🧬 GA‑Sudoku‑Solver

A Sudoku solver implemented using Genetic Algorithms, with Streamlit web app for interactive puzzle input, GA configuration, and results visualization.

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🚀 Features

• 🧩 Interactive Sudoku input — enter or edit givens in the browser
• 🧬 Genetic Algorithm solver with configurable evolution parameters
• 📈 Fitness visualization showing GA progress over generations
• 🧠 Supports elitism, tournament selection, adaptive mutation, and stagnation handling
• 🖼️ Streamlit UI for end-to-end solving and display
• 📊 Matplotlib charts for fitness history
• 🧪 Prettified console output for CLI use

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📁 Repository Structure

├── app.py # Streamlit web application
├── genetic_algo.py # GA and configuration logic
├── individual.py # GA Individual class
├── puzzle.py # SudokuPuzzle class
├── run_ga.py # CLI entry point (optional)
└── README.md

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⚙️ Installation

Clone the repository and navigate to the folder:

git clone https://github.com/ahany42/GA-Sudoku-Solver.git
cd GA-Sudoku-Solver

Install Python dependencies:

Copy code
pip install streamlit matplotlib
Python 3.7+ is recommended.

🧠 Usage

Run Streamlit app.py

Enter Sudoku givens (0 = empty)

Configure GA parameters (population, crossover, mutation, etc.)

Click “🚀 Solve with GA”

View best solution & fitness charts

📌 Core Classes

🧩 SudokuPuzzle Immutable puzzle definition using @dataclass(frozen=True)

Computes total conflicts, fitness score, and performs sanity checks

🧪 GeneticAlgorithm

Implements evolutionary loop with:

✔ Tournament selection

✔ Row-wise uniform crossover

✔ Elitism

✔ Adaptive mutation & stagnation

✔ Immigrants injection