Source: lightgbm
Section: admin
Priority: optional
Maintainer: Adam Cecile <acecile@le-vert.net>
Build-Depends: debhelper (>= 9), lsb-release, cmake, dh-python, python, python3, python-setuptools, python3-setuptools, r-base-dev (>= 3.0),
# https://github.com/Microsoft/LightGBM/wiki/Installation-Guide#build-mpi-version
 libopenmpi-dev,
# https://github.com/Microsoft/LightGBM/wiki/Installation-Guide#with-gpu-support
 ocl-icd-opencl-dev,
 libboost-dev (>= 1.56), libboost-system-dev (>= 1.56), libboost-filesystem-dev (>= 1.56),
# Additional R dependencies @@@@R_DEPS_TOKEN@@@@ See: R-package/DESCRIPTION 
 r-cran-r6 (>= 2.0), r-cran-matrix (>= 1.1-0), r-cran-data.table (>= 1.9.6), r-cran-magrittr (>= 1.5), r-cran-jsonlite (>= 1.0)
Standards-Version: 3.9.8
Homepage: https://github.com/Microsoft/LightGBM
X-Python-Version: >= 2.7
X-Python3-Version: >= 3.4

Package: lightgbm
Architecture: any
Depends: ${shlibs:Depends}, ${misc:Depends}, liblightgbm (= ${binary:Version})
Description: High performance gradient boosting framework (command line)
 LightGBM is a gradient boosting framework that uses tree based learning
 algorithms.
 .
 It is designed to be distributed and efficient with the following
 advantages:
 .
  * Faster training speed and higher efficiency
  * Lower memory usage
  * Better accuracy
  * Parallel and GPU learning supported
  * Capable of handling large-scale data
 .
 This package contains command line tool.

Package: liblightgbm
Section: libs
Architecture: any
Depends: ${shlibs:Depends}, ${misc:Depends}
Description: High performance gradient boosting framework (library)
 LightGBM is a gradient boosting framework that uses tree based learning
 algorithms.
 .
 It is designed to be distributed and efficient with the following
 advantages:
 .
  * Faster training speed and higher efficiency
  * Lower memory usage
  * Better accuracy
  * Parallel and GPU learning supported
  * Capable of handling large-scale data
 .
 This package contains the shared library.

Package: lightgbm-dev
Section: devel
Architecture: all
Depends: ${shlibs:Depends}, ${misc:Depends}, liblightgbm (>= ${source:Version}), liblightgbm (<< ${source:Version}.1~)
Description: High performance gradient boosting framework (development)
 LightGBM is a gradient boosting framework that uses tree based learning
 algorithms.
 .
 It is designed to be distributed and efficient with the following
 advantages:
 .
  * Faster training speed and higher efficiency
  * Lower memory usage
  * Better accuracy
  * Parallel and GPU learning supported
  * Capable of handling large-scale data
 .
 This package contains the shared library development headers.

Package: python-lightgbm
Section: python
Architecture: all
Depends: ${misc:Depends}, ${python:Depends}, liblightgbm (>= ${source:Version}), liblightgbm (<< ${source:Version}.1~)
Description: High performance gradient boosting framework (Python2)
 LightGBM is a gradient boosting framework that uses tree based learning
 algorithms.
 .
 It is designed to be distributed and efficient with the following
 advantages:
 .
  * Faster training speed and higher efficiency
  * Lower memory usage
  * Better accuracy
  * Parallel and GPU learning supported
  * Capable of handling large-scale data
 .
 This package contains Python2 module.

Package: python3-lightgbm
Section: python
Architecture: all
Depends: ${misc:Depends}, ${python3:Depends}, liblightgbm (>= ${source:Version}), liblightgbm (<< ${source:Version}.1~)
Description: High performance gradient boosting framework (Python3)
 LightGBM is a gradient boosting framework that uses tree based learning
 algorithms.
 .
 It is designed to be distributed and efficient with the following
 advantages:
 .
  * Faster training speed and higher efficiency
  * Lower memory usage
  * Better accuracy
  * Parallel and GPU learning supported
  * Capable of handling large-scale data
 .
 This package contains Python3 module.

Package: r-lightgbm
Section: gnu-r
Architecture: any
Depends: ${shlibs:Depends}, ${misc:Depends}, ${R:Depends}
Description: High performance gradient boosting framework (R module)
 LightGBM is a gradient boosting framework that uses tree based learning
 algorithms.
 .
 It is designed to be distributed and efficient with the following
 advantages:
 .
  * Faster training speed and higher efficiency
  * Lower memory usage
  * Better accuracy
  * Parallel and GPU learning supported
  * Capable of handling large-scale data
 .
 This package contains GNU R module.
