def evaluation_from_board(board: chess.Board,
evaluation_depth: int = 22) -> Dict:
board_fen = board.fen()
stockfish = Stockfish("/opt/homebrew/Cellar/stockfish/13/bin/stockfish")
stockfish.set_depth(evaluation_depth) # set engine depth
stockfish.set_fen_position(board_fen)
return stockfish.get_evaluation()
class Engine:
def __init__(self, skill_level):
parameters = {
"Write Debug Log": "false",
"Contempt": 0,
"Min Split Depth": 0,
"Threads": 1,
"Ponder": "false",
"Hash": 16,
"MultiPV": 1,
"Skill Level": skill_level,
"Move Overhead": 30,
"Minimum Thinking Time": 20,
"Slow Mover": 80,
"UCI_Chess960": "false",
}
self.engine = Stockfish("resources/stockfish.exe",
parameters=parameters)
self.engine.set_depth(ENGINE_DEPTH)
def set_position(self, fen):
self.engine.set_fen_position(fen)
def get_move(self, time):
return self.engine.get_best_move_time(time)
def generate_random_advantage_position(evaluation_depth: int):
stockfish = Stockfish("/opt/homebrew/Cellar/stockfish/13/bin/stockfish")
stockfish.set_depth(evaluation_depth) # set engine depth
while True:
board = chess.Board()
end_game = False
for i in range(random.randint(10, 200)):
move = random.choice(list(board.legal_moves))
board.push(move)
if board.is_game_over():
end_game = True
print("Final position")
break
if not end_game:
board_fen = board.fen()
stockfish.set_fen_position(board_fen)
position_evaluation = stockfish.get_evaluation()
print(
f"Position_evaluation: {position_evaluation}, fen = {board_fen}"
)
if position_evaluation['type'] == 'cp' and abs(
position_evaluation["value"]) < 300 and abs(
position_evaluation["value"]
) > 1000: # rule out when no big advantage
print(
f"position_evaluation: {position_evaluation}. Passing: rule out when no big advantage"
)
pass
elif position_evaluation['type'] == 'mate' and position_evaluation[
'value'] <= 1: # rule out mate in 1
print(
f"position_evaluation: {position_evaluation}. Passing: rule out mate in 1"
)
pass
else:
if board.turn == chess.WHITE and position_evaluation[
"value"] <= 0: # not an advantage white
print(f"Turn: {board.turn}")
print(
f"position_evaluation: {position_evaluation}. Passing: not an advantage for white"
)
pass
elif board.turn == chess.BLACK and position_evaluation[
"value"] >= 0: # not an advantage black
print(f"Turn: {board.turn}")
print(
f"position_evaluation: {position_evaluation}. Passing: not an advantage for black"
)
pass
else:
yield board, board_fen, position_evaluation
BestMove=None
MinEval=100000
moves = ListEveryLegalMove(ChessBoard.Board,ChessBoard.WhiteToMove,ChessBoard.Castle)
for move in moves:
SBoard,SCastle,SWhiteToMove=deepcopy(ChessBoard.Board),ChessBoard.Castle,ChessBoard.WhiteToMove
ChessBoard.Move(move)
Eval=Search(depth-1,-10000,10000,True)
if Eval<MinEval:
MinEval=Eval
BestMove=move
ChessBoard.Board,ChessBoard.Castle,ChessBoard.WhiteToMove=SBoard,SCastle,SWhiteToMove
return BestMove
#To use traning function u have to have stockfish installed in this directory
stockfish=Stockfish("./stockfish_13/stockfish_13")
stockfish.set_depth(1)
model=tf.keras.models.load_model('Data/Data')
accuracy=[]
round=1
def Train(ChessBoard,WhiteToMove,Castle):
global round
global model
round+=1
fen_position=ToPositionInFENNotation(ChessBoard,WhiteToMove,Castle)
stockfish.set_fen_position(fen_position)
info=stockfish.get_evaluation()
if info["type"]=="mate": print('mate in',info['value'])
else:
info=info['value']
class Ai(Player):
def __init__(self, color: str, game):
"""
une classe pour l'ordinateur
Parameters
----------
color : str
la couleur des pièces
game: Game
le jeu
"""
super().__init__()
self.name = f"ai{color}"
self.color = color
self.check = False
self.game = game
# variables propres
self.engine = Stockfish(
path="stockfish/stockfish_13_win_x64_bmi2.exe",
parameters=self.game.settings["parameters"],
)
self.steps = self.game.settings["number_of_steps"]
self.depth = self.game.settings["depth"]
def en_avant_pawn(self, board) -> np.array:
"""
clone de la méthode de la classe Board\\
ne modifie pas les valeurs étant donné qu'on ne déplace pas de pièces dans le tableau courant\\
mais dans des tableaux provisoires
"""
for i in range(8): # ligne
for j in range(8): # colonne
piece = board[i, j]
if piece is not None:
if piece.pawn_forward >= 2:
piece.pawn_forward = 0
piece.pawn_forward += piece.pawn_forward
return board
def get_move(self) -> str:
move = self.game.board.last_move
indexes = ["a", "b", "c", "d", "e", "f", "g", "h"]
y1 = str(8 - move[0][0])
y2 = str(8 - move[1][0])
x1 = indexes[move[0][1]]
x2 = indexes[move[1][1]]
return x1 + y1 + x2 + y2
def get_pos(self, move: str) -> list({tuple({int})}):
indexes = ["a", "b", "c", "d", "e", "f", "g", "h"]
x1, y1, x2, y2 = move[:4]
x1 = indexes.index(x1)
x2 = indexes.index(x2)
y1 = 8 - int(y1)
y2 = 8 - int(y2)
return [(y1, x1), (y2, x2)]
def empty(self, board, color: str) -> set({tuple({int})}):
"""
clone de la méthode de la classe Board\\
ne modifie pas les valeurs étant donné qu'on ne déplace pas de pièces dans le tableau courant\\
mais dans des tableaux provisoires
"""
res = set()
for i in range(8): # ligne
for j in range(8): # colonne
piece = board[i, j]
if piece is None or piece.color != color:
res.add((i, j))
return res
def play(self):
"""
joue le coup de l'ia
"""
# affichage
textsurface = font.render(
"modélisation...", True,
self.game.data["ai_thinking_indicator_color"])
self.game.screen.blit(textsurface, (720, 25))
pygame.display.flip()
# si l'ia ne joue pas le premier coup de la partie
if self.game.board.last_move[0][0] >= 0:
moves = self.game.all_moves # on récupère les coups précédents
# !print("last moves :", moves)
self.engine.set_position(moves)
# meilleur coup
self.engine.set_depth(self.depth)
move = self.engine.get_best_move()
self.engine.set_depth(2)
# !print("best move :", move)
# nouvelle position pour le moteur
self.engine.set_position([move])
# !print()
getpos = self.get_pos(move)
from_index = getpos[0]
to_index = getpos[1]
# affichage
pygame.draw.rect(self.game.screen, self.game.data["background_color"],
(720, 25, 100, 20))
textsurface = font.render(
"réflexion...", True,
self.game.data["ai_thinking_indicator_color"])
self.game.screen.blit(textsurface, (720, 25))
pygame.display.flip()
# préparer les coups
board = self.game.board.board
for i in range(8):
for j in range(8):
piece = board[i, j]
if piece is not None:
piece.viable = piece.accessible(
board,
(i, j)).intersection(self.empty(board, piece.color))
piece.viable = piece.accessible_with_checked(
(i, j), piece.viable, board)
# jouer le coup
piece = self.game.board.board[from_index]
if len(move) == 5:
piece.promoted = move[4]
if to_index in piece.viable:
piece.move_to(self.game, self.game.board.board, from_index,
to_index)
else:
print("error : illegal move played by ai\nsearching new move...\n")
self.play_alt()
self.game.next_player() # joueur suivant
def play_alt(self):
"""
permet à l'ordinateur de jouer son tour
"""
self.tree = Node(
self.color,
None,
self.game.board.deep_copy(self.game.board.board),
((0, 0), (0, 0)),
)
steps = self.steps
start = time.time() # durée de la réflexion totale
# on construit l'arbre des coups
pygame.draw.rect(self.game.screen, self.game.data["background_color"],
(720, 25, 100, 20))
textsurface = font.render(
"modélisation...", True,
self.game.data["ai_thinking_indicator_color"])
self.game.screen.blit(textsurface, (720, 25))
pygame.display.flip()
self.build(self.tree, steps, self.color)
# on cherche le meilleur coup
pygame.draw.rect(self.game.screen, self.game.data["background_color"],
(720, 25, 100, 20))
textsurface = font.render(
"réflexion...", True,
self.game.data["ai_thinking_indicator_color"])
self.game.screen.blit(textsurface, (720, 25))
pygame.display.flip()
self.tree.get_values(self.game.board.get_score)
# on modifie le nombre d'étape au besoin
end = time.time()
if end - start <= 0.5 and not self.check:
if self.steps + 1 <= self.settings["max_number_of_steps"]:
self.steps += self.settings["number_of_steps_increase_allowed"]
move = ()
# on joue ce coup
for child in self.tree.list_of_leaves:
if child.value == self.tree.value:
move = child.move
break
from_index = move[0]
to_index = move[1]
self.game.board.board[from_index].move_to(self.game,
self.game.board.board,
from_index, to_index)
# on passe au joueur suivant
self.game.next_player()
def build(self, current_node: Node, remaining_steps: int, color: str):
if remaining_steps == 0:
current_node.value = self.game.board.get_score(current_node.board)
return
board = current_node.board.copy()
list_of_pieces = []
# création de la liste des pièces de la bonne couleur
for i in range(8):
for j in range(8):
piece = board[i, j]
if piece is not None and piece.color == color:
list_of_pieces.append((piece, (i, j)))
# pour chaque pièce
for piece, from_index in list_of_pieces:
piece.viable = piece.accessible(board, from_index).intersection(
self.empty(board, piece.color))
piece.viable = piece.accessible_with_checked(
from_index, piece.viable, board)
# pour chaque déplacement viable
for to_index in piece.viable:
new_board = board.copy()
new_board = self.en_avant_pawn(new_board)
piece.move_to(None, new_board, from_index, to_index)
if piece.name == "pion":
if to_index[0] == 0 or to_index[0] == 7:
new_board[to_index] = Dame(piece.color)
new_node = Node(
color,
current_node,
new_board,
(from_index, to_index),
)
color = ("b", "n")[color == "b"]
current_node.__append__(new_node)
self.build(new_node, remaining_steps - 1, color)
class Player(abc.ABC):
"""
An abstract class for player.
"""
QUIT_MOVE = 'a1a1'
def __init__(self, first: bool, host: str, port: int,
skill_level: Optional[int], depth: Optional[int],
stockfish: Optional[str]):
"""
Initialize a player.
Args:
first: Is the player going first.
host: The host of the game.
port: The port in the host of the game.
skill_level: Still level for stockfish.
depth: Depth to search for best move for stockfish.
stockfish: Path to the stockfish executable to use.
"""
self.player_turn = first
self.host = host
self.port = port
self.skill_level = skill_level
self.depth = depth
self.moves = []
self.socket = None
self.stockfish = Stockfish(stockfish or "./stockfish")
if self.skill_level is not None:
self.stockfish.set_skill_level(self.skill_level)
if self.depth is not None:
self.stockfish.set_depth(self.depth)
def get_turns(self) -> List[str]:
"""
Get previous turns to the game from the other player, gets the board to the desired initial state.
Returns:
The pre turns set by the other player.
"""
moves_num = struct.unpack('H', self.socket.recv(2))[0]
moves = []
for _ in range(moves_num):
moves.append(self.socket.recv(5).decode('utf-8').rstrip('\0'))
return moves
def forward_turns(self, moves: Optional[List[str]] = None):
"""
Send previous turns to the game to the other player.
Args:
moves: The pre turns set by this player.
"""
if moves is None:
moves = []
self.socket.send(struct.pack('H', len(moves)))
for move in moves:
self.socket.send(move.ljust(5, '\0').encode('utf-8'))
def set_turns(self, moves: List[str]):
"""
Set the pre turns of the game.
Args:
moves: The pre turns of the game.
"""
self.moves = moves
self.player_turn ^= len(moves) % 2
def choose_move(self):
"""
Choose a move to perform.
Chooses the move using stockfish and sends it to the other player.
"""
self.stockfish.set_position(self.moves)
move = self.stockfish.get_best_move()
if not move:
raise RuntimeError('game over')
print('Move chosen:', move)
self.socket.send(move.ljust(5, '\0').encode('utf-8'))
self.moves.append(move)
def get_move(self):
"""
Get the move done by the other player.
"""
move = self.socket.recv(5).decode('utf-8').rstrip('\0')
if move == self.QUIT_MOVE:
raise RuntimeError('game over')
self.moves.append(move)
print('Move got:', move)
def turn(self):
"""
Perform a single turn, either get the move done by the other player, or do a move.
"""
if self.player_turn:
self.choose_move()
else:
self.get_move()
self.player_turn = not self.player_turn
def print_board(self):
"""
Print the current board's state.
"""
self.stockfish.set_position(self.moves)
print(self.stockfish.get_board_visual())
def __del__(self):
"""
Destruct a player.
Disconnects the socket.
"""
self.socket and self.socket.close()
def create_fish():
s = Stockfish() #parameters={'Threads':cpu_count()})
s.set_depth(20)
#print(s.get_parameters())
return s
import requests
import json
from stockfish import Stockfish
stockfish = Stockfish('stockfish_20090216_x64_bmi2.exe',
parameters={
"Threads": 8,
"Minimum Thinking Time": 300
})
stockfish.set_depth(15)
stockfish.set_skill_level(25)
api_key = 'REPLACE_WITH_API_KEY'
headers = {'Authorization': f'Bearer {api_key}'}
game_state_url = 'https://lichess.org/api/stream/event'
game_id = 'placeholder'
is_checkmate = False
bot_challenges = False
while True:
state_session = requests.Session()
request = state_session.get(game_state_url, headers=headers, stream=True)
for line in request.iter_lines():
if len(line) == 0:
print('Request response is empty.')
if len(line) != 0:
challenge_state_json = json.loads(line)
if challenge_state_json['type'] == 'challenge':
print('BOT_NAME has been challenged.')
challenge_id = challenge_state_json['challenge']['id']
from interface import *
from connexion import connection, reconnect
from stockfish import Stockfish
sf = Stockfish(
r"C:\Users\dyildiz\Downloads\stockfish_12_win_x64_avx2\stockfish_20090216_x64_avx2.exe",
parameters={
"Threads": 3,
"Hash": 2048,
"Skill Level": 20,
"Minimum Thinking Time": 1,
"Slow Mover": 200
})
sf.set_depth(17)
chromedriver = "path/to/chromedriver"
driver = initialise(chromedriver)
driver = reconnect(driver)
# driver = connection(driver)
driver.get("https://www.chess.com/play/online")
sleep(10)
while (True):
print("Search for a new Game")
home = time.time()
ng = False
while (not ng):
sleep(1)
ng = nouveau_jeu(driver)
if (time.time() - home) > 30:
print("Cannot play a new game")
