Q: How do we use constraint propagation to solve the naked twins problem?
A: Naked twins strategy uses constraint proprogation to match a set of twins are within a peer group. We can do this by finding boxes that only have pairs. Then
we see if the same pair of numbers is in that box's peer group. If this is true, then we can remove the two numbers from all other
peers since it can be assumed that the other two numbers must be in either twin box. This further eliminates the number of choices for the other peers.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: Constraint propagation further reduces what numbers can be placed in the diagonal boxes. By adding diagonals, a player is further restricted
on what values can go into the diagonal boxes. For example, box A1 could be the only number in its peers. Previously, this was
only row A, column 1, and the first square unit. Adding the diagonal unit means these boxes have even more constraints
limiting the numbers that can be used in those boxes and further solving the puzzle.
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.