kitty-scaffold 0.1.2
A professional project scaffolding tool for Python developers - quickly bootstrap AI, Data Science, Research, and Backend projects
License: MIT
Requires Python: >=3.8
Keywords: scaffolding, project-template, cli, data-science, ai, backend, automation, boilerplate

# 🐱 Kitty - Project Scaffolding Tool

**Stop wasting time on boilerplate. Start building.**

Kitty is a professional CLI tool that instantly scaffolds standardized project structures for Data Science, AI/ML, Research, Backend APIs, and Automation projects.

[![PyPI version](https://badge.fury.io/py/kitty-scaffold.svg)](https://pypi.org/project/kitty-scaffold/)
[![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

---

## 🚀 Why Kitty?

Every developer faces the same problem: **starting a new project means spending hours setting up folder structures, configuration files, and boilerplate code**.

Kitty solves this by providing **battle-tested project templates** that follow industry best practices:

- ✅ **Data Science** - Structured for reproducible research
- ✅ **AI/ML Applications** - Production-ready ML pipelines  
- ✅ **Research Projects** - Academic workflow with notebooks & papers
- ✅ **Backend APIs** - Clean architecture with FastAPI
- ✅ **Automation Scripts** - Modular automation tools

No more Googling "how to structure a Python project" — Kitty gives you the answer.

---

## 📦 Installation

```bash
pip install kitty-scaffold
```

**Requirements:** Python 3.8 or higher

That's it. No configuration needed. Works on Windows, macOS, and Linux.

---

## 🎯 Quick Start

### See All Available Templates

```bash
kitty list
```

### Create Your First Project

```bash
# Create a Data Science project
kitty init ds my_data_project
cd my_data_project
```

**You get:**
```
my_data_project/
├── data/
│   ├── raw/          # Original data (never modified)
│   ├── interim/      # Intermediate processing
│   └── processed/    # Final datasets
├── notebooks/
│   ├── 01_eda.ipynb
│   ├── 02_features.ipynb
│   └── 03_modeling.ipynb
├── src/              # Reusable Python modules
├── reports/figures/
├── requirements.txt
└── README.md
```

### Create an AI/ML Application

```bash
kitty init ai chatbot_app
```

**You get:**
```
chatbot_app/
├── src/
│   ├── models/       # Model architectures
│   ├── training/     # Training scripts
│   ├── inference/    # Prediction code
│   └── data/         # Data loaders
├── notebooks/        # Experiments
├── models_saved/     # Checkpoints
├── config/
└── tests/
```

### Create a Backend API

```bash
kitty init backend api_server
```

**You get:**
```
api_server/
├── src/app/
│   ├── api/          # Routes & endpoints
│   ├── services/     # Business logic
│   ├── models/       # Data models
│   ├── core/         # Config & security
│   └── main.py
├── tests/
├── .env.example
└── requirements.txt
```

---

## 🛠️ All Commands

| Command | Description |
|---------|-------------|
| `kitty init <type> <name>` | Create a new project |
| `kitty list` | List all available templates |
| `kitty help` | Show help information |

### Available Templates

| Template | Use Case | Key Features |
|----------|----------|-------------|
| `ds` | Data Science & Analytics | Jupyter notebooks, data pipeline, reproducible workflows |
| `research` | Academic Research | Paper drafts, experiments tracking, LaTeX-ready |
| `backend` | REST APIs & Services | FastAPI structure, database models, testing setup |
| `ai` | ML/AI Applications | Model training, inference, config management |
| `automation` | Scripts & Pipelines | Modular architecture, logging, config files |

---

## 💡 Examples

```bash
# Data Science project
kitty init ds customer_churn_analysis

# Research project
kitty init research quantum_computing_study

# Backend API
kitty init backend ecommerce_api

# AI application
kitty init ai image_classifier

# Automation tool
kitty init automation data_pipeline
```

---

## 🎓 Philosophy

Kitty follows these principles:

1. **Convention over Configuration** - Sensible defaults, zero setup
2. **Industry Best Practices** - Structures used by top companies
3. **Reproducibility** - Clean separation of data, code, and outputs
4. **Developer Experience** - Get started in seconds, not hours

---

## 🤝 Contributing

Contributions are welcome! To add a new template or improve existing ones:

1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-template`)
3. Commit your changes (`git commit -m 'Add amazing template'`)
4. Push to the branch (`git push origin feature/amazing-template`)
5. Open a Pull Request

---

## 📝 License

MIT License - see [LICENSE](LICENSE) file for details.

---

## 🌟 Why This Matters

Most students and developers copy-paste project structures from tutorials or old projects. This leads to:

- ❌ Inconsistent organization
- ❌ Missing best practices  
- ❌ Hard-to-maintain code
- ❌ Wasted time on setup

**Kitty gives you a professional starting point**, so you can focus on building, not organizing.

---

## 📊 Who Uses This?

Perfect for:

- 🎓 Students working on projects
- 🏆 Hackathon participants
- 🔬 Researchers running experiments
- 💼 Professionals starting new services
- 🚀 Developers building MVPs

---

## 🔗 Links

- **GitHub**: [bisal2003/Python_kitty](https://github.com/bisal2003/Python_kitty)
- **Documentation**: [Full README](https://github.com/bisal2003/Python_kitty#readme)
- **Issues**: [Report bugs](https://github.com/bisal2003/Python_kitty/issues)
- **PyPI**: [kitty-scaffold](https://pypi.org/project/kitty-scaffold/)

---

## ⚡ What's Next?

After installation, verify it works:

```bash
# Check installation
kitty --help

# List all templates
kitty list

# Create your first project
kitty init ds my_project
```

Pick a template and start building. **Your next great project is one command away.**

## 🐛 Troubleshooting

**Command not found after install?**
- Make sure Python's Scripts directory is in your PATH
- Try: `python -m pip install --upgrade kitty-scaffold`
- Restart your terminal

**Need help?** [Open an issue](https://github.com/bisal2003/Python_kitty/issues)

---

**Made with ❤️ for developers who value their time.**