lightgbm-rs

Python bindings for LightGBM-rs — a pure-Rust reimplementation of Microsoft's LightGBM gradient-boosting library, numerically faithful to the C++ reference (~1e-6 absolute on the CPU anchor) and built on PyO3.

The package mirrors the official lightgbm low-level surface for the in-scope APIs, so you can switch import lightgbm → import lightgbm_rs:

import numpy as np
import lightgbm_rs as lgb

X = np.random.standard_normal((1000, 10))
y = X @ np.random.standard_normal(10)

ds = lgb.Dataset(X, y)
model = lgb.train({"objective": "regression", "num_leaves": 31}, ds, num_boost_round=100)
pred = model.predict(X)  # owned numpy array

Input is marshalled into owned Rust buffers and the GIL is released (Python::detach) around the CPU-bound train/predict, so background Python threads make progress during training.

Building from source

pip install maturin
maturin develop --release   # inside this directory, into your active venv

See the workspace root for the full project, license, and the numerical-parity contract.

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