A library that extends PySyft with SMPC support.

SyMPC /ˈsɪmpəθi/ is a library which extends PySyft ≥0.3 with SMPC support. It allows computing over encrypted data, and to train and evaluate neural networks.


SyMPC is a companion library for PySyft. Therefore, we will need to install PySyft among other dependencies. We recommend using a virtual environment like conda.

$ conda create -n sympc python=3.9
$ conda activate sympc
$ pip install -r requirements.txt
$ pip install .

You can also run SyMPC using docker by running the following commands.

$ docker build -t sympc -f docker-images/Dockerfile .  #builds image named sympc
$ docker run -i -t sympc  #runs the container

Getting Started

If we want to start learning how to use SyMPC we can go to the examples folder and execute the introduction.ipynb.

$ conda activate sympc
$ pip install jupyter
$ jupyter notebook examples/introduction.ipynb

If we decided to use docker, we would need to run the image and publish the jupyter notebook port

$ sudo docker run -i -t -p 8888:8888 sympc
$ jupyter notebook examples/introduction.ipynb --allow-root --ip=

Finally, we would need to copy the url shown in the docker to our browser.