Q: How do we use constraint propagation to solve the naked twins problem?
A: Naked Twins is another constraint that we apply to narrow down the potential solutions for a given box in the sudoku problem. To apply naked twins constraint, we first identify all the boxes
that have only two possible solutions from earlier constraints. Once we get these boxes, we look at each box , and its peers to identify which of the peers have the same value as the box.
Once we have these two boxes, we identify their peers and replace all boxes which contains both these digits with ''. Applying this constraint repeatedly along with the others (eliminate and only choice)
we narrow down to possible solution if one exists.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: Since a diagonal sudoku only adds an extra constraint to what we consider units, we add the list of diagnol boxes to the units and peers definition and that adds. So the diagnolity condition
gets applied automatically since we use the concepts of units/peers across all constraint propogation as part of 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 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.