Q: How do we use constraint propagation to solve the naked twins problem?
A: We add an additional constraint, naked_twins to our reduce_puzzle function. The reduce_puzzle function
iteratively removes values from squares that would violate constraints. The naked_twins constraint prevents any
boxes from containing any of the same values as a pair of unit peers that have exactly two values that are the same
as one another.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: We simply added two additionally unit, the diagonal units, to the set of units that we check our constraints against.
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.