Q: How do we use constraint propagation to solve the naked twins problem?
A: We determine, within a unit, if there are two boxes that have the same values. If we find that these two boxes exist, then we can find other boxes in the same unit and remove the twins' values. This will cause our game to have fewer possibilites to search for which will speed up the time to find the solution.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: The diagonal sudoku is very similar to regular sudoku. In the regular game, we have row units, column units and 3x3 units. From these units we construct our pairs. With diagonal sudoku, we just add two additional sets of boxes; the boxes that move diagonally across the board. This causes increased processing time, since we have to calculate a successful game based on more units to solve.
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.
Run python -m cProfile -s cumtime solution.py, to profile the performance characteristics of your application.