https://github.com/opendp/tumult-analytics
Tumult Analytics is a Python library for privately computing aggregate queries on tabular data. It is built atop the Tumult Core library.
https://github.com/opendp/tumult-analytics
differential-privacy privacy pyspark
Last synced: 6 months ago
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Tumult Analytics is a Python library for privately computing aggregate queries on tabular data. It is built atop the Tumult Core library.
- Host: GitHub
- URL: https://github.com/opendp/tumult-analytics
- Owner: opendp
- License: apache-2.0
- Created: 2025-05-07T17:25:23.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-11-08T12:02:57.000Z (8 months ago)
- Last Synced: 2025-11-08T14:16:00.372Z (8 months ago)
- Topics: differential-privacy, privacy, pyspark
- Language: Python
- Homepage:
- Size: 4.88 MB
- Stars: 12
- Watchers: 7
- Forks: 4
- Open Issues: 34
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.rst
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Notice: NOTICE
Awesome Lists containing this project
README
[](https://pypi.org/project/tmlt-analytics/) |
[](https://docs.tmlt.dev/analytics/latest/) |
[][slack]
[slack]: https://join.slack.com/t/opendp/shared_invite/zt-1aca9bm7k-hG7olKz6CiGm8htI2lxE8w
# Tumult Analytics — an OpenDP project
Tumult Analytics is a Python library to execute differentially private
operations on data, with a strong emphasis on usability and scalability. It is
built atop the [Tumult Core library](https://github.com/opendp/tumult-core).
It was originally developed by
[Tumult Labs](https://www.linkedin.com/company/tmltlabs), and joined the
[OpenDP project](https://opendp.org) after the Tumult Labs team joined LinkedIn.
## Demo video
Want to see Tumult Analytics in action? Check out this video introducing the
interface fundamentals:
[](https://www.youtube.com/watch?v=SNfbYOp0CEs)
A selection of more advanced features is shown on the second part of this demo,
in a [separate video](https://www.youtube.com/watch?v=BRUPlfwzHHo).
## Installation
See the [installation instructions in the documentation](https://docs.tmlt.dev/analytics/latest/installation.html#prerequisites)
for information about setting up prerequisites such as Spark.
Once the prerequisites are installed, you can install Tumult Analytics using [pip](https://pypi.org/project/pip).
```bash
pip install tmlt.analytics
```
## Documentation
The full documentation is located at https://docs.tmlt.dev/analytics/latest/.
## Support
If you have any questions, feedback, or feature requests, please reach out via the [OpenDP Slack][slack].
## Contributing
We welcome external volunteers! If you are interested in contributing, please
let us know on [Slack][slack].
See [CONTRIBUTING.md](https://github.com/opendp/tumult-analytics/blob/main/CONTRIBUTING.md) for information about installing our development dependencies and running tests.
## Citing Tumult Analytics
If you use Tumult Analytics for a scientific publication, we would appreciate citations to the published software or/and its whitepaper. Both citations can be found below; for the software citation, please replace the version with the version you are using.
```
@software{tumultanalyticssoftware,
author = {Tumult Labs},
title = {Tumult {{Analytics}}},
month = dec,
year = 2022,
version = {latest},
url = {https://tmlt.dev}
}
```
```
@article{tumultanalyticswhitepaper,
title={Tumult {{Analytics}}: a robust, easy-to-use, scalable, and expressive framework for differential privacy},
author={Berghel, Skye and Bohannon, Philip and Desfontaines, Damien and Estes, Charles and Haney, Sam and Hartman, Luke and Hay, Michael and Machanavajjhala, Ashwin and Magerlein, Tom and Miklau, Gerome and Pai, Amritha and Sexton, William and Shrestha, Ruchit},
journal={arXiv preprint arXiv:2212.04133},
month = dec,
year={2022}
}
```
## License
Tumult Analytics' source code is licensed under the Apache License, version 2.0
(Apache-2.0). Tumult Analytics' documentation is licensed under Creative Commons
Attribution-ShareAlike 4.0 International (CC-BY-SA-4.0).