Q: How do we use constraint propagation to solve the naked twins problem?
Well, I would say naked twins is not a problem per se, but a new strategy (constraint) that can be added
to the constraint propagation loop, helping to reduce the problem space in each iteration.
This strategy enforces the constraint that if there are two cells/boxes in a unit sharing the same two
possibilities, any other cells in the unit must not contain those possibilities.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
We solve the diagonal sudoku problem enforcing new constraints that represent the diagonal requirements. In this case
those constraints can be represented as two new units in unitlist. We would then apply eliminate, naked_twins and only_choice
repeteadly until the board converges into a solution or it stalls.
As we added both diagonals as units, the solver enforces the same constraints as the other units during the constraint propagation phase.
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.