lightgbm 4.3.0

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.

setuptools is needed.

Install from PyPI

pip install lightgbm

Compiled library that is included in the wheel file supports both GPU and CPU versions out of the box. This feature is experimental and 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 on Windows and PoCL on Linux. Many modern Linux distributions provide packages for PoCL, look for pocl-opencl-icd on Debian-based distributions and pocl on RedHat-based distributions.

For Windows users, VC runtime is needed if Visual Studio (2015 or newer) is not installed.

For Linux users, glibc >= 2.14 is required for LightGBM <=3.3.3 and glibc >= 2.28 is required for newer versions. Also, in some rare cases, when you hit OSError: libgomp.so.1: cannot open shared object file: No such file or directory error during importing LightGBM, you need to install OpenMP runtime library separately (use your package manager and search for lib[g|i]omp for doing this).

For macOS (we provide wheels for 3 newest macOS versions) users:

• Starting from version 2.2.1, the library file in distribution wheels is built by the Apple Clang (Xcode_8.3.3 for versions 2.2.1 - 2.3.1, Xcode_9.4.1 for versions 2.3.2 - 3.3.2 and Xcode_11.7 from version 4.0.0) compiler. This means that you don’t need to install the gcc compiler anymore. Instead of that you need to install the OpenMP library, which is required for running LightGBM on the system with the Apple Clang compiler. You can install the OpenMP library by the following command: brew install libomp.

• For version smaller than 2.2.1 and not smaller than 2.1.2, gcc-8 with OpenMP support must be installed first. Refer to Installation Guide for installation of gcc-8 with OpenMP support.

• For version smaller than 2.1.2, gcc-7 with OpenMP is required.

pip install 'lightgbm[dask]'

pip install 'lightgbm[pandas]'

pip install 'lightgbm[scikit-learn]'

pip install --no-binary lightgbm lightgbm

pip install lightgbm --config-settings=cmake.define.USE_OPENMP=OFF

pip install lightgbm --config-settings=cmake.define.USE_MPI=ON

pip install lightgbm --config-settings=cmake.define.USE_GPU=ON

pip install lightgbm \
  --config-settings=cmake.define.USE_GPU=ON \
  --config-settings=cmake.define.OpenCL_INCLUDE_DIR="/usr/local/cuda/include/" \
  --config-settings=cmake.define.OpenCL_LIBRARY="/usr/local/cuda/lib64/libOpenCL.so"

pip install lightgbm --config-settings=cmake.define.USE_CUDA=ON

pip install lightgbm --config-settings=cmake.define.USE_HDFS=ON

# in sh.exe, git bash, or other Unix-like shell
export CMAKE_GENERATOR='MinGW Makefiles'
pip install lightgbm --config-settings=cmake.define.CMAKE_SH=CMAKE_SH-NOTFOUND

# in sh.exe, git bash, or other Unix-like shell
export CMAKE_GENERATOR='Visual Studio 17 2022'
export CMAKE_GENERATOR_PLATFORM='Win32'
pip install --no-binary lightgbm lightgbm

pip install lightgbm --config-settings=cmake.define.USE_TIMETAG=ON

Install from conda-forge channel

If you use conda to manage Python dependencies, you can install LightGBM using conda install.

We strongly recommend installation from the conda-forge channel and not from the default one due to many reasons. The main ones are less time delay for new releases, greater number of supported architectures and better handling of dependency conflicts, especially workaround for OpenMP is crucial for LightGBM. More details can be found in this comment.

Note: The lightgbm conda-forge feedstock is not maintained by LightGBM maintainers.

conda install -c conda-forge lightgbm

Install from GitHub

All requirements from Build from Sources section apply for this installation option as well.

For Windows users, if you get any errors during installation and there is the warning WARNING:LightGBM:Compilation with MSBuild from existing solution file failed. in the log, you should install CMake (version 3.8 or higher).

git clone --recursive https://github.com/microsoft/LightGBM.git
# export CXX=g++-7 CC=gcc-7  # macOS users, if you decided to compile with gcc, don't forget to specify compilers (replace "7" with version of gcc installed on your machine)
sh ./build-python.sh install

Note: sudo (or administrator rights in Windows) may be needed to perform the command.

Run sh ./build-python.sh install --nomp to disable OpenMP support. All requirements from Build Threadless Version section apply for this installation option as well.

Run sh ./build-python.sh install --mpi to enable MPI support. All requirements from Build MPI Version section apply for this installation option as well.

Run sh ./build-python.sh install --mingw, if you want to use MinGW-w64 on Windows instead of Visual Studio. All requirements from Build with MinGW-w64 on Windows section apply for this installation option as well.

Run sh ./build-python.sh install --gpu to enable GPU support. All requirements from Build GPU Version section apply for this installation option as well. To pass additional options to CMake use the following syntax: sh ./build-python.sh install --gpu --opencl-include-dir="/usr/local/cuda/include/", see Build GPU Version section for the complete list of them.

Run sh ./build-python.sh install --cuda to enable CUDA support. All requirements from Build CUDA Version section apply for this installation option as well.

Run sh ./build-python.sh install --hdfs to enable HDFS support. All requirements from Build HDFS Version section apply for this installation option as well.

Run sh ./build-python.sh install --bit32, if you want to use 32-bit version. All requirements from Build 32-bit Version with 32-bit Python section apply for this installation option as well.

Run sh ./build-python.sh install --time-costs, if you want to output time costs for different internal routines. All requirements from Build with Time Costs Output section apply for this installation option as well.

If you get any errors during installation or due to any other reasons, you may want to build dynamic library from sources by any method you prefer (see Installation Guide) and then just run sh ./build-python.sh install --precompile.

sh ./build-python.sh bdist_wheel --no-isolation

MSBuild.exe windows/LightGBM.sln /p:Configuration=DLL /p:Platform=x64 /p:PlatformToolset=v143

sh ./build-python.sh install --precompile