A practical engine for Secure Multiparty Computation (SMPC) that is part of privacy-enhancing technologies (PETs). QuickMPC can perform computations on personal data used in fundamental static calculations while keeping confidentiality.
This will enable businesses and engineers worldwide to use Python client libraries to easily develop SaaS products that utilize SMPC functions without the need for expert SMPC knowledge.

You can easily describe a process using SMPC as follows:
makedockerdocker-composevscode-yaml-sortThe demonstration with libClient-py
16 GB20 GBscripts/cd QuickMPC/scripts
make debug t=./manage_container
scripts/cd QuickMPC/scripts
# Testing all containers
make test
# Only the Computation Container test
make test t=./computation_container/
# Only the Manage Container test
make test t=./manage_container/
This section is usefule when you want to stand 2 containers and dare to test manually.
make debug t=./computation_container # Launch of the dev_cc{1,2,3}
make debug t=./manage_container # Then, all container is launched
cd packages/server/computation_container
make upd
make login
cd QuickMPC
# build
bazel build //:all
# test
bazel test ... --test_env=IS_TEST=true --test_output=errors
The files generated by bazel can be removed by running the following in the /QuickMPC directory in the container
bazel clean
cd packages/server/manage_container
make upd
make login
# Create a vendor directory directly under QuickMPC and copy all dependent packages
go mod vendor
# build
go build
# test
go test ... -v