Privacy Preserving Python Packages

humbug

Get usage metrics and crash reports for your API, library, or command line tool.

spu

SPU (Secure Processing Unit) aims to be a provable, measurable secure computation device, which provides computation ability while keeping your private data protected.

anonlink

Python implementation of anonymous linkage using cryptographic linkage keys

secretflow

A unified framework for privacy-preserving data analysis and machine learning

pycanon

pyCANON is a Python library and CLI to assess the values of the parameters associated with the most common privacy-preserving techniques.

secretflow-serving-lib

SecretFlow-Serving is a serving system for privacy-preserving machine learning models.

secretflow-lite

A unified framework for privacy-preserving data analysis and machine learning

holographic-vsa

High-performance Holographic Memory System (HMS) for Node.js, powered by Rust. This library implements Vector Symbolic Architectures (VSA) using Binary Spatter Code (BSC) to enable semantic search, analogical reasoning, and associative memory at scale.

ammp

Reference implementation of AMMP (Agentic Mentor-Mentee Protocol, draft-arturo-ammp-01), Mentoring track, on FastMCP. Multi-mentor + multi-mentee, LLM-synthesised AskMentor with confidence-driven escalation.

dp-sequential-events

Differential privacy for sequential event logs, anonymizing case IDs and timestamps while preserving statistical properties.

secretflow-rayfed

A multiple parties joint, distributed execution engine based on Ray, to help build your own federated learning frameworks in minutes.

rayfed-nightly

A multiple parties joint, distributed execution engine based on Ray, to help build your own federated learning frameworks in minutes.

fate-test

An Industrial Grade Federated Learning Framework

indexnetwork-sdk

Social Discovery Protocol

cardinalitykit

A comprehensive Python toolkit for cardinality estimation algorithms (Flajolet-Martin, LogLog, SuperLogLog, HyperLogLog, HyperReal) — enabling privacy-preserving analytics, audience measurement, and sample-to-population extrapolation through probabilistic counting techniques.

privjedai

An open-source library that leverages Python’s data science ecosystem to build powerful end-to-end Privacy Preserving Record Linkage workflows.

insurance-synthetic

Vine copula synthetic portfolio generation for insurance — exposure-aware, fidelity reporting

sage-testsuite

An Industrial Grade Federated Learning Framework

secretflow-spec

SecretFlow Open Specification is a protocol stack designed for privacy-preserving applications.

sf-sml

SPU (Secure Processing Unit) aims to be a provable, measurable secure computation device, which provides computation ability while keeping your private data protected.

spark-privacy-preserver

Anonymizing Library for Apache Spark

ai-mysql-translator

A new package enables AI systems to securely interact with MySQL databases by translating natural language queries into structured SQL commands. It processes user text input to generate safe, validate

flypaper

Get usage metrics and crash reports for your API, library, or command line tool.

trustflow-csv-generation

A privacy-preserving computing system based on TEE.