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 (3.11+). 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.

Metadata

Release files for mplang-nightly 0.1.dev301

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.dev301
File Size Uploaded
mplang_nightly-0.1.dev301.tar.gz 394.4 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for mplang-nightly 0.1.dev301
File Interpreter ABI Platform
mplang_nightly-0.1.dev301-py3-none-any.whl Python 3 none any Details

Total release size: 736.1 kB

Release files / mplang_nightly-0.1.dev301.tar.gz

Download URL mplang_nightly-0.1.dev301.tar.gz
Size 394.4 kB
Tags Source
SHA-256 checksum
How to use checksums
866a884d404e5aedf245d517a41479801bb677a9ba0ffff71433b1bd5f8f7877
BLAKE2b-256 checksum
How to use checksums
6c119a2de6e10d832019b63449c7bd39c4c714d2a3f36b6469db97d30b098f44
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via Hatch/1.16.5 cpython/3.11.14 HTTPX/0.28.1

Release files / mplang_nightly-0.1.dev301-py3-none-any.whl

Download URL mplang_nightly-0.1.dev301-py3-none-any.whl
Size 341.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
870f2460506ad32304cafb4072758de5a79ae4eb8f9f548a406f147835016346
BLAKE2b-256 checksum
How to use checksums
5775e0cf8bbf56087fac5de741769a19928cc51f2d6e0be8b106c29b9f0bbd36
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via Hatch/1.16.5 cpython/3.11.14 HTTPX/0.28.1

Release history Release notifications | RSS feed

This release

0.1.dev301 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