A monorepo for technology exploration and learning, featuring experimental UI libraries, utilities, and various tools.

Features • Packages • Quick Start • Documentation • Contributing

English · 中文

• 🎨 UI Libraries: web components
• 🛠️ Utility Libraries: TypeScript utilities
• 🤖 Machine Learning: Basic ML tools and experiments
• 📱 Web Applications: IM chat app (prototype)
• 🔧 Development Tools: Build tools and debug utilities
• 🌐 Web3: Smart contract experiments
• 🎯 Visual Tools: Data visualization experiments

This monorepo contains various experimental packages:

Package	Version	Downloads	Description
ranui			web component library
ranuts			Utility library

# Clone the repository
git clone https://github.com/chaxus/ran.git
cd ran

# Install dependencies
pnpm install

# Build all packages
pnpm build

# Install ranui (web components)
npm install ranui

# Install utilities
npm install ranuts

# Start development server
pnpm dev

# Run tests
pnpm test

# Build specific package
pnpm --filter ranui build

• 📖 Blog & Articles: Design Patterns & More
• 🎨 RanUI Documentation: UI Library Guide
• 🛠️ RanUTS Documentation: Utility Library Guide
• 📝 Project Documentation: docs

This is a technology exploration and learning project in early development. Most packages are in alpha stage or experimental phase.

Key points:

• 🚧 Early Development: Most features are still being developed
• 🧪 Experimental: APIs may change frequently
• 📚 Learning Focus: Primarily for learning and experimentation

We welcome contributions from learners and developers! Here's how you can help:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

• Follow the existing code style
• Add tests for new features when possible
• Update documentation as needed
• Be patient with experimental features

I believe in the power of open source to accelerate learning and innovation. Throughout my development journey, I've been greatly influenced by countless open-source projects. By open-sourcing this experimental code, I hope to:

• Share learning experiences with the community
• Enable others to learn from and experiment with this code
• Foster collaboration and knowledge sharing
• Create a platform for continuous learning and improvement

This project is licensed under the MIT License - see the LICENSE file for details.