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meta.yaml
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meta.yaml
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{% set name = "xgboost" %}
{% set version = "1.3.0" %}
package:
name: {{ name|lower }}
version: {{ version }}
source:
# we have to use git urls here to get the submodules needed for the
# build
git_url: https://github.com/dmlc/xgboost
git_tag: 1bf389998383f333490155dba4608bff9ca63b42
patches:
# xgboost patches
- 0001-conda-Unbundle-libxgboost.-dll-dylib-so.patch
- 0002-Fix-R-package-PKGROOT.patch
build:
number: 1
skip: true # [win or linux32 or py2k]
requirements:
build:
- {{ compiler('c') }}
- {{ compiler('cxx') }}
- git
- cmake
- make
- llvm-openmp # [osx]
host:
- llvm-openmp # [osx]
outputs:
- name: libxgboost
script: install-libxgboost.sh
requirements:
build:
- {{ compiler('c') }}
- {{ compiler('cxx') }}
- git
- cmake
- make
- llvm-openmp # [osx]
host:
- llvm-openmp # [osx]
run:
- llvm-openmp # [osx]
- name: _py-xgboost-mutex
version: 2.0
build:
string: cpu_0
- name: py-xgboost
script: install-py-xgboost.sh
requirements:
host:
- {{ pin_subpackage('libxgboost', exact=True) }}
- python
- setuptools
- pip
run:
- {{ pin_subpackage('libxgboost', exact=True) }}
- {{ pin_subpackage('_py-xgboost-mutex', exact=True) }}
- python
- numpy
- scipy
- scikit-learn
test:
script: test-py-xgboost.py
imports:
- xgboost
- name: py-xgboost-cpu
requirements:
host:
- python
run:
- python
- {{ pin_subpackage('py-xgboost', exact=True) }}
- name: xgboost
requirements:
host:
- python
# we install llvm-opnemp here to convince conda to
# install llvm-openmp in the top-level host env above
- llvm-openmp # [osx]
run:
- python
- {{ pin_subpackage('py-xgboost', exact=True) }}
- name: _r-xgboost-mutex
version: 2.0
build:
string: cpu_0
- name: r-xgboost
script: install-r-xgboost.sh
build:
rpaths:
- lib/R/lib
requirements:
build:
- {{ compiler('c') }}
- {{ compiler('cxx') }}
- git
- cmake
- make
- llvm-openmp # [osx]
host:
- {{ pin_subpackage('libxgboost', exact=True) }}
- r-base
- llvm-openmp # [osx]
- r-matrix
- r-data.table
- r-magrittr
- r-stringi
- r-knitr
run:
- {{ pin_subpackage('libxgboost', exact=True) }}
- {{ pin_subpackage('_r-xgboost-mutex', exact=True) }}
- llvm-openmp # [osx]
- r-base
- r-matrix
- r-data.table
- r-magrittr
- r-stringi
test:
files:
- test-r-xgboost.r
commands:
- Rscript test-r-xgboost.r
- name: r-xgboost-cpu
requirements:
host:
- r-base
run:
- r-base
- {{ pin_subpackage('r-xgboost', exact=True) }}
about:
home: https://github.com/dmlc/xgboost
license: Apache-2.0
license_file: LICENSE
summary: |
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for
Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink
and DataFlow
description: |
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 (Hadoop, SGE, MPI) and can solve problems beyond billions of examples.
doc_url: https://xgboost.readthedocs.io/
dev_url: https://github.com/dmlc/xgboost/
extra:
recipe-maintainers:
- aldanor
- jakirkham
- ksangeek