from __future__ import annotations

from dataclasses import dataclass, field
from enum import Enum, unique
from typing import Tuple, Optional, List

from common.constants import ROWS, COLUMNS

FREE_FIELD = ' '


@unique
class Direction(Enum):
    LEFT = (0, -1)
    RIGHT = (0, 1)
    UP = (-1, 0)
    DOWN = (1, 0)


@unique
class Action(Enum):
    TURN_LEFT = 'TURN_LEFT'
    TURN_RIGHT = 'TURN_RIGHT'
    FORWARD = 'FORWARD'


@dataclass
class State:
    position: Tuple[int, int]
    direction: Direction


@dataclass
class Node:
    state: State
    parent: Optional[Node]
    action: Action
    cost: int = field(init=False)
    depth: int = field(init=False)

    def __post_init__(self) -> None:
        self.cost = 0 if not self.parent else self.parent.cost + 1
        self.depth = self.cost

    def __eq__(self, other: Node) -> bool:
        return self.state == other.state

    def __hash__(self) -> int:
        return hash(self.state)


def expand(node: Node) -> List[Node]:
    return [child_node(node=node, action=action) for action in actions(node.state)]


def child_node(node: Node, action: Action) -> Node:
    next_state = result(state=node.state, action=action)
    return Node(state=next_state, parent=node, action=action)


def next_position(current_position: Tuple[int, int], direction: Direction) -> Tuple[int, int]:
    x1, y1 = direction.value
    x2, y2 = current_position
    return x1 + x2, y1 + y2


def valid_move(position: Tuple[int, int], grid: List[List[str]]) -> bool:
    row, col = position
    return grid[row][col] == FREE_FIELD


def actions(state: State, grid: List[List[str]]) -> List[Action]:
    possible_actions = [Action.FORWARD, Action.TURN_LEFT, Action.TURN_RIGHT]
    row, col = state.position
    direction = state.direction

    if direction == Direction.UP and row == 0:
        remove_forward(possible_actions)
    if direction == Direction.DOWN and row == ROWS - 1:
        remove_forward(possible_actions)
    if direction == Direction.LEFT and col == 0:
        remove_forward(possible_actions)
    if direction == Direction.RIGHT and col == COLUMNS - 1:
        remove_forward(possible_actions)

    if not valid_move(next_position(state.position, direction), grid):
        remove_forward(possible_actions)

    return possible_actions


def remove_forward(possible_actions: List[Action]) -> None:
    if Action.FORWARD in possible_actions:
        possible_actions.remove(Action.FORWARD)


def result(state: State, action: Action, grid: List[List[str]]) -> State:
    pass


def goal_test(state: State, goal_list: List[Tuple[int, int]]) -> bool:
    return state.position in goal_list


def h(state: State, goal: Tuple[int, int]) -> int:
    """heuristics that calculates Manhattan distance between current position and goal"""
    x1, y1 = state.position
    x2, y2 = goal
    return abs(x1 - x2) + abs(y1 - y2)  # Manhattan distance


def f(current_node: Node, goal: Tuple[int, int]) -> int:
    """f(n) = g(n) + h(n), g stands for current cost, h for heuristics"""
    return current_node.cost + h(state=current_node.state, goal=goal)