This repository contains the pilot implementation of the core privacy methods for Energy Differential Privacy (EDP). The key components are:

• Core Differential Privacy for energy efficiency analytics (eeprivacy)
• Python API documentation for eeprivacy
• Sample implementations of key use cases

Examples and library documentation

Energy Differential Privacy (EDP) enables the use of the gold standard of privacy protection, differential privacy, for high value energy efficiency analytics.

pip install eeprivacy

Notebooks

With your preferred notebook environment (like JupyterLab or nteract), install eeprivacy and try out any of the example notebooks.

REPL

>>> from eeprivacy.mechanisms import LaplaceMechanism
>>> LaplaceMechanism.execute(value=0, epsilon=0.1, sensitivity=1)
1.198515653814998

Build docs:

./bin/build_docs

Run tests:

./bin/test