MPyC: Multiparty Computation in Python

From VIFF, via TUeVIFF, to MPyC, launched on Wednesday May 30, 2018 at the Theory and Practice of Multiparty Computation (TPMPC) 2018 workshop in Aarhus, Denmark.

See MPyC--Python Package for Secure Multiparty Computation (PDF Slides) for some background information.

Use pip install mpyc for version 0.10 (April 16, 2024) of MPyC on PyPI. The documentation of this version is available at MPyC on github.io.

Use pip install git+https://github.com/lschoe/mpyc to get the latest version from GitHub, with up-to-date documentation at MPyC on readthedocs.io.

See github.com/lschoe/mpyc for source code and demos (Python scripts as well as Jupyter notebooks).

See what others are doing with MPyC: scholar.google.com/scholar?q=mpyc+multiparty.


hMPC for Multiparty Computation in Haskell!

Checkout Nick van Gils' wonderful counterpart of MPyC in Haskell: hMPC.

The hMPC package implements a nontrivial subset of MPyC, covering support for the id3gini.py demo for privacy-preserving training of ID3 decision trees, see Id3gini.hs.


Run MPyC in your browser!

Run MPyC with PyScript entirely inside your web browser without any install:

Try it out in the cloud!

Run MPyC without installing anything by running a Jupyter notebook in your browser with Binder: Or, click launch binder to work with the entire MPyC GitHub repo, running JupyterLab in your browser.
Check out this cool YouTube video on MPC by TNO to see where the MPyC logo MPyC logo comes from!

Also, preview future extension to "Verifiable MPyC", see github.com/toonsegers/verifiable_mpc for code and ZKProof 2019 video (ZKProof 2019 PowerPoint) for a presentation.


Last updated Tuesday, 06-Aug-2024 11:00:39 CEST by Berry Schoenmakers.