Q: How do we use constraint propagation to solve the naked twins problem?
A: Constraint propagation is an efficient way to iterate the possible values that peers could take to reach to the final solution.
I consider Naked Twins is a manner to simplify the number of iterations choosing a couple of boxes simultaneously having 2 possible values. This simplification could reduce from 4 to 2 the options to be tested as solutions, and it could optimize the algorithm's performance to solve the puzzle.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: The standard sudoku's solution implies defining the boxes to contain all digits. When we implement the 2 additional boxes for diagonals we just follow the same approach, we simply add 2 additional boxes requiring the same requisites than the boxes for the standard solution.
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.