PySyft
A Python library for performing data science and machine learning on data without direct access, using remote datasites.
What is PySyft?
PySyft is a Python library that enables remote data science on sensitive data without requiring data scientists to see or copy the data. It connects to secure 'datasites'—servers where data remains under the owner's control—allowing statistical analysis and machine learning while preserving privacy and compliance. This approach, termed 'structured transparency,' lets data owners define acceptable use policies and data scientists operate within those bounds.
Data scientists and researchers who need to analyze sensitive or private datasets (e.g., in healthcare, finance, or government) without direct access, as well as data owners (like organizations or institutions) who want to enable secure, policy-controlled data collaboration. It also targets developers building privacy-preserving data platforms using Docker or Kubernetes deployments.
Developers choose PySyft because it uniquely enables executing Python code, including third-party libraries, directly on remote data that never leaves the owner's server, balancing data utility with strict privacy controls. Its datasite architecture provides a deployable, policy-driven framework for secure data access, differentiating it from traditional data-sharing or federated learning tools by emphasizing owner-controlled, transparent workflows.
Overview
Perform data science on data that remains in someone else's server
Use Cases
Best For
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