Q: How do we use constraint propagation to solve the naked twins problem?
As we apply eliminate and only_value as part of the constraint propagation to reduce the search space, we also apply the naked twins in the same phase. If we do find a pair of naked twin and eliminate values for other boxes in the same unit, this will further reduce the search space by enforcing these additional constraints.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
Instead of 27 units, we simply add two more units (both diagonals) as part of the solution. Then we apply the same method of using DFS Search along with constraint propogation to find a viable solution that satisfy all the constraints (ie the numbers 1-9 in each of the 29 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.