meta.yaml

{% set name = "shogun" %}

{% set version = "6.1.3" %}
{% set commit = 'shogun_' + version %}
{% set sha256 = "75f4d555efe06eaa7c4c12a1dc942f6e4d41a8ed495777a790b9bd9df936c19c" %}

# Shogun doesn't produce a single tarball you can build from anymore;
# need to get the gpl-shogun tarball too. Remember to update this when updating
# the version!
{% set gpl_commit = "29ca2ff930cd5d963b3a78e79160cc04d48970c2" %}
{% set gpl_sha256 = "ff8a46b7775e784f07e9ffb02e7cd9b101f508c1c7b7d8cdbf1024a2efacdb22" %}

{% set blas_variant = "openblas" %}

package:
  name: {{ name|lower }}
  version: {{ version }}

source:
  - url: https://github.com/shogun-toolbox/shogun/archive/{{ commit }}.tar.gz
    sha256: {{ sha256 }}
    patches:
      # https://github.com/shogun-toolbox/shogun/issues/4068
      - libpython-linking.patch
  - url: https://github.com/shogun-toolbox/shogun-gpl/archive/{{ gpl_commit }}.tar.gz
    sha256: {{ gpl_sha256 }}
    folder: src/gpl

{% set lc, vs, ve, prefix, parbuild = "\\", "$", "", "$PREFIX", "-j $CPU_COUNT" %}  # [unix]
{% set lc, vs, ve, prefix, parbuild = "^", "%", "%", "%LIBRARY_PREFIX%", "" %}      # [win]
build:
  number: 3
  features:
    - blas_{{ blas_variant }}  # [not win]
  skip: true  # [win32 or (win and vc<14)]
  script: |
    mkdir build
    cd build

    # figure out include / library paths
    # https://github.com/conda/conda-build/issues/2130 will be proper solution
    pyinc=$($PYTHON -c "from distutils import sysconfig; print(sysconfig.get_python_inc())")                           # [unix]
    pylib=$(otool -L $PYTHON | grep 'libpython.*\.dylib' | tr '\t' ' ' | cut -d' ' -f2 | sed "s|@rpath|$PREFIX/lib|")  # [osx]
    pylib=$(ldd $PYTHON | grep $PREFIX | grep 'libpython.*\.so' | cut -d' ' -f3)                                       # [linux]

    cmake ..                                      {{ lc }}
        -G"{{vs}}CMAKE_GENERATOR{{ve}}"           {{ lc }}
        -DCMAKE_PREFIX_PATH="{{ prefix }}"        {{ lc }}
        -DCMAKE_INSTALL_PREFIX="{{ prefix }}"     {{ lc }}
        -DCMAKE_BUILD_TYPE=Release                {{ lc }}
        -DBUILD_EXAMPLES=OFF                      {{ lc }}
        -DBUILD_META_EXAMPLES=OFF                 {{ lc }}
        -DENABLE_TESTING=OFF                      {{ lc }}
        -DENABLE_COVERAGE=OFF                     {{ lc }}
        -DUSE_SVMLIGHT=OFF                        {{ lc }}
        -DPYTHON_EXECUTABLE={{vs}}PYTHON{{ve}}    {{ lc }}
        -DPYTHON_INCLUDE_DIR=$pyinc               \  # [unix]
        -DPYTHON_LIBRARY=$pylib                   \  # [unix]
        -DLIBSHOGUN=OFF                           {{ lc }}
        -DINTERFACE_PYTHON=ON
    if errorlevel 1 exit 1  # [win]

    cmake --build . --target _interface_python --config Release -- {{ parbuild }}
    if errorlevel 1 exit 1  # [win]

    cmake --build . --target install --config Release -- {{ parbuild }}
    if errorlevel 1 exit 1  # [win]


requirements:
  build:
    - {{ compiler('c') }}
    - {{ compiler('cxx') }}
    - cmake
    - swig
  host:
    - python
    - setuptools
    - numpy
    - shogun-cpp {{ version }}
    - arpack       # [not win]
    - bzip2
    - ctags
    - curl
    - eigen
    - glpk
    - hdf5
    - json-c       # [not win]
    - libxml2
    - lzo
    - openblas     # [not win]
    - libprotobuf  # [not win]  # conda-forge doesn't have shared lib yet
    - rxcpp 4.0.0
    - snappy
    - xz
    - zlib
  run:
    - python
    - {{ pin_compatible('numpy') }}
    - {{ pin_compatible('shogun-cpp', max_pin='x.x.x') }}
    - arpack       # [not win]
    - bzip2
    - ctags
    - curl
    - glpk
    - hdf5
    - json-c       # [not win]
    - libxml2
    - lzo
    - openblas     # [not win]
    - libprotobuf  # [not win]
    - snappy
    - xz
    - zlib

test:
  imports:
    - shogun
  commands:
    - conda inspect linkages -p $PREFIX shogun  # [not win]
    - conda inspect objects -p $PREFIX shogun   # [osx]

about:
  home: http://shogun.ml
  license: GPL-3.0
  license_family: GPL
  license_file: COPYING
  summary: 'Unified and efficient Machine Learning'
  description: |
    The Shogun Machine learning toolbox offers a wide range of efficient and
    unified Machine Learning methods.
  doc_url: http://shogun.ml/examples/latest/index.html
  dev_url: https://github.com/shogun-toolbox/shogun/wiki

extra:
  recipe-maintainers:
    - djsutherland