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.dev152
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.dev152.tar.gz | 313.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mplang_nightly-0.1.dev152-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 517.6 kB
Release files / mplang_nightly-0.1.dev152.tar.gz
| Download URL | mplang_nightly-0.1.dev152.tar.gz |
|---|---|
| Size | 313.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
34e2f01ebd6f4a52560b3803e7b56e1b77da3ddfe35eefee65bebbb8de9a0c5f
|
|
BLAKE2b-256 checksum How to use checksums |
fecf34acefa4f175c6fd44579bb5529cf6f7f12aba04f1b87df907423188b944
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
python-httpx/0.28.1
|
Release files / mplang_nightly-0.1.dev152-py3-none-any.whl
| Download URL | mplang_nightly-0.1.dev152-py3-none-any.whl |
|---|---|
| Size | 204.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
56f2495fb949d24324b2b5ab20ca23fd894a732889114e388ff718f28bc01122
|
|
BLAKE2b-256 checksum How to use checksums |
d5250373626c966c214e3602d4ad2a6b6c6500ec9d5e9269e6d0047243ed94c7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
python-httpx/0.28.1
|
