Q: How do we use constraint propagation to solve the naked twins problem?
A: The naked twins problem is to eliminate possible values of shared peers from twins which belongs to the same unit. This strategy adds more constraint propagation to solve sudoku problem because it reduces the search space before we try all possible number of cases. To implement the naked twins problem, we find twins and delete values of twins' value from shared peers of them if they have any.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: The diagonal sudoku problem is like a regular sudoku, but the numbers 1 to 9 should all appear exactly one on two diagonals. This strategy is another constraint propagation since it gives more way to apply elimination, only-one, and naked-twins strategies. To implement the Diagonal Sudoku problem, we add two units to the original units.
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.