Q: How do we use constraint propagation to solve the naked twins problem?
A: In naked twins implementation, each unit (row, column, square and diagonal)
is scanned to identify a pair of identical value boxes of size 2 (naked twins).
If there is naked twins present in a unit, it acts as a constraint on the other unsolved boxes in unit (constraint propagation) in that the other unsolved units cannot hold the digits in the naked twins. As a result we are able to eliminate these digits as a possible solution to the unsolved boxes in the unit. This helps in greatly simplifying the sudoku
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: In my implementation I added an extra unit called the diagonal units. Now during
the process of solving sudoku, the diagonals will act as an extra constraint in
all the peer boxes.
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_values 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](https://project-assistant.udacity.com/auth_tokens/jwt_login 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.