see-algorithms.com is a website designed to help you understand basic algorithms through interactive animations and visualization. Whether you're a beginner looking to grasp fundamental concepts or a seasoned developer revisiting the basics, this project offers a unique and engaging way to learn.
- Visual Learning: Stop guessing what happens inside the loop. Our visualizer isolates and highlights the algorithm's exact decisions as they occur.
- Playback Control: Don't just watch — control the flow. Pause, resume, and step through animations at your own pace to truly understand the algorithm's behavior.
- Custom Inputs: Move beyond static examples. Draw custom directed or undirected graphs, edit weights, create binary trees, or input your own numbers to sort.
- Share Insights: Created a tricky graph or a specific tree structure? Generate a unique URL to share your exact visualization setup with peers or students instantly.
- Sorting Algorithms: Bubble Sort, Heap Sort, Merge Sort etc.
- Graph Algorithms: DFS, BFS, Prim's Algorithm etc.
- Data Structures: Linked List, Binary Heap, AVL Tree etc.
- Convex Hull, Huffman Coding and more!
This is a Next.js project bootstrapped with create-next-app.
To run this project locally, follow these steps:
- Clone the repository:
git clone https://github.com/akshay9136/see-algorithms.git- Navigate to the project directory:
cd see-algorithms- Install dependencies:
npm install- Start the development server:
npm run dev- Open your browser and visit: http://localhost:3000
Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (git checkout -b feature/AmazingFeature)
- Commit your Changes (git commit -m "Add some AmazingFeature")
- Push to the Branch (git push origin feature/AmazingFeature)
- Open a Pull Request
If you have any questions, suggestions, or feedback, feel free to reach out.
Email: hello@see-algorithms.com
If you find this project helpful, please consider giving it a star ⭐ on GitHub. Your support is greatly appreciated!
