https://github.com/felixleopoldo/benchpress

Scalable open-source software to run, develop, and benchmark causal discovery algorithms
https://github.com/felixleopoldo/benchpress

bayesian-networks benchmarking causal-discovery causal-models causality graphical-models markov-networks reproducible-research snakemake-workflow structure-learning

Last synced: 29 days ago
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Scalable open-source software to run, develop, and benchmark causal discovery algorithms

• Host: GitHub
• URL: https://github.com/felixleopoldo/benchpress
• Owner: felixleopoldo
• License: gpl-2.0
• Created: 2020-01-15T13:26:10.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2025-09-28T21:46:44.000Z (about 1 month ago)
• Last Synced: 2025-09-28T23:24:38.351Z (about 1 month ago)
• Topics: bayesian-networks, benchmarking, causal-discovery, causal-models, causality, graphical-models, markov-networks, reproducible-research, snakemake-workflow, structure-learning
• Language: Python
• Homepage: https://benchpressdocs.readthedocs.io
• Size: 124 MB
• Stars: 72
• Watchers: 4
• Forks: 20
• Open Issues: 24
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

Awesome Lists containing this project

README

          

  











[![Snakemake](https://img.shields.io/badge/snakemake-≥7.30.1-brightgreen.svg)](https://snakemake.bitbucket.io)

[![Documentation Status](https://readthedocs.org/projects/benchpressdocs/badge/?version=latest)](https://benchpressdocs.readthedocs.io/en/latest/?badge=latest)

[![License: GPL v2](https://img.shields.io/badge/License-GPL%20v2-blue.svg)](https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html)

---

Benchpress [[1]](#1) is a [Snakemake](https://snakemake.readthedocs.io/en/stable/) workflow where structure learning (sometimes called causal discovery) algorithms, implemented in possibly different languages, can be executed and compared.

The computations scale seamlessly on multiple cores or *"... to server, cluster, grid and cloud environments, without the need to modify the workflow definition" - Snakemake*.

The documentation is found at https://benchpressdocs.readthedocs.io. 

The following main functionalities are provided by Benchpress 

* Benchmarks - Benchmark structure learning algorithms.

* Algorithm development - Benchmark your own algorithm along with the existing ones while developing.

* Data analysis - Estimate the underlying graph structure for your own dataset(s).

You may also have a look at [this Medium story](https://medium.com/@felixleopoldorios/structure-learning-using-benchpress-826847db0aa8) for an introduction.

## Citing

```

@Article{Benchpress,

    author = {Felix L. Rios and Giusi Moffa and Jack Kuipers},

    title = {{Benchpress}: A Versatile Platform for Structure Learning in Causal and Probabilistic Graphical Models},

    journal = {Journal of Statistical Software},

    year = {2025},

    volume = {114},

    number = {12},

    pages = {1--43},

    doi = {10.18637/jss.v114.i12}

}

```

## Contact

For problems, bug reporting, or questions please raise an issue or open a discussion thread.

## Contributing

Contributions are very welcomed. See [CONTRIBUTING.md](CONTRIBUTING.md) for instructions. 

1. Fork it!

2. Create your feature branch: `git checkout -b my-new-feature`

3. Commit your changes: `git commit -am 'Add some feature'`

4. Push to the branch: `git push origin my-new-feature`

5. Open a pull request

## License

This project is licensed under the GPL-2.0 License - see the [LICENSE](LICENSE) file for details

  

## References

* [1] [Felix L. Rios and Giusi Moffa and Jack Kuipers Benchpress: A Versatile Platform for Structure Learning in Causal and Probabilistic Graphical Models. *Journal of Statistical Software.*, 10.18637/jss.v114.i12, 2025.](https://doi.org/10.18637/jss.v114.i12)