Q: How do we use constraint propagation to solve the naked twins problem?
A: The sudoku constraint is that every unit (row, column, or square) be a permutation of the digits 1-9. Therefore, the fact that two boxes that belong to a particular unit have the same two digits as their only possible values forbids those two values from being valid options for the remaining boxes of that unit. Indeed, the constraint that each digit (1-9) only appear once in a unit requires that, since the two digits are certain to be found in the two 'twin' boxes (even if we don't know yet which digit goes in which 'twin' box), they are certain not to be found in the other boxes of that unit.

Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: We include an additional type of unit in our unit list. Concretely, this amounts to adding two new units to our list, namely the two main diagonals of the board. We then apply constraint propagation and search as before, only this time they apply to the two diagonals as well.

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 running python 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.