lightgbm

LightGBM Python-package

lightgbm License unclear Active ★ 18,682 v4.7.0 released 2026-07-18

Install

lightgbm on PyPI

pip

pip install lightgbm

uv

uv add lightgbm

poetry

poetry add lightgbm

Package facts

License	not declared (unclear)
Python support	supports the current Python release (>=3.10)
Install friction	medium — platform-specific wheel
Runtime dependencies	3 — narwhals, numpy, scipy
Maintenance	actively maintained — 26 days since the last release
Last repo commit	2026-08-11
First released	2017-06-20
Popularity	one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13)
Known vulnerabilities	none known (OSV.dev, checked 2026-08-13)

Evidence: lightgbm-4.7.0-py3-none-macosx_10_15_x86_64.whl; lightgbm-4.7.0-py3-none-macosx_12_0_arm64.whl; lightgbm-4.7.0-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; lightgbm-4.7.0-py3-none-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; lightgbm-4.7.0-py3-none-win_amd64.whl

Development Status :: 5 - Production/StableIntended Audience :: Science/ResearchNatural Language :: EnglishOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIXOperating System :: UnixProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: Artificial Intelligence

About lightgbm

from the package's own PyPI description — quoted content, verbatim

LightGBM Python-package

Installation

Preparation '''''''''''

32-bit Python is not supported. Please install 64-bit version. If you have a strong need to install with 32-bit Python, refer to Build 32-bit Version with 32-bit Python section <#build-32-bit-version-with-32-bit-python>__.

Install from PyPI <https://pypi.org/project/lightgbm>_ ''''''''''''''''''''''''''''''''''''''''''''''''''''''''

.. code:: sh

pip install lightgbm

Compiled library that is included in the wheel file supports both GPU (don't confuse with CUDA version) and CPU versions out of the box. This feature is available only for Windows and Linux currently. To use GPU version you only need to install OpenCL Runtime libraries. For NVIDIA and AMD GPU they are included in the ordinary drivers for your graphics card, so no action is required. If you would like your AMD or Intel CPU to act like a GPU (for testing and debugging), you can install `AMD APP SDK...

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AI interpretation — verify before relying

AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page

LightGBM is a fast, distributed gradient boosting framework for classification, regression, and ranking tasks that works with numpy, scipy, and narwhals dataframe libraries.

Medium install friction due to compiled C++ components; pre-built wheels available for macOS (x86_64 and arm64), Linux (aarch64 and x86_64), and Windows. Requires 64-bit Python 3.10+. macOS users need OpenMP (installable via brew); Windows users may need VC runtime if Visual Studio is absent.

Usage

pip install lightgbm
import lightgbm as lgb
model = lgb.LGBMClassifier()
model.fit(X_train, y_train)

Requires 64-bit Python 3.10 or later; macOS users must install OpenMP library (brew install libomp); Windows users may need VC runtime.

Verdict: LightGBM 4.7.0 is a production-stable, actively maintained gradient boosting library with no known vulnerabilities. It has medium install friction due to compiled dependencies but offers pre-built wheels for major platforms. License treatment is unclear, which warrants verification before adoption in proprietary contexts.

Needs verification

What is the actual license (SPDX identifier or raw license text) for lightgbm 4.7.0?
Does the compiled library in wheels support GPU acceleration out-of-the-box on all platforms, or only Windows/Linux as stated?
Are there any known compatibility issues with the three runtime dependencies (narwhals, numpy, scipy) at specific versions?

gradient boosting machine learninglightgbm classifier regressorfast gradient boosting frameworkdistributed tree boostinggbdt gradient descent decision treeslightgbm python packageboosting algorithm implementation