Algorithm for solving Sudoku

Question

I want to write a code in python to solve a sudoku puzzle. Do you guys have any idea about a good algorithm for this purpose. I read somewhere in net about a algorithm which

Answer 1

Here is a much faster solution based on hari's answer. The basic difference is that we keep a set of possible values for cells that don't have a value assigned. So when we try a new value, we only try valid values and we also propagate what this choice means for the rest of the sudoku. In the propagation step, we remove from the set of valid values for each cell the values that already appear in the row, column, or the same block. If only one number is left in the set, we know that the position (cell) has to have that value.

This method is known as forward checking and look ahead (http://ktiml.mff.cuni.cz/~bartak/constraints/propagation.html).

The implementation below needs one iteration (calls of solve) while hari's implementation needs 487. Of course my code is a bit longer. The propagate method is also not optimal.

import sys
from copy import deepcopy

def output(a):
    sys.stdout.write(str(a))

N = 9

field = [[5,1,7,6,0,0,0,3,4],
         [2,8,9,0,0,4,0,0,0],
         [3,4,6,2,0,5,0,9,0],
         [6,0,2,0,0,0,0,1,0],
         [0,3,8,0,0,6,0,4,7],
         [0,0,0,0,0,0,0,0,0],
         [0,9,0,0,0,0,0,7,8],
         [7,0,3,4,0,0,5,6,0],
         [0,0,0,0,0,0,0,0,0]]

def print_field(field):
    if not field:
        output("No solution")
        return
    for i in range(N):
        for j in range(N):
            cell = field[i][j]
            if cell == 0 or isinstance(cell, set):
                output('.')
            else:
                output(cell)
            if (j + 1) % 3 == 0 and j < 8:
                output(' |')

            if j != 8:
                output(' ')
        output('\n')
        if (i + 1) % 3 == 0 and i < 8:
            output("- - - + - - - + - - -\n")

def read(field):
    """ Read field into state (replace 0 with set of possible values) """

    state = deepcopy(field)
    for i in range(N):
        for j in range(N):
            cell = state[i][j]
            if cell == 0:
                state[i][j] = set(range(1,10))

    return state

state = read(field)


def done(state):
    """ Are we done? """

    for row in state:
        for cell in row:
            if isinstance(cell, set):
                return False
    return True


def propagate_step(state):
    """
    Propagate one step.

    @return:  A two-tuple that says whether the configuration
              is solvable and whether the propagation changed
              the state.
    """

            new_units = False

    # propagate row rule
    for i in range(N):
        row = state[i]
        values = set([x for x in row if not isinstance(x, set)])
        for j in range(N):
            if isinstance(state[i][j], set):
                state[i][j] -= values
                if len(state[i][j]) == 1:
                    val = state[i][j].pop()
                    state[i][j] = val
                    values.add(val)
                    new_units = True
                elif len(state[i][j]) == 0:
                    return False, None

    # propagate column rule
    for j in range(N):
        column = [state[x][j] for x in range(N)]
        values = set([x for x in column if not isinstance(x, set)])
        for i in range(N):
            if isinstance(state[i][j], set):
                state[i][j] -= values
                if len(state[i][j]) == 1:
                    val = state[i][j].pop()
                    state[i][j] = val
                    values.add(val)
                    new_units = True
                elif len(state[i][j]) == 0:
                    return False, None

    # propagate cell rule
    for x in range(3):
        for y in range(3):
            values = set()
            for i in range(3 * x, 3 * x + 3):
                for j in range(3 * y, 3 * y + 3):
                    cell = state[i][j]
                    if not isinstance(cell, set):
                        values.add(cell)
            for i in range(3 * x, 3 * x + 3):
                for j in range(3 * y, 3 * y + 3):
                    if isinstance(state[i][j], set):
                        state[i][j] -= values
                        if len(state[i][j]) == 1:
                            val = state[i][j].pop()
                            state[i][j] = val
                            values.add(val)
                            new_units = True
                        elif len(state[i][j]) == 0:
                            return False, None

    return True, new_units

def propagate(state):
    """ Propagate until we reach a fixpoint """
    while True:
        solvable, new_unit = propagate_step(state)
        if not solvable:
            return False
        if not new_unit:
            return True


def solve(state):
    """ Solve sudoku """

    solvable = propagate(state)

    if not solvable:
        return None

    if done(state):
        return state

    for i in range(N):
        for j in range(N):
            cell = state[i][j]
            if isinstance(cell, set):
                for value in cell:
                    new_state = deepcopy(state)
                    new_state[i][j] = value
                    solved = solve(new_state)
                    if solved is not None:
                        return solved
                return None

print_field(solve(state))