from solver.state import State
from solver.node import Node


def idfs(initial_state: State):
    """
    Performs iterative deepening search.

    Parameters
    ----------
    initial_state: State
        Initial problem configuration.
    Returns: Node
        Final Node from search or None if no path is found.
    """
    final_node = None
    
    for i in range(1, 10000):
        final_node = dfs(initial_state, i)
        if final_node != None:
            break

    return final_node

def dfs(initial_state: State, max_depth: int=-1):
    """
    Performs depth first search, if max_depth is defined,
    then it will performs the limited depth dfs.

    Parameters
    ----------
    initial_state: State
        Initial problem configuration.
    max_detph: int
        Max depth of dfs search.

    Returns
    -------
    Node:
        Final node or None if no path is found
    """

    open_l = [Node(initial_state, None, True, 0)]
    closed_l = []
    visiteds = set()
    final_node = None

    while open_l:
        actual_node = open_l.pop(-1)
        visiteds.add(actual_node)

        if max_depth > -1 and actual_node.depth == max_depth:
            continue
        elif actual_node.state.is_done():
            return actual_node

        possible_movs = actual_node.possible_movs()
        for mov in possible_movs:
            if not mov in visiteds:
                depth = actual_node.depth + 1 if max_depth > -1 else -1
                new_node = Node(mov, actual_node, not actual_node.left, depth)
                open_l.append(new_node)

    return final_node


def bfs(initial_state: State):
    """
    Performs breadth first search, returning the final node if a path
    is found, otherwise returns None

    Paramters
    ---------
    initial_state: State
        Initial configuration of the problem.

    Returns
    -------
    Node:
        Final node or None.
    """

    open_l = [Node(initial_state, None)]
    closed_l = []
    visiteds = set()
    
    final_node = None

    while open_l:
        actual_node = open_l.pop(0)
        visiteds.add(actual_node)

        if actual_node.state.is_done():
            final_node = actual_node
            break

        possible_movs = actual_node.possible_movs()
        for possible_mov in possible_movs:
            if not possible_mov in visiteds:
                new_node = Node(possible_mov, actual_node, not actual_node.left)
                open_l.append(new_node)
    return final_node


from solver.state import State
from solver.node import Node


def idfs(initial_state: State):
    """
    Performs iterative deepening search.

    Parameters
    ----------
    initial_state: State
        Initial problem configuration.
    Returns: Node
        Final Node from search or None if no path is found.
    """
    final_node = None
    
    for i in range(1, 10000):
        final_node = dfs(initial_state, i)
        if final_node != None:
            break

    return final_node

def dfs(initial_state: State, max_depth: int=-1):
    """
    Performs depth first search, if max_depth is defined,
    then it will performs the limited depth dfs.

    Parameters
    ----------
    initial_state: State
        Initial problem configuration.
    max_detph: int
        Max depth of dfs search.

    Returns
    -------
    Node:
        Final node or None if no path is found
    """

    open_l = [Node(initial_state, None, True, 0)]
    closed_l = []
    visiteds = set()
    final_node = None

    while open_l:
        actual_node = open_l.pop(-1)
        visiteds.add(actual_node)

        if max_depth > -1 and actual_node.depth == max_depth:
            continue
        elif actual_node.state.is_done():
            return actual_node

        possible_movs = actual_node.possible_movs()
        for mov in possible_movs:
            if not mov in visiteds:
                depth = actual_node.depth + 1 if max_depth > -1 else -1
                new_node = Node(mov, actual_node, not actual_node.left, depth)
                open_l.append(new_node)

    return final_node


def bfs(initial_state: State):
    """
    Performs breadth first search, returning the final node if a path
    is found, otherwise returns None

    Paramters
    ---------
    initial_state: State
        Initial configuration of the problem.

    Returns
    -------
    Node:
        Final node or None.
    """

    open_l = [Node(initial_state, None)]
    closed_l = []
    visiteds = set()
    
    final_node = None

    while open_l:
        actual_node = open_l.pop(0)
        visiteds.add(actual_node)

        if actual_node.state.is_done():
            final_node = actual_node
            break

        possible_movs = actual_node.possible_movs()
        for possible_mov in possible_movs:
            if not possible_mov in visiteds:
                new_node = Node(possible_mov, actual_node, not actual_node.left)
                open_l.append(new_node)
    return final_node


Performs iterative deepening search.      Parameters     ----------     initial_state: State         Initial problem configuration.     Returns: Node         Final Node from search or None if no path is found. Performs depth first search, if max_depth is defined,     then it will performs the limited depth dfs.      Parameters     ----------     initial_state: State         Initial problem configuration.     max_detph: int         Max depth of dfs search.      Returns     -------     Node:         Final node or None if no path is found Performs breadth first search, returning the final node if a path     is found, otherwise returns None      Paramters     ---------     initial_state: State         Initial configuration of the problem.      Returns     -------     Node:         Final node or None.