PySyft

Secure and private Deep Learning library built on PyTorch and TensorFlow.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is PySyft?

PySyft is a Python library that enables secure and private deep learning by providing tools for differential privacy, federated learning, and secure multi-party computation. It's built on top of PyTorch and TensorFlow, making it easy to integrate into existing workflows while ensuring data privacy.

Key differentiator

PySyft stands out by providing a comprehensive set of tools for ensuring data privacy and security in deep learning, making it ideal for applications that handle sensitive information.

Capability profile

Strength Radar

Support for diff…Federated learni…Secure multi-par…Integration with…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Support for differential privacy

Federated learning capabilities

Secure multi-party computation

Integration with PyTorch and TensorFlow

Fit analysis

Who is it for?

✓ Best for

Teams working with sensitive data that require strict privacy guarantees

Developers looking to integrate federated learning into their applications

Researchers who need tools for secure multi-party computation in deep learning

✕ Not a fit for

Projects where performance is prioritized over privacy

Applications requiring real-time processing of large datasets without privacy constraints

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Next step

Get Started with PySyft

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →