eeprivacy
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](https://openeemeter.github.io/eeprivacy/)
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Energy Differential Privacy (EDP) enables the use of the gold standard of privacy protection, differential privacy, for high value energy efficiency analytics.
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Installation
pip install eeprivacy
Local Usage
Notebooks
With your preferred notebook environment (like [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) or [nteract](https://nteract.io/)), install eeprivacy and try out any of the [example notebooks](https://openeemeter.github.io/eeprivacy/private-load-shape-algorithm-design.html).
REPL
>>> from eeprivacy.mechanisms import LaplaceMechanism >>> LaplaceMechanism.execute(value=0, epsilon=0.1, sensitivity=1) 1.198515653814998
Development
Build docs:
./bin/build_docs
Run tests:
./bin/test
1 maintainer
Metadata
1 maintainer
Release files for eeprivacy 0.0.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| eeprivacy-0.0.5.tar.gz | 5.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| eeprivacy-0.0.5-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 16.2 kB
Release files / eeprivacy-0.0.5.tar.gz
| Download URL | eeprivacy-0.0.5.tar.gz |
|---|---|
| Size | 5.8 kB |
| Tags | Source |
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Release files / eeprivacy-0.0.5-py2.py3-none-any.whl
| Download URL | eeprivacy-0.0.5-py2.py3-none-any.whl |
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| Size | 10.4 kB |
| Tags | Python 2 Python 3 |
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