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