Q: How do we use constraint propagation to solve the naked twins problem?
A: Constraint propagation is used to solve the naked twins problem by identifying
a new strategy in sudoku games. In this case, it is that if two (or more in other
variants of the "naked" strategies) boxes contain the same two value options, their
shared peers cannot be either one of those values in the solution. By applying
this constrain to the Naked Twins' shared peers, it helps reduce the number of
possible solutions that need to be evaluted.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: Unlike Naked Twins, diagonal sudoku is not a new strategy, but simply a new rule
for the game that expands the definition of units and peers. As a result, since we are already limiting the possible solutions based on units and peers (through rows,
columns, and squares), we just need to simply update those existing constraints to include
the main diagonals in the sudoku table.
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.