Skip to main content

OpenDP

Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public. License: MIT Python ci tests

OpenDP is a modular library of statistical algorithms that adhere to the definition of differential privacy. It can be used to build applications of privacy-preserving computations, using a number of different models of privacy. OpenDP is implemented in Rust, with bindings for easy use from Python.

The architecture of OpenDP is based on a conceptual framework for expressing privacy-aware computations. This framework is described in the paper A Programming Framework for OpenDP.

OpenDP (the library) is part of the larger OpenDP Project, a community effort to build trustworthy, open source software tools for analysis of private data.

Status

OpenDP is under development, and we aim to release new versions frequently. It's a work in progress, but we feel that OpenDP already can be used to build some useful applications. We also hope that it may be a vehicle for exploring new ideas in privacy. We welcome you to try it and look forward to feedback on the usability of the library! However, please be aware of the following limitations.

WARNING

OpenDP is not yet recommended for production deployments. It has known privacy concerns, particularly around floating point handling and side channel attacks. We expect to address these issues, but until then, please don't use OpenDP for any privacy-critical applications.

More details can be found in the Limitations section of the User Guide

Installation

The easiest way to install OpenDP is using pip (the package installer for Python):

% pip install opendp

More information can be found in the Getting Started section of the User Guide

Documentation

The full documentation for OpenDP is located at https://docs.opendp.org. Here are some helpful entry points:

Getting Help

If you're having problems using OpenDP, or want to submit feedback, please reach out! Here are some ways to contact us:

Contributing

OpenDP is a community effort, and we welcome your contributions to its development! If you'd like to participate, please see the Contributing section of the Developer Guide

Metadata

Release files for opendp 0.2.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for opendp 0.2.0
File Interpreter ABI Platform
opendp-0.2.0-py3-none-any.whl Python 3 none any Details

Release files / opendp-0.2.0-py3-none-any.whl

Download URL opendp-0.2.0-py3-none-any.whl
Size 15.8 MB
Tags Python 3
SHA-256 checksum
How to use checksums
6dcfe4c4d7f055a3221e6890fff64f42d74145686a3709c8886de986671653fd
BLAKE2b-256 checksum
How to use checksums
bdb131b48a3fb7157048fe8ff651cfd39bd64f249479d406774f1149b6e5ebc6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.6.14
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page