I'm trying to make a 'smart' opponent in my Tic Tac Toe program. To do this I've created a 'possible win' function which will decide if there is a possible win in the next turn. My problem when running this code is that on every iteration of the for loop the variable board seems to be changed.
I want to reset potential board to the original board at the start of every iteration which is why I included potential_board = board[:] at the start of the loop. I then edit potential_board but every time the loop repeats this variable is not reset, and board is in fact changed as well. Why is this?
Many thanks!
import random,copy
board = [['o','o',' '],[' ',' ',' '],[' ',' ',' ']]
cols = [['o',' ',' '],['o','',''],['o','','']]
def possible_win(board,player):
""" This function should predict whether a winning move is possible in
the next turn. This could be done by simulating every possible next move
and running check_win() on those positions.
:param board,player: checks a win for the specified player
:return:
"""
spaces = empty_spaces(board)
print('Spaces',spaces)
winning_moves = []
for space in spaces:
potential_board = board[:]
print('PBoard',potential_board)
print(space[0],space[1])
potential_board[space[0]][space[1]] = 'o'
if check_win(potential_board,'o'):
winning_moves.append(space)
return winning_moves
def choose_space(board):
a = True
while a:
col = int(input('Choose your column of 1,2,3: ')) - 1
row = int(input('Choose your row of 1,2,3: ')) - 1
if board[row][col] == ' ':
board[row][col] = 'o'
a = False
else: print('Sorry, try again')
return board
def empty_spaces(board):
empty_spaces = []
ind = 0
for row in board:
ind1 = 0
for space in row:
if space == ' ':
empty_spaces.append((ind, ind1))
ind1 += 1
ind += 1
return empty_spaces
def comp_choose_space(board):
choice = random.choice(empty_spaces(board))
board[choice[0]][choice[1]] = 'x'
return board
def check_win(board,player):
rows = board
columns = construct_cols(board)
for row in board:
# if player fills row win = True
a = ind = 0
for space in row:
if rows[board.index(row)][ind] != player: break
else: a += 1
ind += 1
if a == 3:
return True
for col in columns:
a = ind = 0
for space in col:
if rows[columns.index(col)][ind] != player:
break
else:
a += 1
ind += 1
if a == 3:
return True
if rows[0][0] == player and rows[1][1] == player and rows[2][2] == player \
or rows[0][2] == player and rows[1][1] == player and rows[2][0] == player:
return True
return False
def construct_cols(board):
cols = [['','',''],['','',''],['','','']]
for row in range(len(board)):
for col in range(row):
cols[col][row] = board[row][col] # sounds like this should work
return cols
def print_board(board):
for row in board:
print('| {} {} {} |'.format(row[0],row[1],row[2]))
def main():
turns = 0
board = [[' ',' ',' '],[' ',' ',' '],[' ',' ',' ']]
print_board(board)
win = False
while win == False and turns < 9:
turns += 1
board = choose_space(board)
if check_win(board,'o'): win,winner = True,'won'
board = comp_choose_space(board)
if check_win(board,'x'): win,winner = True,'lost'
print_board(board)
if turns == 9: print('You drew!')
else:
print('{}, you {}'.format('Congratulations' if winner == 'won' else 'Sorry',winner))
print(possible_win(board,'o'))
# print(empty_spaces(board))
# print(check_win(board,'o'))
# print_board(board)
# print(comp_choose_space(board))
# main()
# Future project - make the computer smarter than just randomly choosing a space
# ie seeing how close i am to winning
EDIT: By using copy.deepcopy() I managed to fix this, but I dont understand why this works and copy.copy() and board[:] did not work? Could somebody explain this?
This is what
copy.deepcopy
is for. It will traverse the structure, creating copies of each mutable object within. Using a slice[:]
or shallowcopy
duplicated only the top level, leaving the list for each row shared.Basically, if we start out with a list:
The two
shallow
copies have operated only onl
, not ona
,b
orc
. They both have the value[a, b, c]
but are distinct lists. All of them refer to the samea
,b
andc
objects (the only change from their perspective is that there are more references).The
deep
copy has gone deeper and copied each element; it is a new list with the shape[deepcopy(a), deepcopy(b), deepcopy(c)]
, whatever those values turned into.