{% set name = "ppanini" %}
{% set version = "0.6.4" %}

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

source:
  fn: {{ name|lower }}_{{ version }}.tar.gz
  url: https://pypi.python.org/packages/10/56/61250c8e6ba48f76c1270a337f9985808e41aa13c377fd76b818abc6b488/ppanini-0.6.4.tar.gz
  md5: 8768da1bd4546fc78bf29c84e26491de

build:
  skip: True # [not py27]
  entry_points:
    - ppanini = ppanini.ppanini:_main
    - ppanini_abundance_table = ppanini.utils.preppanini:main
    - ppanini_eval_roc = ppanini.utils.plot_roc:main
    - ppanini_test = ppanini.tests.ppanini_test:main

requirements:
  build:
    - python
    - setuptools
    - numpy >=1.9.2
    - scikit-learn  >=0.14.1
    - matplotlib >=1.1.1
    - biopython >=1.66

  run:
    - python
    - numpy >=1.9.2
    - scikit-learn  >=0.14.1
    - matplotlib >=1.1.1
    - biopython >=1.66

test:
  # Python imports
  imports:
    - ppanini
    - ppanini.tests
    - ppanini.tests.data
    - ppanini.utils

  commands:
    - ppanini --help
    - ppanini_abundance_table --help

about:
  home: http://huttenhower.sph.harvard.edu/ppanini
  license: MIT
  summary: 'PPANINI: Prioritization and Prediction of functional Annotations for Novel and Important genes via automated data Network Integration.'
