def callback_query(call):
chat_id = call.message.chat.id
base = SQLighter(config.database_name)
player = base.select_single(chat_id)
i = int(call.data[0])
j = int(call.data[1])
if not utils.update_board(chat_id, i, j, True):
bot.answer_callback_query(call.id, 'Выберите пустую ячейку!')
else:
if utils.check_win(chat_id):
bot.send_message(chat_id, 'Поздравляю, ты победил(а)!')
return
elif player[2] == 8:
bot.send_message(chat_id, 'Победила дружба!')
return
utils.bot_move(chat_id)
if utils.check_win(chat_id):
bot.send_message(chat_id, 'К сожалению, ты проиграл!')
return
elif player[2] == 7:
bot.send_message(chat_id, 'Победила дружба!')
return
global prev_msg
if prev_msg != '':
bot.delete_message(chat_id, prev_msg)
msg = bot.send_message(chat_id,
'Твой ход!',
reply_markup=utils.create_markup(chat_id))
prev_msg = msg.message_id
def _selection(self, root_id):
node_id = root_id
while self.tree[node_id]['n'] > 0:
win_index = utils.check_win(self.tree[node_id]['board'],
self.win_mark)
if win_index != 0:
return node_id, win_index
qu = {}
ids = []
total_n = 0
for action_idx in self.tree[node_id]['child']:
edge_id = node_id + (action_idx, )
n = self.tree[edge_id]['n']
total_n += n
for action_index in self.tree[node_id]['child']:
child_id = node_id + (action_index, )
n = self.tree[child_id]['n']
q = self.tree[child_id]['q']
p = self.tree[child_id]['p']
u = self.c_puct * p * np.sqrt(total_n) / (n + 1)
qu[child_id] = q + u
max_value = max(qu.values())
ids = [key for key, value in qu.items() if value == max_value]
node_id = ids[np.random.choice(len(ids))]
win_index = utils.check_win(self.tree[node_id]['board'], self.win_mark)
return node_id, win_index
def minimax(self, board, move, computerChar, playerChar, depth=0):
"""
Implements the minimax algorithm. Returns 1 : computer has won.
Returns -1 when player wins.
When it's the computer's turn and it has to return a value to its parent,
the maximum value from the array is chosen else, the minimum value.
"""
[is_win, who_won] = utils.check_win(board, computerChar, playerChar)
if is_win == 2:
return 0
if is_win == 1:
if who_won == computerChar:
return 1
if who_won == playerChar:
return -1
ret_list = []
for i in range(9):
if board[i] == '-':
if move == computerChar:
next_move = playerChar
else:
next_move = computerChar
board[i] = move
minimax_val = self.minimax(board, next_move, computerChar,
playerChar, depth + 1)
board[i] = '-'
ret_list.append(minimax_val)
if depth == 0:
return ret_list
if move == computerChar:
return max(ret_list)
else:
return min(ret_list)
def abprune(board, depth, Max, alpha, beta):
# Max - True for maximizer , False for minimizer
value_board = utils.check_win(board)
# printer(board,value_board)
if value_board != 2:
return value_board # if game-over return winner..
moves = utils.get_moves_left(board)
if Max:
best = -99
for move in moves:
board[move] = 1
val = abprune(board, depth + 1, False, alpha, beta)
best = max(best, val)
board[move] = 9
alpha = max(alpha, best)
if beta <= alpha:
break
return best
else:
best = 99
for move in moves:
board[move] = 0
val = abprune(board, depth + 1, True, alpha, beta)
best = min(best, val)
board[move] = 9
beta = min(beta, best)
if beta <= alpha:
break
return best
def decide_winner(win_conditions, size, board, move):
winner = utils.check_win(win_conditions, board)
if winner != -1:
print("The winner is {}".format("X" if winner == 1 else "O"))
return True
elif move >= size * size:
print("No winner")
return True
def _expansion_simulation(self, leaf_id, win_index):
leaf_board = self.tree[leaf_id]['board']
current_player = self.tree[leaf_id]['player']
if win_index == 0:
# expansion
actions = utils.valid_actions(leaf_board)
for action in actions:
action_index = action[1]
child_id = leaf_id + (action_index, )
child_board = utils.get_board(child_id, self.board_size)
next_turn = utils.get_turn(child_id)
self.tree[child_id] = {
'board': child_board,
'player': next_turn,
'parent': leaf_id,
'child': [],
'n': 0.,
'w': 0.,
'q': 0.
}
self.tree[leaf_id]['child'].append(action_index)
if self.tree[leaf_id]['parent']:
# simulation
board_sim = leaf_board.copy()
turn_sim = current_player
while True:
actions_sim = utils.valid_actions(board_sim)
action_sim = actions_sim[np.random.choice(
len(actions_sim))]
coord_sim = action_sim[0]
if turn_sim == 0:
board_sim[coord_sim] = 1
else:
board_sim[coord_sim] = -1
win_idx_sim = utils.check_win(board_sim, self.win_mark)
if win_idx_sim == 0:
turn_sim = abs(turn_sim - 1)
else:
reward = utils.get_reward(win_idx_sim, leaf_id)
return reward
else:
# root node don't simulation
reward = 0.
return reward
else:
# terminal node don't expansion
reward = 1.
return reward
def two_player(self, board):
'''
Play in 2 player mode
'''
keyboardIndexMapping = constants.keyboardIndexMapping
playerOne, playerTwo, playerOneChar, playerTwoChar, whichPlayerFirst = utils.getTwoPlayerDetails(
)
move_mapping = {playerOne: playerOneChar, playerTwo: playerTwoChar}
if whichPlayerFirst == 1:
chance = playerOne
else:
chance = playerTwo
while (utils.check_win(board, playerOneChar, playerTwoChar)[0] == 0):
utils.clearScreen()
utils.display_board(board)
print(chance + ": Your chance")
index = int(input())
if index > 9 or index < 1:
utils.clearScreen()
continue
index = keyboardIndexMapping[index]
if (board[index] != '-'):
continue
board[index] = move_mapping[chance]
if (chance == playerOne):
chance = playerTwo
else:
chance = playerOne
[isWin, whoWon] = utils.check_win(board, playerOneChar, playerTwoChar)
if (isWin == 2):
utils.clearScreen()
utils.display_board(board)
print("It's a tie")
if (isWin == 1):
utils.clearScreen()
utils.display_board(board)
if (whoWon == playerOneChar):
print(playerOne + " won!")
else:
print(playerTwo + " won!")
def _selection(self, root_id):
node_id = root_id
# 한 번이라도 시뮬레이션이 이루어진 노드에서만 선택
while self.tree[node_id]['n'] > 0:
# node_id로부터 보드의 현 상태를 생성하고 승패를 판단함
board = utils.get_board(node_id, self.board_size)
win_index = utils.check_win(board, self.win_mark)
if win_index != 0:
return node_id, win_index # 해당 노드에서 승패가 결정나면 node_id 와 win_index(승패결과) 반환
qu = {} # q + u
ids = [] # key에 child_id와 value에 qu가 입력될 dict
total_n = 0 # 해당 부모노드에 포함된 자식노드들 시뮬레이션 수의 합
# 모든 자식노드들의 n값을 더해 total_n을 구함
for action_idx in self.tree[node_id]['child']:
edge_id = node_id + (action_idx, )
n = self.tree[edge_id]['n']
total_n += n
# 모든 자식노드들의 q+u 값을 구함
for i, action_index in enumerate(self.tree[node_id]['child']):
child_id = node_id + (action_index, )
n = self.tree[child_id]['n']
q = self.tree[child_id]['q']
p = self.tree[child_id]['p']
u = self.c_puct * p * np.sqrt(total_n) / (n + 1)
qu[child_id] = q + u
max_value = max(qu.values()) # qu중 최대값을 구함
ids = [key for key, value in qu.items() if value == max_value
] # qu최대값에 해당하는 child_id와 value를 dict에 입력
node_id = ids[np.random.choice(len(ids))] # 최대값 중 하나에 해당하는 노드를 선택
# node_id로부터 보드의 현 상태를 생성하고 승패를 판단함
board = utils.get_board(node_id, self.board_size)
win_index = utils.check_win(board, self.win_mark)
return node_id, win_index
def test_check_win__lose_count_reset():
"""If count is not reset, then this will be a false win
"""
board = [
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[1, 1, 0, 0, 0, 0, 0],
[1, 1, 0, 2, 0, 0, 0],
[2, 1, 2, 2, 2, 0, 0],
]
assert utils.check_win(board, 2) == []
def _selection(self, root_id):
node_id = root_id
while self.tree[node_id]['n'] > 0: # if it is leaf node
board = utils.get_board(node_id, self.board_size, self.win_mark)
win_index = utils.check_win(board, self.win_mark)
if win_index != 0: # if the game is over and the current node is not leaf
return node_id, win_index
qu = {}
ids = []
total_n = 0
for action_idx in self.tree[node_id]['child']:
edge_id = node_id + (action_idx, )
n = self.tree[edge_id]['n']
total_n += n # the total number of visit of child nodes
# PUCT calculation
for i, action_index in enumerate(self.tree[node_id]['child']):
child_id = node_id + (action_index,
) # history + action visited previously
n = self.tree[child_id]['n']
q = self.tree[child_id]['q']
p = self.tree[child_id]['p']
u = self.c_puct * p * np.sqrt(total_n) / (n + 1
) # 2nd term of PUCT
qu[child_id] = q + u
max_value = max(qu.values())
ids = [key for key, value in qu.items()
if value == max_value] # argmax indices
node_id = ids[np.random.choice(
len(ids))] # key & value of seleted index among argmax indices
board = utils.get_board(node_id, self.board_size, self.win_mark)
win_index = utils.check_win(board, self.win_mark)
return node_id, win_index
def test_check_win():
logger.debug('Testing check_win() from minimax.py')
state = [['X', None, None],
['O', 'X', None],
[None, 'O', 'X']]
assert (check_win(state, 'X') == True)
state = [[None, 'X', 'O'],
[None, 'X', None],
[None, 'O', 'X']]
assert (check_win(state, 'X') == False)
state = [['X', 'O', None],
[None, 'X', None],
[None, 'O', 'X']]
assert (check_win(state, 'O') == False)
state = [['O', None, 'X'],
[None, None, 'X'],
[None, 'O', 'X']]
assert (check_win(state, 'X') == True)
state = [['X', 'O', None],
['X', 'O', None],
['X', 'O', 'X']]
assert (check_win(state, 'X') == True)
assert (check_win(state, 'O') == True)
logger.debug('Passed')
def test_check_win__diagonal_fwd_slash_far_left():
board = [
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 0, 0],
[0, 0, 2, 1, 1, 0, 0],
[0, 0, 1, 1, 2, 0, 0],
[0, 1, 2, 2, 2, 0, 0],
]
diff = DeepDiff(utils.check_win(board, 2),
[[(5, 1), (4, 2), (3, 3), (2, 4)]],
ignore_order=True)
assert diff == {}
def repl(board: Board) -> Player:
"""
players - Players list - A list of player objects that represent the players.
board - Board - a fresh board to start the game
"""
game_over, winner = check_win(board.players)
while not game_over:
p_turn = board.players[board.turn]
# print(" Current Turn: ", p_turn.name)
# print(" Player's influence ", [p.influence for p in board.players])
# print(" Player's bank ", [p.bank for p in board.players])
# print(" Player's hand size", [len(p.hand) for p in board.players])
if p_turn.influence <= 0:
board.end_turn()
else:
#print("THIS IS P_TURN", p_turn.name)
if isinstance(p_turn, RandomPlayer) or isinstance(
p_turn, HeuristicPlayer):
selected_action = p_turn.select_action()
#enable_print()
# print(p_turn.name, selected_action)
# block_print()
process_action(selected_action, p_turn, board)
else:
print("{} it is your turn".format(p_turn.name))
prompt_user()
i = input()
while not i.isalnum():
print("{} it is your turn".format(p_turn.name))
prompt_user()
i = input()
process_input(i, p_turn, board)
# End of action
game_over, winner = check_win(board.players)
print("{} has won the game!".format(winner.name))
return winner
def test_check_win__diagonal_back_slash_middle():
board = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0],
[0, 2, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 0, 0],
[0, 2, 2, 1, 1, 0, 0],
[0, 1, 2, 1, 2, 0, 0],
]
diff = DeepDiff(utils.check_win(board, 3),
[[(1, 1), (2, 2), (3, 3), (4, 4)]],
ignore_order=True)
assert diff == {}
def test_check_win__vertical():
board = [
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0],
[0, 1, 0, 2, 0, 0, 0],
[0, 1, 2, 2, 0, 0, 0],
]
diff = DeepDiff(utils.check_win(board, 2),
[[(5, 1), (4, 1), (3, 1), (2, 1)]],
ignore_order=True)
assert diff == {}
def test_check_win__bug_with_vertical():
"""The last move was the far right of the win
Actual board that said player 1 won
Issue: the diagonal was wraping around the top and comming up on the bottom
"""
board = [
[0, 1, 0, 0, 0, 0, 0],
[0, 2, 0, 0, 0, 0, 0],
[0, 1, 1, 0, 2, 2, 0],
[0, 1, 2, 2, 1, 1, 0],
[0, 1, 1, 1, 2, 2, 2],
[0, 2, 1, 2, 1, 2, 1],
]
assert utils.check_win(board, 2) == []
def test_check_win__horizontal_far_left():
"""The last move was the far left of the win
"""
board = [
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 2, 0, 0, 2, 0],
[0, 0, 2, 1, 1, 1, 1],
]
diff = DeepDiff(utils.check_win(board, 4),
[[(5, 3), (5, 4), (5, 5), (5, 6)]],
ignore_order=True)
assert diff == {}
def simulation(self, tree, child_id):
state = deepcopy(tree[child_id]['state'])
player = deepcopy(tree[child_id]['player'])
while True:
win = check_win(state, self.win_mark)
if win != 0:
return win
else:
actions = valid_actions(state)
action = random.choice(actions)
if player == 0:
player = 1
state[action[0]] = 1
else:
player = 0
state[action[0]] = -1
def expansion(self, tree, leaf_id):
leaf_state = deepcopy(tree[leaf_id]['state'])
is_terminal = check_win(leaf_state, self.win_mark)
actions = valid_actions(leaf_state)
expand_thres = 10
if leaf_id == (0, ) or tree[leaf_id]['n'] > expand_thres:
is_expand = True
else:
is_expand = False
if is_terminal == 0 and is_expand:
# expansion for every possible actions
childs = []
for action in actions:
state = deepcopy(tree[leaf_id]['state'])
action_index = action[1]
current_player = tree[leaf_id]['player']
if current_player == 0:
next_turn = 1
state[action[0]] = 1
else:
next_turn = 0
state[action[0]] = -1
child_id = leaf_id + (action_index, )
childs.append(child_id)
tree[child_id] = {
'state': state,
'player': next_turn,
'child': [],
'parent': leaf_id,
'n': 0,
'w': 0,
'q': 0
}
tree[leaf_id]['child'].append(action_index)
child_id = random.sample(childs, 1)
return tree, child_id[0]
else:
# If leaf node is terminal state,
# just return MCTS tree
return tree, leaf_id
def minimax(board, depth, Max):
# Max - True for maximizer , False for minimizer
value_board = utils.check_win(board)
# printer(board,value_board)
if value_board != 2:
return value_board # if game-over return winner..
moves = utils.get_moves_left(board)
if Max:
best = -99
for move in moves:
board[move] = 1
val = minimax(board, depth + 1, False)
best = max(best, val)
board[move] = 9
return best
else:
best = 99
for move in moves:
board[move] = 0
val = minimax(board, depth + 1, True)
best = min(best, val)
board[move] = 9
return best
def step(self, input_):
# Initial settings
if self.init is True:
self.num_stones = 0
# No stone: 0, Black stone: 1, White stone = -1
self.gameboard = np.zeros([GAMEBOARD_SIZE, GAMEBOARD_SIZE])
# black turn: 0, white turn: 1
self.turn = 0
self.init = False
# Key settings
mouse_pos = 0
if np.all(input_) == 0 and self.gamemode == 'pygame':
# If guide mode of O's turn
for event in pygame.event.get(): # event loop
if event.type == QUIT:
self.terminate()
if pygame.mouse.get_pressed()[0]:
mouse_pos = pygame.mouse.get_pos()
# get action and put stone on the board
check_valid_pos = False
x_index = 100
y_index = 100
# action = np.reshape(input_, (GAMEBOARD_SIZE, GAMEBOARD_SIZE))
action_index = 0
if mouse_pos != 0:
for i in range(len(self.X_coord)):
for j in range(len(self.Y_coord)):
if ((self.X_coord[i] - 15 < mouse_pos[0] <
self.X_coord[i] + 15)
and (self.Y_coord[j] - 15 < mouse_pos[1] <
self.Y_coord[j] + 15)):
check_valid_pos = True
x_index = i
y_index = j
action_index = y_index * GAMEBOARD_SIZE + x_index
# If selected spot is already occupied, it is not valid move!
if self.gameboard[y_index,
x_index] == 1 or self.gameboard[
y_index, x_index] == -1:
check_valid_pos = False
# If self mode and MCTS works
if np.any(input_) != 0:
action_index = np.argmax(input_)
y_index = int(action_index / GAMEBOARD_SIZE)
x_index = action_index % GAMEBOARD_SIZE
check_valid_pos = True
# If selected spot is already occupied, it is not valid move!
if self.gameboard[y_index,
x_index] == 1 or self.gameboard[y_index,
x_index] == -1:
check_valid_pos = False
# Change the gameboard according to the stone's index
if np.any(input_) != 0:
# update state
# self.state = update_state(self.state, self.turn, x_index, y_index)
if self.turn == 0:
self.gameboard[y_index, x_index] = 1
self.turn = 1
self.num_stones += 1
else:
self.gameboard[y_index, x_index] = -1
self.turn = 0
self.num_stones += 1
if self.gamemode == 'pygame':
# Fill background color
DISPLAYSURF.fill(BLACK)
# Draw board
self.draw_main_board()
# Display Information
self.title_msg()
self.rule_msg()
self.score_msg()
# Display who's turn
self.turn_msg()
pygame.display.update()
# Check_win 0: playing, 1: black win, 2: white win, 3: draw
win_index = check_win(self.gameboard, WIN_STONES)
self.display_win(win_index)
return self.gameboard, check_valid_pos, win_index, self.turn, action_index
def select(b, n):
global a, ai_enabled, player_first, button_dictionary, ttt_board
if ttt_board[n] != 9:
tkinter.messagebox.showinfo("Error", " Choose some other box")
return
a = a + 1
if ai_enabled and player_first: # True, and player_first then
if (a % 2 == 0):
b.configure(image=x)
ttt_board[n] = 1 # computer's move done..
if utils.check_win(ttt_board) == 1:
reset()
tkinter.messagebox.showinfo("COMPUTER WON",
" Better Luck next time.. ")
elif utils.check_win(ttt_board) == 0:
reset()
tkinter.messagebox.showinfo("It's a DRAW", " Well played.. ")
else:
b.configure(image=o)
ttt_board[n] = 0
if utils.check_win(ttt_board) == -1:
reset()
tkinter.messagebox.showinfo("PLAYER WON",
" CONGRATULATIONS.... ")
elif utils.check_win(ttt_board) == 0:
reset()
tkinter.messagebox.showinfo("It's a DRAW", " Well played.. ")
move = method_ai.best_move(ttt_board)
select(button_dictionary[move],
move) # call for computer to make a move
elif ai_enabled:
# player goes second
if (a % 2 != 0):
b.configure(image=x)
ttt_board[n] = 1 # computer's move done..
if utils.check_win(ttt_board) == 1:
reset()
tkinter.messagebox.showinfo("COMPUTER WON",
" Better Luck next time.. ")
elif utils.check_win(ttt_board) == 0:
reset()
tkinter.messagebox.showinfo("It's a DRAW", "Well played .. ")
else:
b.configure(image=o)
ttt_board[n] = 0
if utils.check_win(ttt_board) == -1:
reset()
tkinter.messagebox.showinfo("Player WON",
" CONGRATULATIONS... ")
elif utils.check_win(ttt_board) == 0:
reset()
tkinter.messagebox.showinfo("It's a DRAW", "Well played .. ")
move = method_ai.best_move(ttt_board)
select(button_dictionary[move],
move) # call for computer to make a move
else:
# double player mode
if (a % 2 == 0):
b.configure(image=x)
ttt_board[n] = 1
else:
b.configure(image=o)
ttt_board[n] = 0
res = utils.check_win(ttt_board)
if res == 0:
reset()
tkinter.messagebox.showinfo("It's a DRAW", "Well played people.. ")
elif res == -1:
reset()
tkinter.messagebox.showinfo(" RESULTS ", " And the winner is O")
elif res == 1:
reset()
tkinter.messagebox.showinfo(" RESULTS ", " And the winner is X ")
def check_win(self, column):
self.win = utils.check_win(self.board, column)
return self.win
def one_player(self, board):
"""
Play with the computer
"""
keyboardIndexMapping = constants.keyboardIndexMapping
computerChar, playerChar, displayWinChance, whichPlayerFirst = utils.getSinglePlayerDetails(
)
if whichPlayerFirst == 1:
utils.clearScreen()
utils.display_board(board)
while utils.check_win(board, computerChar, playerChar)[0] == 0:
if utils.check_empty(board):
tut = [0, 0, 0, 0, 0, 0, 0, 0, 0]
else:
tut = [
-i for i in self.minimax(board, playerChar,
computerChar, playerChar)
]
if displayWinChance == 1:
utils.clearScreen()
utils.display_tutorial_board(board, tut)
index = int(input())
if index > 9 or index < 1:
utils.clearScreen()
utils.display_board(board)
if displayWinChance == 1:
utils.clearScreen()
utils.display_tutorial_board(board, tut)
continue
index = keyboardIndexMapping[index]
# cant use already used index
if board[index] != '-':
utils.clearScreen()
utils.display_board(board)
if displayWinChance == 1:
utils.clearScreen()
utils.display_tutorial_board(board, tut)
continue
board[index] = playerChar
utils.clearScreen()
utils.display_board(board)
if displayWinChance == 1:
utils.clearScreen()
utils.display_tutorial_board(board, tut)
if utils.check_win(board, computerChar, playerChar)[0] != 0:
break
ret = self.minimax(board, computerChar, computerChar,
playerChar)
# chose move for computer
board[utils.the_move(board, ret)] = computerChar
utils.clearScreen()
utils.display_board(board)
if utils.check_win(board, computerChar, playerChar)[0] == 1:
print("You lost!!")
else:
print("It's a draw!")
if whichPlayerFirst == 2:
while utils.check_win(board, computerChar, playerChar)[0] == 0:
if utils.check_empty(board):
board[random.randrange(0, 9)] = computerChar
else:
ret = self.minimax(board, computerChar, computerChar,
playerChar)
# chose move for computer
board[utils.the_move(board, ret)] = computerChar
utils.clearScreen()
utils.display_board(board)
if utils.check_win(board, computerChar, playerChar)[0] != 0:
break
# index already used can't be reused
flag = 0
while flag == 0:
tut = [
-i for i in self.minimax(board, playerChar,
computerChar, playerChar)
]
utils.clearScreen()
utils.display_board(board)
if displayWinChance == 1:
utils.clearScreen()
utils.display_tutorial_board(board, tut)
index = int(input())
if index > 9 or index < 1:
utils.clearScreen()
utils.display_board(board)
if displayWinChance == 1:
utils.clearScreen()
utils.display_tutorial_board(board, tut)
continue
index = keyboardIndexMapping[index]
if board[index] == '-':
flag = 1
board[index] = playerChar
utils.clearScreen()
utils.display_board(board)
if displayWinChance == 1:
utils.clearScreen()
utils.display_tutorial_board(board, tut)
else:
utils.clearScreen()
utils.display_board(board)
if displayWinChance == 1:
utils.clearScreen()
utils.display_tutorial_board(board, tut)
if utils.check_win(board, computerChar, playerChar)[0] == 1:
print("You lost!!")
else:
print("It's a draw!")
def test_move_win(size, board, turn, move, win_conditions):
board_copy = board[:]
utils.update_board(board_copy, move, turn, size)
return False if utils.check_win(win_conditions, board_copy) == -1 else True
