{% set name = "deepac" %}
{% set version = "0.12.0" %}

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

source:
  url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name }}-{{ version }}.tar.gz
  sha256: 1a6df71867c33e4d52d1ca585f023d097c340ffe3ddeea3c64979e4719ca5b1b

build:
  noarch: python
  number: 0
  entry_points:
    - deepac=deepac.command_line:main
  script: "{{ PYTHON }} -m pip install . --no-deps --ignore-installed -vvv "

requirements:
  host:
    - python >=3
    - pip
  run:
    - biopython >=1.76
    - h5py >=2.10
    - matplotlib-base >=3.1.3
    - numpy >=1.18
    - python >=3.6
    - scikit-learn >=0.22
    - tensorflow >=2.1
    - psutil >=5.6.7
    - pandas >=1.0
    - shap >=0.35
    - weblogo >=3.7
    - bedtools >=2.29
    - pybedtools >=0.8.1
    - statsmodels >=0.11

test:
  imports:
    - deepac
    - deepac.eval
    - deepac.tests
    - deepac.explain
    - deepac.gwpa
  commands:
    - deepac --help

about:
  home: https://gitlab.com/rki_bioinformatics/DeePaC
  license: MIT
  license_family: MIT
  license_file: LICENSE
  summary: Predicting pathogenic potentials of novel DNA with reverse-complement neural networks.
  doc_url: https://rki_bioinformatics.gitlab.io/DeePaC/
  dev_url: https://gitlab.com/rki_bioinformatics/DeePaC

extra:
  recipe-maintainers:
    - JakubBartoszewicz
