<commit_before>{% set name = "BlackBoxAuditing" %}
{% set version = "0.1.54" %}

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

source:
  url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name }}-{{ version }}.tar.gz
  sha256: 02824682f4ac3a89e606d3dc7e99481d09e82655513511e9406268f8b17be3d6

build:
  number: 0
  script: "{{ PYTHON }} -m pip install . -vv"

requirements:
  host:
    - python
    - pip

  run:
    - python
    - numpy
    - pandas
    - matplotlib
    - networkx

test:
  imports:
    - BlackBoxAuditing

about:
  home: http://github.com/algofairness/BlackBoxAuditing
  license: Apache 2.0
  license_family: Apache
  license_file: LICENSE.txt
  summary: 'Research code for auditing and exploring black box machine-learning models'

  description: |
    This repository contains a sample implementation of Gradient Feature Auditing (GFA) meant to be generalizable to most datasets. For more information on the repair process, see our paper on Certifying and Removing Disparate Impact. For information on the full auditing process, see our paper on Auditing Black-box Models for Indirect Influence.
  doc_url: https://github.com/algofairness/BlackBoxAuditing
  dev_url: https://github.com/algofairness/BlackBoxAuditing

extra:
  recipe-maintainers:
    - pavelgrib<commit_msg>add sklearn dep<commit_after>{% set name = "BlackBoxAuditing" %}
{% set version = "0.1.54" %}

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

source:
  url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name }}-{{ version }}.tar.gz
  sha256: 02824682f4ac3a89e606d3dc7e99481d09e82655513511e9406268f8b17be3d6

build:
  number: 0
  script: "{{ PYTHON }} -m pip install . -vv"

requirements:
  host:
    - python
    - pip

  run:
    - python
    - numpy
    - pandas
    - matplotlib
    - networkx
    - scikit-learn

test:
  imports:
    - BlackBoxAuditing

about:
  home: http://github.com/algofairness/BlackBoxAuditing
  license: Apache 2.0
  license_family: Apache
  license_file: LICENSE.txt
  summary: 'Research code for auditing and exploring black box machine-learning models'

  description: |
    This repository contains a sample implementation of Gradient Feature Auditing (GFA) meant to be generalizable to most datasets. For more information on the repair process, see our paper on Certifying and Removing Disparate Impact. For information on the full auditing process, see our paper on Auditing Black-box Models for Indirect Influence.
  doc_url: https://github.com/algofairness/BlackBoxAuditing
  dev_url: https://github.com/algofairness/BlackBoxAuditing

extra:
  recipe-maintainers:
    - pavelgrib
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