Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

MPLang: A Programming Language for Multi-Party Computation

CircleCI Lint Mypy License

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 secure SPU).
  • Function-Level Compilation: Use the @mplang.function decorator 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 (3.10+). 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.

Metadata

Release files for mplang-nightly 0.1.dev219

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for mplang-nightly 0.1.dev219
File Size Uploaded
mplang_nightly-0.1.dev219.tar.gz 367.2 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for mplang-nightly 0.1.dev219
File Interpreter ABI Platform
mplang_nightly-0.1.dev219-py3-none-any.whl Python 3 none any Details

Total release size: 605.1 kB

Release files / mplang_nightly-0.1.dev219.tar.gz

Download URL mplang_nightly-0.1.dev219.tar.gz
Size 367.2 kB
Tags Source
SHA-256 checksum
How to use checksums
096f2a1daa59dbe22593fadfa0e33ce67dba05144a2800e0747f2a2a50fbda49
BLAKE2b-256 checksum
How to use checksums
2f887bc1304e8fb7f5c84d92e1e600db0e0d2c0bec7f4124b684d1bb8b1e90e8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via Hatch/1.16.1 cpython/3.10.19 HTTPX/0.28.1

Release files / mplang_nightly-0.1.dev219-py3-none-any.whl

Download URL mplang_nightly-0.1.dev219-py3-none-any.whl
Size 237.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
8a81a95706ab50cb4668f3bae36306b8e11d59d0f4ce064f22bac04931b3056e
BLAKE2b-256 checksum
How to use checksums
c1e8226257e26c8aac8f883db5dc4aa816192a6dcf7ea5744867718b6aeb9d60
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via Hatch/1.16.1 cpython/3.10.19 HTTPX/0.28.1

Release history Release notifications | RSS feed

This release

0.1.dev219 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page