Q: How do we use constraint propagation to solve the naked twins problem?
A: In Sudoku we have a constraint "no digit can appear more than once in unit",
so if we will take a look at unit and find twins (same two-digit value in
different two boxes of same unit) we can guarantee that digits of those
twins cannot appear in other boxes of same unit. So we can enforce the
constraint and simplify our task by removing twin's digits from every other
box of this particular unit.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: Diagonal Sudoku means that digit can appear only once on main diagonals
(A1..I9 and A9..I1 respectively). Main diagonals in this kind of Sudoku
are the same kind of constraints as addition to row units, column units and
square units for classic sudoku. Since I already have a list of constraints
in unitlist, I just have to add two diagonal units to this list and the
whole solve/search algorythm will work with respect to them.
This project requires Python 3.
We recommend students install Anaconda, a pre-packaged Python distribution that contains all of the necessary libraries and software for this project. Please try using the environment we provided in the Anaconda lesson of the Nanodegree.
Optionally, you can also install pygame if you want to see your visualization. If you've followed our instructions for setting up our conda environment, you should be all set.
If not, please see how to download pygame here.
solutions.py- You'll fill this in as part of your solution.solution_test.py- Do not modify this. You can test your solution by runningpython solution_test.py.PySudoku.py- Do not modify this. This is code for visualizing your solution.visualize.py- Do not modify this. This is code for visualizing your solution.
To visualize your solution, please only assign values to the values_dict using the assign_values function provided in solution.py
The data consists of a text file of diagonal sudokus for you to solve.