Project Lighthouse Anonymize

Privacy-preserving data anonymization using k-anonymity and related algorithms.

Installation

pip install project-lighthouse-anonymize

Documentation

Full documentation: https://project-lighthouse-anonymize.readthedocs.io

• Getting Started Guide
• API Reference

Publications

This work builds on research into privacy-preserving data analysis:

• Measuring Discrepancies in Airbnb Guest Acceptance Rates Using Anonymized Demographic Data - The foundational paper for Project Lighthouse
• Core Mondrian: Scalable Mondrian for Partition-Based Anonymization - Covers the anonymization algorithm
• Measuring data quality for Project Lighthouse - Covers the way we measure the impact of anonymization

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Releasing

To create a new release, use the /release command in Claude Code. This will:

1. Analyze changes since the last release
2. Propose an appropriate version bump following semantic versioning
3. Update CHANGELOG.md
4. Create and push a git tag
5. Trigger automated PyPI publishing via GitHub Actions

License

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

Acknowledgments

Developed by the Airbnb Anti-Discrimination & Equity team.

Citation

If you use this software in your research, please cite:

Bloomston, A., & Airbnb Anti-Discrimination & Equity Engineering Team. (2026).
Project Lighthouse Anonymize. https://github.com/airbnb/project-lighthouse-anonymize

BibTeX:

@software{bloomston2025lighthouse,
  author = {Bloomston, Adam and {Airbnb Anti-Discrimination \& Equity Engineering Team}},
  title = {Project Lighthouse Anonymize},
  year = {2026},
  url = {https://github.com/airbnb/project-lighthouse-anonymize},
  license = {MIT}
}