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, 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.
1 maintainer
Metadata
1 maintainer
Release files for mplang-nightly 0.1.dev156
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mplang_nightly-0.1.dev156.tar.gz | 314.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mplang_nightly-0.1.dev156-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 520.5 kB
Release files / mplang_nightly-0.1.dev156.tar.gz
| Download URL | mplang_nightly-0.1.dev156.tar.gz |
|---|---|
| Size | 314.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
763a5206c8cdb34f06881464f27daa4d17de2408d3b390568e065b2a2aaa8cd7
|
|
BLAKE2b-256 checksum How to use checksums |
bfd3617f41b4fe3abad0052404f1356f17309d2d577e3f6bbfc0606b201451fc
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
python-httpx/0.28.1
|
Release files / mplang_nightly-0.1.dev156-py3-none-any.whl
| Download URL | mplang_nightly-0.1.dev156-py3-none-any.whl |
|---|---|
| Size | 205.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
693967fa6700493fa349bd755a6194b330d1d4485b4844c1789005d3b23efe0b
|
|
BLAKE2b-256 checksum How to use checksums |
797381b9b24acb0fd007f473a91ae115c33a8e2280430f9704922fc1adfd614e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
python-httpx/0.28.1
|
