The provided Python code utilizes the Constraint Satisfaction Problem (CSP) approach to solve a Sudoku puzzle, employing backtracking and constraint propagation to iteratively fill in the grid's empty cells based on the rules of Sudoku.
The code initializes a 9x9 Sudoku grid with given values and a graphical user interface using the Pygame library.
The Pygame window displays the initial state of the Sudoku grid, showing the unsolved puzzle.
The Constraint Satisfaction Problem (CSP) solver is implemented to find a solution for the Sudoku puzzle.
The solver uses a backtracking approach to explore possible values for empty cells, checking the validity of each move.
The code employs constraint propagation by updating and displaying the grid during solving, showing the intermediate steps.
Once the CSP solver completes, the Pygame window displays the final solved state of the Sudoku grid.
The program waits for the user to close the Pygame window, ending the execution.
This code demonstrates how CSP can be applied to solve a Sudoku puzzle through iterative backtracking and constraint propagation techniques.