def populateBoard(s, row, col):
"""
Starting with a 9x9 grid of 0's, this function recursively populates
the grid. It makes a list of integers from 1-9, shuffles the order, and
tries the first number in the list in the current cell. If the inserted
integer works, then it continues on. If the integer does not work then
it tries the next one in the list. If none of the integers work, then
set it to blank and return false.
"""
if row == 8 and col == 8:
used = pySudoku.test_cell(s, row, col)
s[row][col] = used.index(0)
return True
if col == 9:
row = row+1
col = 0
temp = list(range(1, 10))
random.shuffle(temp)
# Fill Sudoku
for i in range(9):
s[row][col] = temp[i]
if checkValid(s, row, col):
if populateBoard(s, row, col+1):
return True
s[row][col] = 0
return False
def DFS_solve(copy_s, row, col):
# DFS algorithm, while returning the number of solutions found.
num_solutions = 0
# Reached the last cells without no error, so there is a solution
if row == 8 and col == 8:
return num_solutions + 1
if col == 9:
row = row + 1
col = 0
if copy_s[row][col] == 0:
used = pySudoku.test_cell(copy_s, row, col)
# No possible solutions. Return 0 for number of solutions
if 0 not in used:
return 0
while 0 in used:
copy_s[row][col] = used.index(0)
used[used.index(0)] = 1
num_solutions += DFS_solve(copy_s, row, col + 1)
# For No solution
copy_s[row][col] = 0
return num_solutions
num_solutions += DFS_solve(copy_s, row, col + 1)
return num_solutions
def populateBoard(s, row, col):
"""
Starting with a 9x9 grid of 0's, this function recursively populates
the grid. It makes a list of integers from 1-9, shuffles the order, and
tries the first number in the list in the current cell. If the inserted
integer works, then it continues on. If the integer does not work then
it tries the next one in the list. If none of the integers work, then
set it to blank and return false.
"""
if row == 8 and col == 8:
used = pySudoku.test_cell(s, row, col)
s[row][col] = used.index(0)
return True
if col == 9:
row = row+1
col = 0
temp = list(range(1, 10))
random.shuffle(temp)
# Fill Sudoku
for i in range(9):
s[row][col] = temp[i]
if checkValid(s, row, col):
if populateBoard(s, row, col+1):
return True
s[row][col] = 0
return False
def DFS_solve(copy_s, row, col):
"""
Recursively solves the copy_s puzzle with a backtracking
DFS algorithm, while returning the number of solutions found.
Starts at row 0 and column 0, and continues on to the right and
down the rows.
"""
num_solutions = 0
# Reached the last cells without any error, so there is a solution
if row == 8 and col == 8:
return num_solutions + 1
if col == 9:
row = row+1
col = 0
if copy_s[row][col] == 0:
# Used = list of size 10 representing which numbers are possible
# in the puzzle. 0 = possible, 1 = not possible. Ignore index 0.
used = pySudoku.test_cell(copy_s, row, col)
# No possible solutions. Return 0 for number of solutions
if 0 not in used:
return 0
while 0 in used:
copy_s[row][col] = used.index(0)
used[used.index(0)] = 1
num_solutions += DFS_solve(copy_s, row, col+1)
# Reached here? Then we tried 1-9 without success
copy_s[row][col] = 0
return num_solutions
num_solutions += DFS_solve(copy_s, row, col+1)
return num_solutions
def DFS_solve(copy_s, row, col):
"""
Recursively solves the copy_s puzzle with a backtracking
DFS algorithm, while returning the number of solutions found.
Starts at row 0 and column 0, and continues on to the right and
down the rows.
"""
num_solutions = 0
# Reached the last cells without any error, so there is a solution
if row == 8 and col == 8:
return num_solutions + 1
if col == 9:
row = row+1
col = 0
if copy_s[row][col] == 0:
# Used = list of size 10 representing which numbers are possible
# in the puzzle. 0 = possible, 1 = not possible. Ignore index 0.
used = pySudoku.test_cell(copy_s, row, col)
# No possible solutions. Return 0 for number of solutions
if 0 not in used:
return 0
while 0 in used:
copy_s[row][col] = used.index(0)
used[used.index(0)] = 1
num_solutions += DFS_solve(copy_s, row, col+1)
# Reached here? Then we tried 1-9 without success
copy_s[row][col] = 0
return num_solutions
num_solutions += DFS_solve(copy_s, row, col+1)
return num_solutions
