This release is a pre-release and may not be stable for production use.
MPLang: A Programming Language for Multi-Party Computation
MPLang is a Python-native library for building and executing multi-party and multi-device programs. It simplifies secure computation by allowing developers to write a single program that orchestrates multiple parties in a synchronous, SPMD (Single Program, Multiple Data) fashion.
Features
- Single-Controller SPMD: Write one program that runs across multiple parties in lockstep.
- Explicit Device Placement: Clearly annotate and control where data lives and computation happens (e.g., on party
P0,P1, or a secureSPU). - Function-Level Compilation: Use the
@mplang.functiondecorator to compile Python functions into an auditable, optimizable graph representation. - Pluggable Architecture: Easily extend MPLang with new frontends (like JAX) and backends (like StableHLO, SPU).
Getting Started
Installation
You'll need a modern Python environment (3.11+). We recommend using uv for fast installation.
# Install uv (if not already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh
# Install MPLang from PyPI
uv pip install mplang
Quick Example
Here's a taste of what MPLang looks like. This example shows a "millionaire's problem" where two parties compare their wealth without revealing it.
import mplang as mp
from numpy.random import randint
# Use a decorator to compile this function for multi-party execution
@mp.function
def millionaire():
# Alice's value, placed on device P0
x = mp.device("P0")(randint)(0, 1000000)
# Bob's value, placed on device P1
y = mp.device("P1")(randint)(0, 1000000)
# The comparison happens on a secure device (SPU)
z = mp.device("SP0")(lambda a, b: a < b)(x, y)
return z
# Set up a local simulator with 2 parties
sim = mp.Simulator.simple(2)
# Evaluate the compiled function
result = mp.evaluate(sim, millionaire)
# Securely fetch the result (reveals SPU value)
print("Is Alice poorer than Bob?", mp.fetch(sim, result))
Learn More
- Tutorials: Check out the
tutorials/directory for in-depth, runnable examples covering conditions, loops, and more. - Contributing: We welcome contributions! See our Contributing Guide to get started with the development setup.
License
MPLang is licensed under the Apache 2.0 License.
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