https://github.com/macromrit/visualize-nqueens
this is a python/streamlit powered app which lets you visualise how backtracking is performed on a chessboard to solve N-Queens Problem-Statement with additional content regarding the solution as well.
https://github.com/macromrit/visualize-nqueens
algorithms-and-data-structures backtracking python streamlit
Last synced: about 1 month ago
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this is a python/streamlit powered app which lets you visualise how backtracking is performed on a chessboard to solve N-Queens Problem-Statement with additional content regarding the solution as well.
- Host: GitHub
- URL: https://github.com/macromrit/visualize-nqueens
- Owner: macromrit
- License: mit
- Created: 2023-11-20T18:11:05.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-11-26T04:14:21.000Z (over 2 years ago)
- Last Synced: 2025-06-05T23:09:26.755Z (about 1 year ago)
- Topics: algorithms-and-data-structures, backtracking, python, streamlit
- Language: Python
- Homepage: https://nqueens-macromrit.streamlit.app/
- Size: 409 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# N-Queens Problem Solver
The N-Queens problem solver is a Python-based application that uses backtracking and recursion to find solutions for placing queens on a chessboard. The interactive user interface is built with the Streamlit framework, allowing users to visualize and understand the solutions for different board sizes.
## Tech Stack
- **Python:** Programming language for the core implementation.
- **Streamlit:** Web app framework for creating an interactive documentation and user interface.
## Installation
To run the app locally, follow these steps:
```bash
pip install streamlit
git clone https://github.com/macromrit/Visualize-Nqueens
cd Visualize-Nqueens
streamlit run app.py
```
## Usage
1. **Slider for Number of Queens:**
- Use the slider to select the number of queens (N) you want to place on the chessboard.
3. **Display Solutions:**
- Visualize the placement of queens on the chessboard for each solution.
- Solutions are generated using a combination of backtracking and recursion.
4. **Additional Information:**
- Time and space complexity information is displayed for each solution.
- Algorithmic explanation is provided for better understanding.
- Description on Domain, Environment and Constraints(Bounding Function) of this problem
## What to do with the App?
### Start of with adjusting the slider to number of queens needed
### Get access to python snippet which solves nqueens and other info like Space Complexity, Time complexity and more...
### Scroll thorugh the solutions and steps involved in solving it to get a good grasp of this problem
## Get in touch with me, (I'm Macromrit)
**Contact Information:**
- Email: amritsubramanian.c@gmail.com
- LinkedIn: [Amrit Subramanian](https://www.linkedin.com/in/macromrit)
- GitHub: [Macromrit](https://github.com/macromrit)