# 🚀 Skyrelis PyPI Package Build & Publication Guide

This guide walks through building and publishing the Skyrelis AI Agent Security Library to PyPI.

## 📋 Prerequisites

1. **Python 3.8+** installed
2. **build** and **twine** packages:
   ```bash
   pip install build twine
   ```
3. **PyPI Account** at [pypi.org](https://pypi.org)
4. **TestPyPI Account** at [test.pypi.org](https://test.pypi.org) (recommended for testing)

## 🧪 Pre-Build Validation

Always run validation tests before building:

```bash
python test_skyrelis.py
```

Expected output:
```
🎉 SUCCESS! Skyrelis package is ready for PyPI publication!
```

## 📦 Building the Package

1. **Clean previous builds**:
   ```bash
   rm -rf dist/ build/ *.egg-info/
   ```

2. **Build the package**:
   ```bash
   python -m build
   ```

   This creates:
   - `dist/skyrelis-0.1.0.tar.gz` (source distribution)
   - `dist/skyrelis-0.1.0-py3-none-any.whl` (wheel distribution)

3. **Verify the build**:
   ```bash
   ls -la dist/
   ```

## 🧪 Testing on TestPyPI (Recommended)

1. **Upload to TestPyPI**:
   ```bash
   python -m twine upload --repository testpypi dist/*
   ```

2. **Test installation**:
   ```bash
   pip install --index-url https://test.pypi.org/simple/ skyrelis
   ```

3. **Test basic functionality**:
   ```python
   import skyrelis
   from skyrelis import observe
   print(f"Skyrelis v{skyrelis.__version__} working!")
   ```

## 🌍 Publishing to PyPI

Once testing is complete:

1. **Upload to PyPI**:
   ```bash
   python -m twine upload dist/*
   ```

2. **Verify publication**:
   ```bash
   pip install skyrelis
   ```

## 📄 Package Contents

```
skyrelis_package/
├── skyrelis/                    # Main package
│   ├── __init__.py             # Public API
│   ├── decorators.py           # Main decorators
│   ├── core/                   # Core components
│   │   ├── agent_observer.py
│   │   └── monitored_agent.py
│   ├── utils/                  # Utilities
│   │   ├── remote_observer_client.py
│   │   ├── opentelemetry_integration.py
│   │   └── langsmith_integration.py
│   └── config/                 # Configuration
│       └── observer_config.py
├── examples/                   # Usage examples
│   └── simple_usage.py
├── setup.py                   # Setup configuration
├── pyproject.toml             # Modern package config
├── README.md                  # Package documentation
├── LICENSE                    # MIT license
├── MANIFEST.in               # Package manifest
└── test_skyrelis.py          # Validation tests
```

## ✅ Quality Checklist

Before publishing, ensure:

- [ ] All tests pass (`python test_skyrelis.py`)
- [ ] Version number is correct in `setup.py` and `pyproject.toml`
- [ ] README.md is comprehensive and accurate
- [ ] LICENSE file is included
- [ ] Dependencies are properly specified
- [ ] Examples work correctly
- [ ] Package imports cleanly

## 🔧 Troubleshooting

### Build Issues

**Problem**: `ModuleNotFoundError` during build
**Solution**: Ensure all dependencies are installed:
```bash
pip install -r requirements.txt
```

**Problem**: `twine` upload fails
**Solution**: Check credentials and package name availability:
```bash
python -m twine check dist/*
```

### Import Issues

**Problem**: Package imports fail after installation
**Solution**: Check that all imports use relative paths and `__init__.py` files are present

### Dependency Issues

**Problem**: Users can't install due to dependency conflicts
**Solution**: Update version constraints in `setup.py` to be more flexible

## 🎯 Success Metrics

After publication, monitor:

- **PyPI Downloads**: Track adoption via PyPI statistics
- **GitHub Stars**: Monitor community interest
- **Issue Reports**: Address user problems quickly
- **Security Feedback**: Monitor for security-related issues

## 📚 Documentation

Post-publication tasks:

1. **Update GitHub README** to point to PyPI package
2. **Create documentation site** (ReadTheDocs recommended)
3. **Write blog posts** about AI agent security
4. **Engage with community** on forums and social media

## 🔒 Security Considerations

For a security library:

- **Security Reviews**: Get code reviewed by security experts
- **Vulnerability Scanning**: Use tools like `bandit` for security linting
- **Responsible Disclosure**: Set up security contact and disclosure process
- **Regular Updates**: Keep dependencies updated for security patches

---

**Happy Publishing! 🎉**

*Making AI agent security accessible to everyone.* 