
Transform Complex Algorithms into Interactive Visual Experiences
๐ Live Demo ยท ๐ Documentation ยท ๐ Report Bug ยท ๐ก Request Feature
- ๐ Overview
- โจ Key Features
- ๐ ๏ธ Tech Stack
- ๐ฏ Why Choose Algorithm Visualizer Pro?
- ๐ธ Screenshots
- ๐ Quick Start
- โ๏ธ Installation
- ๐ณ Docker Setup
- โ๏ธ Deployment
- ๐ Algorithm Categories
- ๐จ UI/UX Features
- ๐ง Configuration
- ๐ Performance
- ๐ค Contributing
- ๐ License
- ๐จโ๐ป About the Developer
Algorithm Visualizer Pro is a cutting-edge educational platform that transforms abstract algorithmic concepts into engaging, interactive visual experiences. Built with modern web technologies, it serves as a comprehensive learning tool for students, educators, and algorithm enthusiasts worldwide.
To bridge the gap between theoretical computer science and practical understanding by providing intuitive, step-by-step algorithm visualizations that make complex concepts accessible to learners at all levels.
- ๐๏ธ Real-time Controls: Play, pause, step-through, and speed adjustment
- ๐ Performance Metrics: Live complexity analysis and execution statistics
- ๐จ Custom Themes: Multiple color schemes and visual styles
- ๐พ Save & Share: Export visualizations and share with others
- ๐ Code Display: Synchronized code highlighting during execution
- ๐ Audio Feedback: Optional sound effects for better engagement
- ๐ฑ PWA Support: Install as a desktop/mobile app
- ๐ Multi-language: Support for multiple programming languages
Technology | Version | Purpose |
---|---|---|
React | 18.2.0 | Core UI framework with hooks and context |
Vite | 5.0.0 | Lightning-fast build tool and dev server |
TailwindCSS | 3.3.0 | Utility-first styling framework |
Lucide React | 0.294.0 | Beautiful icon library |
Framer Motion | 10.16.0 | Smooth animations and transitions |
Technology | Version | Purpose |
---|---|---|
FastAPI | 0.104.1 | High-performance async API framework |
Python | 3.11+ | Core backend language |
Uvicorn | 0.24.0 | ASGI server for production |
Pydantic | 2.5.0 | Data validation and serialization |
Technology | Purpose |
---|---|
Docker | Containerization and consistent environments |
Docker Compose | Multi-container orchestration |
Render | Frontend deployment and CDN |
Render/Railway | Backend API deployment |
GitHub Actions | CI/CD pipeline automation |
๐ Feature | โ Algorithm Visualizer Pro | โ Traditional Learning |
---|---|---|
Learning Approach | Visual, Interactive, Step-by-step | Text-based, Static examples |
Engagement | High interactivity with real-time feedback | Passive reading and memorization |
Accessibility | Works on any device, responsive design | Limited to textbooks or desktop software |
Complexity Analysis | Real-time visualization of time/space complexity | Abstract mathematical notation |
Progress Tracking | Visual progress indicators and statistics | Manual tracking required |
Customization | Multiple themes, speeds, and input sizes | Fixed presentation format |
Get up and running in under 5 minutes!
# 1๏ธโฃ Clone the repository
git clone https://github.com/CipherYuvraj/Algorithm-Visualizer-Platform.git
cd Algorithm-Visualizer-Platform
# 2๏ธโฃ Install dependencies
npm install
cd backend && pip install -r requirements.txt
# 3๏ธโฃ Start development servers
npm run dev # Frontend (http://localhost:3000)
npm run dev:api # Backend (http://localhost:8000)
# ๐ Open your browser and start exploring!
๐ฅ๏ธ Frontend Setup
# Navigate to project root
cd Algorithm-Visualizer-Platform/frontend
# Install dependencies
npm install
# Available scripts
npm run dev # Start development server
npm run build # Build for production
npm run preview # Preview production build
npm run lint # Run ESLint
npm run lint:fix # Fix ESLint issues
Environment Variables (.env
):
VITE_API_BASE_URL=http://localhost:8000
VITE_APP_TITLE="Algorithm Visualizer Pro"
VITE_ENABLE_ANALYTICS=false
๐ง Backend Setup
# Navigate to backend directory
cd Algorithm-Visualizer-Platform/backend
# Create virtual environment
python -m venv venv
# Activate virtual environment
# Windows:
venv\Scripts\activate
# macOS/Linux:
source venv/bin/activate
# Install dependencies
pip install -r requirements.txt
# Start development server
uvicorn main:app --reload --host 0.0.0.0 --port 8000
Environment Variables (.env
):
ENVIRONMENT=development
DATABASE_URL=sqlite:///./app.db
SECRET_KEY=your-secret-key-here
CORS_ORIGINS=["http://localhost:3000", "http://localhost:5173"]
# Start entire application stack
docker-compose up -d
# View logs
docker-compose logs -f
# Stop services
docker-compose down
Frontend Dockerfile
# Multi-stage build for optimized production image
FROM node:18-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY . .
RUN npm run build
FROM nginx:alpine
COPY --from=builder /app/dist /usr/share/nginx/html
COPY nginx.conf /etc/nginx/nginx.conf
EXPOSE 80
CMD ["nginx", "-g", "daemon off;"]
Backend Dockerfile
FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
EXPOSE 8000
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
- Create new Web Service on Render
- Connect GitHub repository
- Configure settings:
- Build Command:
pip install -r requirements.txt
- Start Command:
uvicorn main:app --host 0.0.0.0 --port $PORT
- Environment:
Python 3.11
- Build Command:
# Build and push images
docker build -t yourusername/algo-visualizer-frontend ./frontend
docker build -t yourusername/algo-visualizer-backend ./backend
docker push yourusername/algo-visualizer-frontend
docker push yourusername/algo-visualizer-backend
AWS Deployment
Using AWS ECS + ECR:
# Build and tag for ECR
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin your-account.dkr.ecr.us-east-1.amazonaws.com
docker build -t algo-visualizer .
docker tag algo-visualizer:latest your-account.dkr.ecr.us-east-1.amazonaws.com/algo-visualizer:latest
docker push your-account.dkr.ecr.us-east-1.amazonaws.com/algo-visualizer:latest
Google Cloud Platform
Using Cloud Run:
# Build and deploy
gcloud builds submit --tag gcr.io/PROJECT-ID/algo-visualizer
gcloud run deploy --image gcr.io/PROJECT-ID/algo-visualizer --platform managed
๐ Sorting Algorithms | ๐ Graph Algorithms |
---|---|
โข Bubble Sort | โข Breadth-First Search (BFS) |
โข Quick Sort | โข Depth-First Search (DFS) |
โข Merge Sort | โข Dijkstra's Algorithm |
โข Heap Sort | โข A* Search Algorithm |
โข Insertion Sort | โข Kruskal's MST |
๐ Search Algorithms | ๐งฎ Dynamic Programming |
---|---|
โข Linear Search | โข Fibonacci Sequence |
โข Binary Search | โข Knapsack Problem |
โข Jump Search | โข Longest Common Subsequence |
โข Interpolation Search | โข Edit Distance |
โข Exponential Search | โข Coin Change Problem |
- Tree Algorithms: AVL, Red-Black, B-Trees
- String Algorithms: KMP, Rabin-Karp, Boyer-Moore
- Machine Learning: Neural Networks, Decision Trees
- Cryptography: RSA, AES, Hash Functions
// Multiple built-in themes
const themes = {
light: { primary: '#4F46E5', background: '#FFFFFF' },
dark: { primary: '#818CF8', background: '#1F2937' },
ocean: { primary: '#0EA5E9', background: '#0F172A' },
forest: { primary: '#059669', background: '#064E3B' }
};
- Mobile: 320px - 768px
- Tablet: 768px - 1024px
- Desktop: 1024px+
- 4K: 2560px+
- Code Splitting: Dynamic imports for better loading
- Lazy Loading: Components loaded on demand
- Image Optimization: WebP format with fallbacks
- Service Worker: Offline capability and caching
Vite Configuration
// vite.config.js
export default defineConfig({
plugins: [react()],
server: {
port: 3000,
proxy: {
'/api': 'http://localhost:8000'
}
},
build: {
outDir: 'dist',
sourcemap: true,
rollupOptions: {
output: {
manualChunks: {
vendor: ['react', 'react-dom'],
utils: ['lodash', 'axios']
}
}
}
}
});
FastAPI Settings
# config.py
from pydantic import BaseSettings
class Settings(BaseSettings):
app_name: str = "Algorithm Visualizer API"
debug: bool = False
cors_origins: list = ["http://localhost:3000"]
class Config:
env_file = ".env"
settings = Settings()
Metric | Value | Target |
---|---|---|
First Contentful Paint | 1.2s | <1.5s |
Largest Contentful Paint | 2.1s | <2.5s |
Time to Interactive | 2.8s | <3.0s |
Cumulative Layout Shift | 0.05 | <0.1 |
Bundle Size | 145KB | <200KB |
- Tree Shaking: Remove unused code
- Code Splitting: Load components on demand
- Image Optimization: WebP with fallbacks
- CDN: Static assets served via CDN
- Compression: Gzip/Brotli compression
We welcome contributions from the community! Here's how you can help:
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature
) - Commit your changes (
git commit -m 'Add amazing feature'
) - Push to the branch (
git push origin feature/amazing-feature
) - Open a Pull Request
Code Standards
- JavaScript: Follow ESLint configuration
- Python: Follow PEP 8 style guide
- Commits: Use conventional commit messages
- Testing: Add tests for new features
- Documentation: Update README and comments
Pull Request Process
- Update documentation for any new features
- Add tests that prove your fix/feature works
- Ensure all tests pass
- Update the README.md if needed
- Request review from maintainers
Use the issue template to report bugs.
Use the feature request template to suggest new features.
This project is licensed under the MIT License - see the LICENSE file for details.
MIT License
Copyright (c) 2024 Yuvraj Udaywal
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
Passionate about creating innovative web applications and making complex algorithms accessible through interactive visualizations. With expertise in full-stack development using React.js, Node.js, and Python, I strive to bridge the gap between theoretical computer science and practical understanding.
"To democratize algorithm education by making complex concepts visually intuitive and accessible to learners worldwide."
- React Team for the incredible framework
- FastAPI for the blazing-fast API framework
- TailwindCSS for the utility-first CSS framework
- Lucide for the beautiful icon library
- Vercel for seamless deployment experience
- Open Source Community for inspiration and contributions
Need Help?
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๐ Share with friends and colleagues who might benefit from visual algorithm learning
Made with โค๏ธ by Yuvraj Udaywal | ยฉ 2024 Algorithm Visualizer Pro