PipelineDP is a Python framework for applying differentially private aggregations to large datasets using batch processing systems such as Apache Spark, Apache Beam, and more.

The core library of differential privacy algorithms powering the OpenDP Project.

RAPPOR: Privacy-Preserving Reporting Algorithms

The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy

Library for training machine learning models with privacy for training data

Diffprivlib: The IBM Differential Privacy Library