Q: How do we use constraint propagation to solve the naked twins problem?
A: This strategy allows to reduce the possible values within a unit by enforcing the constraint that there cannot be repeated numbers. Therefore if there exist two boxes with the same pair of possible values within the same two units, each and one of those two numbers have to be the solution for the the pair of boxes, and the search space is reduced because those two numbers can be disregarded as solutions for all boxes within the same units.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: This strategy finds the sudoku solution by eliminating possible values that do not comply with the constraints of sudoku rules. With help of the Naked Twins, Only Choice and Elimination methods, the algorithm reduces the possible values for the sudoku's box by eliminating numbers that do not comply with the constraints until we are left with the only possible solutions.
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.