Medium Converter

Convert Medium articles to various formats with optional LLM enhancement.

Features

• 📚 Multiple export formats: Markdown, PDF, HTML, LaTeX, EPUB, DOCX
• 🤖 LLM enhancement: Improve clarity and fix grammar with AI
• 🔓 Paywall access: Use your browser cookies to access articles behind the paywall
• 🎨 Custom styling: Customize the output appearance
• ⚡ Async processing: Efficient batch conversion

Installation

# Basic installation
pip install medium-converter

# With PDF support
pip install medium-converter[pdf]

# With LLM enhancement using OpenAI
pip install medium-converter[llm,openai]

# All features
pip install medium-converter[all]

Quick Start

Command Line

# Convert to Markdown (default)
medium convert https://medium.com/example-article

# Convert to PDF with enhancement
medium convert https://medium.com/example-article -f pdf --enhance

Python API

import asyncio
from medium_converter import convert_article

async def main():
    # Basic conversion
    await convert_article(
        url="https://medium.com/example-article",
        output_format="markdown",
        output_path="article.md"
    )
    
    # With enhancement
    await convert_article(
        url="https://medium.com/example-article",
        output_format="pdf",
        output_path="article.pdf",
        enhance=True
    )

if __name__ == "__main__":
    asyncio.run(main())

Development Guide

Prerequisites

• Python 3.11+
• Poetry for dependency management

Setting Up Development Environment

# Clone the repository
git clone https://github.com/MarcusElwin/medium-converter.git
cd medium-converter

# Install dependencies with Poetry
poetry install --all-extras

# Activate virtual environment
poetry shell

Running Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=medium_converter

Code Quality

# Run type checking
mypy medium_converter

# Run linting
ruff medium_converter

# Format code
black medium_converter

Building Documentation

# Build documentation
mkdocs build

# Serve documentation locally
mkdocs serve

Project Structure

medium-converter/
├── medium_converter/       # Main package
│   ├── __init__.py         # Public API & version
│   ├── cli.py              # CLI interface
│   ├── core/               # Core functionality
│   ├── exporters/          # Export formats
│   ├── llm/                # LLM integration
│   └── utils/              # Utilities
├── tests/                  # Test suite
├── docs/                   # Documentation
├── examples/               # Example scripts
├── pyproject.toml          # Project configuration
└── README.md               # Project readme

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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

See Contributing Guide for more details.

Documentation

For detailed documentation, visit medium-converter.readthedocs.io.

LLM Providers

Medium Converter supports multiple LLM providers for content enhancement:

• OpenAI (GPT models)
• Anthropic (Claude models)
• Google (Gemini models)
• Mistral AI
• Local models (via llama-cpp-python)

License

MIT License - See LICENSE for details.