package:
  name: scikit-learn
  version: 1.1.0

source:
  url: https://files.pythonhosted.org/packages/8b/99/b1ec652f2d60a13871a3053f312f9d78977be57e420f2a49d52ba503f1f4/scikit-learn-1.1.0.tar.gz
  sha256: 80f9904f5b1356adfc32406725dd94c8cc9c8d265047d98390033a6c238cbb29

  patches:
    - patches/0001-Cythonize-_cython_blas.pyx-with-include-path-pointin.patch
    - patches/0002-Disable-omp.patch

build:
  cflags: -Wno-implicit-function-declaration

requirements:
  run:
    - scipy
    - joblib
    - threadpoolctl

test:
  imports:
    - sklearn
    - sklearn.calibration
    - sklearn.cluster
    - sklearn.compose
    - sklearn.covariance
    - sklearn.cross_decomposition
    - sklearn.datasets
    - sklearn.decomposition
    - sklearn.discriminant_analysis
    - sklearn.dummy
    - sklearn.ensemble
    - sklearn.exceptions
    - sklearn.externals
    - sklearn.feature_extraction
    - sklearn.feature_selection
    - sklearn.gaussian_process
    - sklearn.impute
    - sklearn.isotonic
    - sklearn.kernel_approximation
    - sklearn.kernel_ridge
    - sklearn.linear_model
    - sklearn.manifold
    - sklearn.metrics
    - sklearn.mixture
    - sklearn.model_selection
    - sklearn.multiclass
    - sklearn.multioutput
    - sklearn.naive_bayes
    - sklearn.neighbors
    - sklearn.neural_network
    - sklearn.pipeline
    - sklearn.preprocessing
    - sklearn.random_projection
    - sklearn.semi_supervised
    - sklearn.svm
    - sklearn.tree
    - sklearn.utils