Source: xgboost
Section: science
Homepage: https://xgboost.ai/
Priority: optional
Standards-Version: 4.7.0
Vcs-Git: https://salsa.debian.org/deeplearning-team/xgboost.git
Vcs-Browser: https://salsa.debian.org/deeplearning-team/xgboost
Maintainer: Debian Deep Learning Team <debian-ai@lists.debian.org>
Uploaders: Mo Zhou <lumin@debian.org>
Rules-Requires-Root: no
Build-Depends: cmake,
               debhelper-compat (= 13),
               dh-python,
               libdmlc-dev (>= 0.5+git20240614.1334185~),
               ninja-build,
               pybuild-plugin-pyproject,
               python3-all,
               python3-hatchling,
               python3-setuptools
#               nvidia-cuda-toolkit,
#               nvidia-cuda-toolkit-gcc,
#               libnccl-dev,
#               libcub-dev,

Package: libxgboost-dev
Section: libdevel
Architecture: any
Depends: libxgboost0 (= ${binary:Version}), ${misc:Depends}
Description: Scalable and Flexible Gradient Boosting (Development)
 XGBoost is an optimized distributed gradient boosting library designed to be
 highly efficient, flexible and portable. It implements machine learning
 algorithms under the Gradient Boosting framework. XGBoost provides a parallel
 tree boosting (also known as GBDT, GBM) that solve many data science problems
 in a fast and accurate way. The same code runs on major distributed environment
 (Kubernetes, Hadoop, SGE, MPI, Dask) and can solve problems beyond billions of
 examples.
 .
 This package contains the xgboost development files.

Package: libxgboost0
Section: libs
Architecture: any
Depends: ${misc:Depends}, ${shlibs:Depends}
Description: Scalable and Flexible Gradient Boosting (Shared lib)
 XGBoost is an optimized distributed gradient boosting library designed to be
 highly efficient, flexible and portable. It implements machine learning
 algorithms under the Gradient Boosting framework. XGBoost provides a parallel
 tree boosting (also known as GBDT, GBM) that solve many data science problems
 in a fast and accurate way. The same code runs on major distributed environment
 (Kubernetes, Hadoop, SGE, MPI, Dask) and can solve problems beyond billions of
 examples.
 .
 This package contains the xgboost shared object.

Package: python3-xgboost
Section: python
Architecture: any
Depends: libxgboost0 (= ${binary:Version}), ${misc:Depends}, ${python3:Depends}
Suggests: python3-sklearn
Description: Scalable and Flexible Gradient Boosting (Python3)
 XGBoost is an optimized distributed gradient boosting library designed to be
 highly efficient, flexible and portable. It implements machine learning
 algorithms under the Gradient Boosting framework. XGBoost provides a parallel
 tree boosting (also known as GBDT, GBM) that solve many data science problems
 in a fast and accurate way. The same code runs on major distributed environment
 (Kubernetes, Hadoop, SGE, MPI, Dask) and can solve problems beyond billions of
 examples.
 .
 This package contains the xgboost python3 binding.