minimax.py

def get_score(board: Ternary, depth: int, player: int = 2) -> Tuple[int, bool]:
    winner = whois_winner(board)

    if winner == player:
        return 10 - depth, True
    elif winner < 1:
        return 0, winner == 0
    else:
        return depth - 10, True


def minimax(board: Ternary, depth: int = 0, player: int = 2) -> Tuple[Ternary, int]:
    score, ended = get_score(board, depth, player)
    if score != 0 or ended:
        return board, score

    depth += 1
    scored_actions: Dict = {}
    actions = np.where(np.array(list(board.number)) == "0")[0]
    active_player = len(actions) % 2 + 1

    for a in actions:
        action_board = list(board.number)
        action_board[a] = str(active_player)
        new_board = "".join(action_board)
        _, scored_actions[new_board] = minimax(Ternary(new_board), depth, player)

    if player == active_player:
        max_value = max(scored_actions.values())
        max_boards = [b for b, v in scored_actions.items() if v == max_value]
        return Ternary(np.random.choice(max_boards)), max_value
    else:
        min_value = min(scored_actions.values())
        min_boards = [b for b, v in scored_actions.items() if v == min_value]
        return Ternary(np.random.choice(min_boards)), min_value