pyodide/packages/scikit-learn/meta.yaml

package:
  name: scikit-learn
  version: 0.20.0

source:
  url: https://pypi.io/packages/source/s/scikit-learn/scikit-learn-0.20.0.tar.gz
  sha256: 97d1d971f8ec257011e64b7d655df68081dd3097322690afa1a71a1d755f8c18

  patches:
   - patches/use-site-joblib.patch
   - patches/support-joblib-011.patch

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

requirements:
  run:
    - numpy   # TODO: add scipy once the corresponding PR is merged
    - joblib

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