#SOLVING SUDOKU PYTHON FOR FREE#
#SOLVING SUDOKU PYTHON ZIP FILE#
#SOLVING SUDOKU PYTHON LICENSE#
#SOLVING SUDOKU PYTHON MAC#

#SOLVING SUDOKU PYTHON LICENSE#

Please, see the license for further details.

#SOLVING SUDOKU PYTHON FOR FREE#

This project is freely available for free non-commercial/ commercial use, and may be redistributed under these conditions. You can also contact me through my LinkedIn Profile. Send me a mail at or create a new Issue on this repository. It is all opensource and for further research purpose, so contact me if you. Using Convolutional Neural Networks and Image processing to detect Sudoku Puzzles from the hard copies and then displaying the found solutions onto it using the AR (Augmented Reality) Technology.Exploring the use of Machine Learning algorithms to solve Sudoku Puzzles using a dataset available on Kaggle which provides 9 million Sudoku Puzzle-Solution pairs.Trying different algorithms than the Backtracking such as Stochastic search, Constraint programming, Exact cover, and others.Some of the things I'm working on currently are listed below. This is a basic academic project and I am planning on exploring other ideas to make it more interesting and intuitive. Feel free to add your own puzzles to explore more.

There are 5 demo puzzles already given in the puzzles.py file and their respective solutions are stored in the solutions.py file. You can change last digits of the puzzle0 and solution0 on lines #5 and #6, respectively, to check the algorithm for different puzzles. So, if you want to skip the visualization part to speed it up, feel free to comment out the lines #28 to #30. It takes more time to show the output on every iteration.

Instructions for which are commented in the same file on line #3.Ģ - The algorithm takes only ~1 second to compute most of the Sudoku Puzzles.

#SOLVING SUDOKU PYTHON MAC#

Run the solve.py file using python to see the solutionġ - If you are using Linux or Mac you will need to change one line of code. If any number has a frequency greater than 1 in the hashMap return false else return true Create a recursive function that takes a grid and the current row and column index. Keep Hashmap for the row, column and boxes.

#SOLVING SUDOKU PYTHON ZIP FILE#

Once the requirements are checked, you can easily download this project and use it on your machine in few simple steps.ĭownload this repository as a zip file onto your machine and extract all the files from it. Follow the steps below to solve the problem: Create a function that checks if the given matrix is valid sudoku or not. Python 3.0 and above OR Python 2.2 and above.To download and use this code, the minimum requirements are: So, to solve this problem in a comparatively less time, the Backtracking Algorithm is one of the best solutions to it. For doing this in a conventional way, the processor will require to try all 2*10 77 possible combinations in a worst case scenario which is a huge number.

The objective of the algorithm is to replace all the zeros with valid digits such that the entire Sudoku Puzzle is solved. This is a project which takes an input of the sudoku puzzles as an 81 characters long string containing the digits from 0 to 9, where 0 represents an unfilled cell of the Sudoku Board. The objective is to fill a 9×9 grid with digits so that each column, each row, and each of the nine 3×3 subgrids that compose the grid contain all of the digits from 1 to 9. Sudoku is a logic-based, combinatorial number-placement puzzle.

Flexible: It can very easily be extended to solve Sudokus.Īll we have to do is describe Sudoku as an exact cover problem.Sudoko Solver using Backtracking Algorithm.

Readable: The very first example above is a word-for-word transcription of an example taken straight from Wikipedia!.

Simple: No need to construct a complicated new data structure, everything we used is provided by Python.

In Sudoku for example, there are exactly 4 entries in each row of the matrix, regardless of size, so this will have complexity N^3. On average it will perform much better, because it won't iterate over all the empty cells. This still has O(m*n) complexity, but only in degenerate cases. Here's an example of the problem written in Python.

It asks whether, for a given set X and a collection Y of subsets of X, there exists a subcollection Y* of Y such that Y* forms a partition of X. If you were ever interested in writing a Sudoku solver, then you probably heard about the exact cover problem.

Solving sudoku python