dokusan 0.1.0a3

Sudoku solver with step-by-step guidance

Sudoku solver with step-by-step guidance

Installation

pip install dokusan

Quickstart

Sudoku Solvers

Step-by-step solver

This solver tries to solve sudoku using human-like strategies. Currently following techniques are supported:

• Naked/Hidden singles

• Naked Pairs/Triplets

• Locked Candidate

• XY-Wing

• Unique Rectangle

For example to see all techniques that sudoku has:

from dokusan import solvers
from dokusan.entities import BoxSize, Sudoku


sudoku = Sudoku.from_list(
    [
        [0, 0, 0, 0, 9, 0, 1, 0, 0],
        [0, 0, 0, 0, 0, 2, 3, 0, 0],
        [0, 0, 7, 0, 0, 1, 8, 2, 5],
        [6, 0, 4, 0, 3, 8, 9, 0, 0],
        [8, 1, 0, 0, 0, 0, 0, 0, 0],
        [0, 0, 9, 0, 0, 0, 0, 0, 8],
        [1, 7, 0, 0, 0, 0, 6, 0, 0],
        [9, 0, 0, 0, 1, 0, 7, 4, 3],
        [4, 0, 3, 0, 6, 0, 0, 0, 1],
    ],
    box_size=BoxSize(3, 3),
)

{step.combination.name for step in solvers.steps(sudoku)}

Backtracking-based solver

This solver is based on backtracking algorithm, however slightly modified to work fast

from dokusan import solvers
from dokusan.entities import BoxSize, Sudoku


sudoku = Sudoku.from_list(
    [
        [0, 0, 0, 0, 0, 0, 0, 0, 0],
        [0, 0, 0, 0, 0, 3, 0, 8, 5],
        [0, 0, 1, 0, 2, 0, 0, 0, 0],
        [0, 0, 0, 5, 0, 7, 0, 0, 0],
        [0, 0, 4, 0, 0, 0, 1, 0, 0],
        [0, 9, 0, 0, 0, 0, 0, 0, 0],
        [5, 0, 0, 0, 0, 0, 0, 7, 3],
        [0, 0, 2, 0, 1, 0, 0, 0, 0],
        [0, 0, 0, 0, 4, 0, 0, 0, 9],
    ],
    box_size=BoxSize(3, 3),
)

solvers.backtrack(sudoku)

Sudoku Generator

Generator algorithm is mainly based on article by Daniel Beer. The average time to generate Sudoku with rank of 150 is 700ms.

To generate a new sudoku:

from dokusan import generators


generators.random_sudoku(min_rank=150)

Ranking and Sudoku difficulty

min_rank option is used to roughly estimate the difficulty of the sudoku. Sudoku with rank lower than 100 contains only naked/hidden singles. Sudoku with rank greater than 150 might contain Naked Subsets/Locked Candidate/XY Wing/etc…, however this is not always guaranteed.

For higher ranks it is also not guaranteed that generated Sudoku rank will be higher than provided min_rank, so to ensure sudoku has desired rank one can do the following:

from dokusan import generators, stats


min_rank = 450
while stats.rank(sudoku := generators.random_sudoku(min_rank=min_rank)) < min_rank:
    continue