Python Csp Solver For Sudoku, g. As a result, this solver is optimized to solve AllDiff constraints, and is also suitable for the map coloring problem, and the N-queens problem. Apr 16, 2026 · Instead of guessing randomly, I modeled Sudoku as a Constraint Satisfaction Problem (CSP) and used three powerful techniques to solve it efficiently. 7 to solve a Sudoku 9x9 of the Android application "Sudoku" of genina. This repository provides python scripts that allows to solve the Sudoku Game, show the solution with a Graphical User Interface and models the Sudoku Game as a CSP. Contribute to davidxk/Sudoku-CSP development by creating an account on GitHub. CSP Sudoku Solver Overview This is a program that solves sudoku puzzles using artificial intelligence concepts. Requirments: Python3 tkinter Dec 7, 2022 · Overview For a homework assignment, I needed to write a program to solve Sudoku, a typical constraint satisfaction problem (CSP), by using python-constraint. We start our CSP model with a two-dimensional array $x$ of $9\times 9$ variables, each variable having $1,2,\dots ,9$ as domain. It uses techniques like Backtracking, Minimum Remaining Values (MRV), and Least Constraining Value (LCV) heuristics to efficiently solve Sudoku puzzles of varying sizes (e. Leveraging Python's rich ecosystem for computational problems, this solver demonstrates efficient puzzle solving through backtracking, forward checking, and different heuristics. Python implementation of a sudoku puzzle solver (CSP) using AC3 and backtracking algorithms - stressGC/Python-AC3-Backtracking-CSP-Sudoku-Solver Python CSP Sudoku Solver It's a simple script which is capable of solving different sudokus usig CSP. Jan 18, 2022 · This article explains a program in python 2. , from an empty grid). : Jun 8, 2025 · This project is a Sudoku solver that uses a backtracking algorithm to solve Sudoku puzzles. The solver implements constraint satisfaction problem (CSP) principles, ensuring that the puzzle adheres to the fundamental rules of Sudoku, such as: Each row must contain the digits 1 through 9 without Sudoku Solvers implemented with CSP techniques. This program treats the puzzle as a Constraint Satisfaction Problem (CSP). Apr 11, 2026 · A constraint satisfaction problem (CSP) solver implemented in Python, featuring multiple search algorithms and a graphical interface to solve Sudoku and N-Queens puzzles. The Sudoku puzzle is provided as a single string consisting of 81 characters, e. , 9x9, 16x16). e. Sudoku-with-CSP-paradigm 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. In a first step, we shall build a Sudoku grid from no data/clues (i. Constraint Satisfaction Problem - Sudoku Solver This repository contains an implementation of a constraint satisfaction problem (CSP) solver, one catered towards solving Sudoku puzzles. com. Sep 18, 2024 · In this blog, we’ll explore how Sudoku can be formulated as a CSP, diving into the variables, domains, and constraints involved, and even walk through one possible solution. This Python script provides a solver for Sudoku puzzles utilizing the Constraint Satisfaction Problem (CSP) algorithm. 9. Each of the squares in the puzzle is treated as a separate variable, with domain 1-9. The solver takes an input Sudoku puzzle and returns the solution if it exists. This project is a Sudoku solver that uses a backtracking algorithm to solve Sudoku puzzles. A generalized CSP (constraint-satisfaction-problem) solver, written in Python 3. Includes an application of the aforesaid: a fullstack webapp implementation of hyper-generalized sudoku, using Flask, Apache2, WSGI, and JavaScript. The solver implements constraint satisfaction problem (CSP) principles, ensuring that the puzzle adheres to the fundamental rules of Sudoku, such as: Each row must contain the digits 1 through 9 without . This project implements a Sudoku solver using the Constraint Satisfaction Problem (CSP) framework. Introduction This project presents a Sudoku solver implemented in Python, modeled as a Constraint Satisfaction Problem (CSP). This Sudoku solver uses Constraint Propagation using the Arc Consistency Algorithm #3 (AC-3) [1], and then depth-first search (DFS) with Backtracking using the Minimum Remaining Value (MRV) heuristic and Forward Checking (FC). The program takes a partially filled Sudoku grid as input, applies constraints to reduce the search space This project is a constraint satisfaction problem (CSP) solver which is adjusted to solve Sudoku puzzles. ujz, uy3c8, okvt18, qz, 19f, 4b89, hhj3, lux4l, roe, h3y4,