♟️ N-Queens Solver (BFS & DFS)

A Python-based solver for the classic N-Queens problem — implemented using both Breadth-First Search (BFS) and Depth-First Search (DFS).
This project compares the performance of the two algorithms and prints a sample solution on the board.

🎯 Developed as part of an AI fundamentals course by Ziyad Azzaz.

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📋 Overview

The N-Queens problem asks:

Can you place N queens on an N×N chessboard so that no two queens attack each other?

This project:

• ✅ Explores both BFS and DFS approaches
• ✅ Measures time taken by each algorithm
• ✅ Displays one possible solution on the board
• ✅ Shows how constraint satisfaction works in AI search

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🧠 Features

• 🔎 BFS Search: Iterative search using queues
• 🧭 DFS with Backtracking: Recursive and memory-efficient
• ⏱️ Performance Timer: Measures execution time of each approach
• 🎨 Board Display: Text-based board output with queen positions
• 💻 CLI Interaction: User inputs N directly from terminal

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📂 Files

File Name	Description
n_queens_solver.py	Main Python script
README.md	Project documentation (this file)

👉 View the Full Code Here

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▶️ How to Run

1. Make sure Python is installed (>= 3.6)

2. Clone this repo:

git clone https://github.com/ZiyadAzzaz/n-queens-solver.git
cd n-queens-solver

3. Run the program:

python3 n_queens_solver.py

🧪 Example Output (N = 4)

Welcome to the N-Queens Solver!
═══════════════════════════════

Enter the number of queens (N): 4

Solving the 4-Queens problem...
──────────────────────────────

Search Results:
• BFS found 2 solutions in 1.85 ms
• DFS found 2 solutions in 0.42 ms

Sample Solution:
┌───┬───┬───┬───┐
│   │ Q │   │   │
├───┼───┼───┼───┤
│   │   │   │ Q │
├───┼───┼───┼───┤
│ Q │   │   │   │
├───┼───┼───┼───┤
│   │   │ Q │   │
└───┴───┴───┴───┘

Performance Comparison:
══════════════════════
│ Algorithm │ Time  │
══════════════════════
│ BFS       │ 1.85ms│
│ DFS       │ 0.42ms│
══════════════════════

Thanks for using the N-Queens Solver!
────────────────────────────────────
Made with ❤️ by Ziyad Azzaz 🧠 
(AI Course Project)

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🛠️ Tech Stack

• Language: Python
• Modules: collections, time

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💡 Educational Purpose

This project was built to demonstrate:

• Basic constraint satisfaction
• AI search strategies (DFS vs BFS)
• Recursive and iterative problem solving
• Performance trade-offs between search methods

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👨‍💻 Author

Ziyad Azzaz
🔗 GitHub: ZiyadAzzaz

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🪪 License

This project is open-source under the MIT License.