Q: How do we use constraint propagation to solve the naked twins problem?
A: Constraint propagation was used to solve the naked twins problem by constraining our domain to a unit (row, column, 3x3 square, diagonal) and searching for unsolved duplicate values within each unit that has a length of 2 and making these values our naked pair, if it exists in the unit. We then further constrain the values within each unit in such way that if a naked pair does exist, no other unsolved box in that unit may contain those values in a naked pair, so we remove the naked pair values from any other unsolved values within the unit.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: We use contraint propagation to solve the diagonal sudoku problem similar to how we solved regular sudokus, however this time we add another constraint and check both diagonals in our sudoku. We use all methods we learned from class (eliminate, only_choice, and search) to accomplish our 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.