Q: How do we use constraint propagation to solve the naked twins problem?
A: We use constraint propagation by first reducing the search space to within a single unit, and forcing the removal of any number within that unit's boxes
that appears as twins elsewhere in the unit. Applying this constraint for every possible unit brings us closer to the solution by removing possibilities
on the board.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: We use constraint propagation recursively to solve the diagonal sudoku problem. We first reduce the search space by applying eliminate() and only_choice() constraints. We
then create child sudoku puzzles from the reduced board, recursively applying both constraints once again, and creating more child sudokus if necessary. This is done until
we arrive at a board which isn't solvable (in which case, we move on to the next case), or we get a solved board.
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.
solution.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_value function provided in solution.py
Before submitting your solution to a reviewer, you are required to submit your project to Udacity's Project Assistant, which will provide some initial feedback.
The setup is simple. If you have not installed the client tool already, then you may do so with the command pip install udacity-pa.
To submit your code to the project assistant, run udacity submit from within the top-level directory of this project. You will be prompted for a username and password. If you login using google or facebook, visit this link for alternate login instructions.
This process will create a zipfile in your top-level directory named sudoku-.zip. This is the file that you should submit to the Udacity reviews system.