<commit_before>{% set name = "champ" %}
{% set version = "2.0.2" %}
{% set sha256 = "2e24d8fea58bf65bb13ec646cbb7404c4fc780ca4c07d5eb03c9aca9cb1609bb" %}

package:
  name: {{ name }}
  version: {{ version }}

source:
  url: https://files.pythonhosted.org/packages/ce/25/b7cba31f1781a7ddbcafb8ff8e96357ffa98d41704ccf7e19bcfe928649a/champ-{{ version }}.tar.gz
  sha256: {{ sha256 }}

build:
  script: python setup.py install --single-version-externally-managed --record record.txt
  number: 0
  skip: True  # [win]


requirements:
  build:
    - pkg-config
    - {{ compiler('c') }}
    - {{ compiler('cxx') }}

  host:
    - python
    - igraph
    - setuptools

  run:
    - python-igraph
    - matplotlib
    - numpy >=1.13
    - scipy >=0.19
    - pandas
    - h5py
    - seaborn
    - tqdm
    - louvain
    - scikit-learn
    - future


test:
  imports:
    - igraph
    - louvain
    - champ


about:
  home: https://github.com/wweir827/CHAMP
  license: MIT
  summary: 'A modularity based tool for screening a set of partitions.'
  description: |
    Modularity based community detection for networks and filtering
    based presence of domain of optimality within the resolution space.
  doc_url: https://champ.readthedocs.io/en/latest

extra:
  recipe-maintainers: 
    - wweir827<commit_msg>remove test import champ<commit_after>{% set name = "champ" %}
{% set version = "2.0.2" %}
{% set sha256 = "2e24d8fea58bf65bb13ec646cbb7404c4fc780ca4c07d5eb03c9aca9cb1609bb" %}

package:
  name: {{ name }}
  version: {{ version }}

source:
  url: https://files.pythonhosted.org/packages/ce/25/b7cba31f1781a7ddbcafb8ff8e96357ffa98d41704ccf7e19bcfe928649a/champ-{{ version }}.tar.gz
  sha256: {{ sha256 }}

build:
  script: python setup.py install --single-version-externally-managed --record record.txt
  number: 0
  skip: True  # [win]


requirements:
  build:
    - pkg-config
    - {{ compiler('c') }}
    - {{ compiler('cxx') }}

  host:
    - python
    - igraph
    - setuptools

  run:
    - python-igraph
    - matplotlib
    - numpy >=1.13
    - scipy >=0.19
    - pandas
    - h5py
    - seaborn
    - tqdm
    - louvain
    - scikit-learn
    - future


test:
  imports:
    - igraph
    - louvain

about:
  home: https://github.com/wweir827/CHAMP
  license: MIT
  summary: 'A modularity based tool for screening a set of partitions.'
  description: |
    Modularity based community detection for networks and filtering
    based presence of domain of optimality within the resolution space.
  doc_url: https://champ.readthedocs.io/en/latest

extra:
  recipe-maintainers: 
    - wweir827
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