parametrize_with_checks#

sklearn.utils.estimator_checks.parametrize_with_checks(estimators)[source]#

Pytest specific decorator for parametrizing estimator checks.

The id of each check is set to be a pprint version of the estimator and the name of the check with its keyword arguments. This allows to use pytest -k to specify which tests to run:

pytest test_check_estimators.py -k check_estimators_fit_returns_self

Parameters:

estimatorslist of estimators instances: Estimators to generated checks for.

Changed in version 0.24: Passing a class was deprecated in version 0.23, and support for classes was removed in 0.24. Pass an instance instead.

Added in version 0.24.

Returns:

decoratorpytest.mark.parametrize

See also

check_estimator: check if estimator adheres to scikit-learn conventions.

Examples

>>> from sklearn.utils.estimator_checks import parametrize_with_checks
>>> from sklearn.linear_model import LogisticRegression
>>> from sklearn.tree import DecisionTreeRegressor

>>> @parametrize_with_checks([LogisticRegression(),
...                           DecisionTreeRegressor()])
... def test_sklearn_compatible_estimator(estimator, check):
...     check(estimator)

Gallery examples#

Release Highlights for scikit-learn 0.22