T]:
    """
    Return a count object whose ``__next__`` method returns consecutive values.
    """
    n = start
    while True:
        yield n
        n += step

@inline
def cycle(iterable: Generator[T], T: type) -> Generator[T]:
    """
    Cycles repeatedly through an iterable.
    """
    saved = []
    for element in iterable:
        yield element
        saved.append(element)
    while saved:
        for element in saved:
            yield element

@inline
def repeat(object: T, times: Optional[int] = None, T: type) -> Generator[T]:
    """
    Make an iterator that returns a given object over and over again.
    """
    if times is None:
        while True:
            yield object
    else:
        for i in range(times):
            yield object

# Iterators terminating on the shortest input sequence

@inline
def accumulate(iterable: Generator[T], func=lambda a, b: a + b, initial=0, T: type):
    """
    Make an iterator that returns accumulated sums, or accumulated results
    of other binary functions (specified via the optional func argument).
    """
    total = initial
    yield total
    for element in iterable:
        total = func(total, element)
        yield total

@inline
@overload
def accumulate(iterable: Generator[T], func=lambda a, b: a + b, T: type):
    """
    Make an iterator that returns accumulated sums, or accumulated results
    of other binary functions (specified via the optional func argument).
    """
    total = None
    for element in iterable:
        total = element if total is None else func(unwrap(total), element)
        yield unwrap(total)

@tuple
class chain:
    """
    Make an iterator that returns elements from the first iterable until it is exhausted,
    then proceeds to the next iterable, until all of the iterables are exhausted.
    """

    @inline
    def __new__(*iterables):
        for it in iterables:
            for element in it:
                yield element

    @inline
    def from_iterable(iterables):
        for it in iterables:
            for element in it:
                yield element

@inline
def compress(
    data: Generator[T], selectors: Generator[B], T: type, B: type
) -> Generator[T]:
    """
    Return data elements corresponding to true selector elements.
    Forms a shorter iterator from selected data elements using the selectors to
    choose the data elements.
    """
    for d, s in zip(data, selectors):
        if s:
            yield d

@inline
def dropwhile(
    predicate: Callable[[T], bool], iterable: Generator[T], T: type
) -> Generator[T]:
    """
    Drop items from the iterable while predicate(item) is true.
    Afterwards, return every element until the iterable is exhausted.
    """
    b = False
    for x in iterable:
        if not b and not predicate(x):
            b = True
        if b:
            yield x

@inline
def filterfalse(
    predicate: Callable[[T], bool], iterable: Generator[T], T: type
) -> Generator[T]:
    """
    Return those items of iterable for which function(item) is false.
    """
    for x in iterable:
        if not predicate(x):
            yield x

# TODO: fix this once Optional[Callable] lands
@inline
def groupby(iterable, key=Optional[int]()):
    """
    Make an iterator that returns consecutive keys and groups from the iterable.
    """
    currkey = None
    group = []

    for currvalue in iterable:
        k = currvalue if isinstance(key, Optional) else key(currvalue)
        if currkey is None:
            currkey = k
        if k != unwrap(currkey):
            yield unwrap(currkey), group
            currkey = k
            group = []
        group.append(currvalue)
    if currkey is not None:
        yield unwrap(currkey), group

def islice(iterable: Generator[T], stop: Optional[int], T: type) -> Generator[T]:
    """
    Make an iterator that returns selected elements from the iterable.
    """
    if stop is not None and stop.__val__() < 0:
        raise ValueError(
            "Indices for islice() must be None or an integer: 0 <= x <= sys.maxsize."
        )
    i = 0
    for x in iterable:
        if stop is not None and i >= stop.__val__():
            break
        yield x
        i += 1

@overload
def islice(
    iterable: Generator[T],
    start: Optional[int],
    stop: Optional[int],
    step: Optional[int] = None,
    T: type,
) -> Generator[T]:
    """
    Make an iterator that returns selected elements from the iterable.
    """
    from sys import maxsize

    start: int = 0 if start is None else start
    stop: int = maxsize if stop is None else stop
    step: int = 1 if step is None else step
    have_stop = False

    if start < 0 or stop < 0:
        raise ValueError(
            "Indices for islice() must be None or an integer: 0 <= x <= sys.maxsize."
        )
    elif step < 0:
        raise ValueError("Step for islice() must be a positive integer or None.")

    it = range(start, stop, step)
    N = len(it)
    idx = 0
    b = -1

    if N == 0:
        for i, element in zip(range(start), iterable):
            pass
        return

    nexti = it[0]
    for i, element in enumerate(iterable):
        if i == nexti:
            yield element
            idx += 1
            if idx >= N:
                b = i
                break
            nexti = it[idx]

    if b >= 0:
        for i, element in zip(range(b + 1, stop), iterable):
            pass

@inline
def starmap(function, iterable):
    """
    Return an iterator whose values are returned from the function
    evaluated with an argument tuple taken from the given sequence.
    """
    for args in iterable:
        yield function(*args)

@inline
def takewhile(
    predicate: Callable[[T], bool], iterable: Generator[T], T: type
) -> Generator[T]:
    """
    Return successive entries from an iterable as long as the predicate evaluates to true for each entry.
    """
    for x in iterable:
        if predicate(x):
            yield x
        else:
            break

def tee(iterable: Generator[T], n: int = 2, T: type) -> List[Generator[T]]:
    """
    Return n independent iterators from a single iterable.
    """
    from collections import deque

    it = iter(iterable)
    deques = [deque[T]() for i in range(n)]

    def gen(mydeque: deque[T], T: type) -> Generator[T]:
        while True:
            if not mydeque:  # when the local deque is empty
                if it.__done__():
                    return
                it.__resume__()
                if it.__done__():
                    return
                newval = it.next()
                for d in deques:  # load it to all the deques
                    d.append(newval)
            yield mydeque.popleft()

    return [gen(d) for d in deques]

@inline
def zip_longest(*iterables, fillvalue):
    """
    Make an iterator that aggregates elements from each of the iterables.
    If the iterables are of uneven length, missing values are filled-in
    with fillvalue. Iteration continues until the longest iterable is
    exhausted.
    """
    if staticlen(iterables) == 2:
        a = iter(iterables[0])
        b = iter(iterables[1])
        a_done = False
        b_done = False

        while not a.done():
            a_val = a.next()
            b_val = fillvalue
            if not b_done:
                b_done = b.done()
            if not b_done:
                b_val = b.next()
            yield a_val, b_val

        if not b_done:
            while not b.done():
                yield fillvalue, b.next()

        a.destroy()
        b.destroy()
    else:
        iterators = tuple(iter(it) for it in iterables)
        num_active = len(iterators)
        if not num_active:
            return
        while True:
            values = []
            for it in iterators:
                if it.__done__():  # already done
                    values.append(fillvalue)
                elif it.done():  # resume and check
                    num_active -= 1
                    if not num_active:
                        return
                    values.append(fillvalue)
                else:
                    values.append(it.next())
            yield values

@inline
@overload
def zip_longest(*args):
    """
    Make an iterator that aggregates elements from each of the iterables.
    If the iterables are of uneven length, missing values are filled-in
    with fillvalue. Iteration continues until the longest iterable is
    exhausted.
    """

    def get_next(it):
        if it.__done__() or it.done():
            return None
        return it.next()

    iters = tuple(iter(arg) for arg in args)
    while True:
        done_count = 0
        result = tuple(get_next(it) for it in iters)
        all_none = True
        for a in result:
            if a is not None:
                all_none = False
        if all_none:
            return
        yield result
    for it in iters:
        it.destroy()

# Combinatoric iterators

def combinations(pool: Generator[T], r: int, T: type) -> Generator[List[T]]:
    """
    Return successive r-length combinations of elements in the iterable.

    combinations(range(4), 3) --> (0,1,2), (0,1,3), (0,2,3), (1,2,3)
    """

    def combinations_helper(pool: List[T], r: int, T: type) -> Generator[List[T]]:
        n = len(pool)
        if r > n:
            return
        indices = list(range(r))
        yield [pool[i] for i in indices]
        while True:
            b = -1
            for i in reversed(range(r)):
                if indices[i] != i + n - r:
                    b = i
                    break
            if b == -1:
                return
            indices[b] += 1
            for j in range(b + 1, r):
                indices[j] = indices[j - 1] + 1
            yield [pool[i] for i in indices]

    if r < 0:
        raise ValueError("r must be non-negative")
    if hasattr(pool, "__getitem__") and hasattr(pool, "__len__"):
        return combinations_helper(pool, r)
    else:
        return combinations_helper([a for a in pool], r)

def combinations_with_replacement(
    pool: Generator[T], r: int, T: type
) -> Generator[List[T]]:
    """
    Return successive r-length combinations of elements in the iterable
    allowing individual elements to have successive repeats.
    """

    def combinations_with_replacement_helper(
        pool: List[T], r: int, T: type
    ) -> Generator[List[T]]:
        n = len(pool)
        if not n and r:
            return
        indices = [0 for _ in range(r)]
        yield [pool[i] for i in indices]
        while True:
            b = -1
            for i in reversed(range(r)):
                if indices[i] != n - 1:
                    b = i
                    break
            if b == -1:
                return
            newval = indices[b] + 1
            for j in range(r - b):
                indices[b + j] = newval
            yield [pool[i] for i in indices]

    if r < 0:
        raise ValueError("r must be non-negative")
    if hasattr(pool, "__getitem__") and hasattr(pool, "__len__"):
        return combinations_with_replacement_helper(pool, r)
    else:
        return combinations_with_replacement_helper([a for a in pool], r)

def permutations(
    pool: Generator[T], r: Optional[int] = None, T: type
) -> Generator[List[T]]:
    """
    Return successive r-length permutations of elements in the iterable.
    """

    def permutations_helper(
        pool: List[T], r: Optional[int], T: type
    ) -> Generator[List[T]]:
        n = len(pool)
        r: int = r if r is not None else n
        if r > n:
            return

        indices = list(range(n))
        cycles = list(range(n, n - r, -1))
        yield [pool[i] for i in indices[:r]]
        while n:
            b = -1
            for i in reversed(range(r)):
                cycles[i] -= 1
                if cycles[i] == 0:
                    indices = indices[:i] + indices[i + 1 :] + indices[i : i + 1]
                    cycles[i] = n - i
                else:
                    b = i
                    j = cycles[i]
                    indices[i], indices[-j] = indices[-j], indices[i]
                    yield [pool[i] for i in indices[:r]]
                    break
            if b == -1:
                return

    if r is not None and r.__val__() < 0:
        raise ValueError("r must be non-negative")
    if hasattr(pool, "__getitem__") and hasattr(pool, "__len__"):
        return permutations_helper(pool, r)
    else:
        return permutations_helper([a for a in pool], r)

@inline
def product(*args):
    """
    Cartesian product of input iterables.
    """
    if staticlen(args) == 0:
        yield ()
    else:
        for a in args[0]:
            rest = args[1:]
            for b in product(*rest):
                yield (a, *b)

@inline
@overload
def product(*args, repeat: int):
    """
    Cartesian product of input iterables.
    """
    if repeat < 0:
        raise ValueError("repeat argument cannot be negative")
    pools = [list(pool) for _ in range(repeat) for pool in args]
    result = [List[type(pools[0][0])]()]
    for pool in pools:
        result = [x + [y] for x in result for y in pool]
    for prod in result:
        yield prod