Skip to main content

Multi-Party Programming Language

Project description

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, Ibis) 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
import mplang.device as mpd
from numpy.random import randint

# Use a decorator to compile this function for multi-party execution
@mplang.function
def millionaire():
    # Alice's value, placed on device P0
    x = mpd.device("P0")(randint)(0, 1000000)
    # Bob's value, placed on device P1
    y = mpd.device("P1")(randint)(0, 1000000)
    # The comparison happens on a secure device (SPU)
    z = mpd.device("SPU")(lambda a, b: a < b)(x, y)
    return z

# Set up a local simulator with 2 parties
sim = mplang.Simulator(2)

# Evaluate the compiled function
result = mplang.eval(sim, millionaire)

# Securely fetch the result
print("Is Alice poorer than Bob?", mplang.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.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mplang_nightly-0.1.dev143.tar.gz (307.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mplang_nightly-0.1.dev143-py3-none-any.whl (200.7 kB view details)

Uploaded Python 3

File details

Details for the file mplang_nightly-0.1.dev143.tar.gz.

File metadata

  • Download URL: mplang_nightly-0.1.dev143.tar.gz
  • Upload date:
  • Size: 307.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-httpx/0.28.1

File hashes

Hashes for mplang_nightly-0.1.dev143.tar.gz
Algorithm Hash digest
SHA256 0e67e7ab87714581c68d1f97cfab463736dba1a9ee4df96c39d46a043b024b1f
MD5 b306c7aeaa985a651209641937828466
BLAKE2b-256 a408083df82cd12b603c19fbaa24e89dff8cc05c9efb1ed225543362d616a128

See more details on using hashes here.

File details

Details for the file mplang_nightly-0.1.dev143-py3-none-any.whl.

File metadata

File hashes

Hashes for mplang_nightly-0.1.dev143-py3-none-any.whl
Algorithm Hash digest
SHA256 7a32f19abcf43a4847b14bb7089ac3bd32fd5a758c4fc90250b21a68d9af1658
MD5 f761aa988e9216954ca0abeb57b696ee
BLAKE2b-256 fad44412f35723de0c0f87c0811170e10f8478640d1c14fb59ec50ea94273fb7

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page