158 lines
4.8 KiB
Python
158 lines
4.8 KiB
Python
import numpy as np
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import pytest
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import warnings
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from sklearn.utils.metaestimators import if_delegate_has_method
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from sklearn.utils.metaestimators import available_if
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class Prefix:
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def func(self):
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pass
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class MockMetaEstimator:
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"""This is a mock meta estimator"""
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a_prefix = Prefix()
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@if_delegate_has_method(delegate="a_prefix")
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def func(self):
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"""This is a mock delegated function"""
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pass
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@pytest.mark.filterwarnings("ignore:if_delegate_has_method was deprecated")
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def test_delegated_docstring():
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assert "This is a mock delegated function" in str(
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MockMetaEstimator.__dict__["func"].__doc__
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)
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assert "This is a mock delegated function" in str(MockMetaEstimator.func.__doc__)
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assert "This is a mock delegated function" in str(MockMetaEstimator().func.__doc__)
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class MetaEst:
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"""A mock meta estimator"""
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def __init__(self, sub_est, better_sub_est=None):
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self.sub_est = sub_est
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self.better_sub_est = better_sub_est
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@if_delegate_has_method(delegate="sub_est")
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def predict(self):
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pass
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class MetaEstTestTuple(MetaEst):
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"""A mock meta estimator to test passing a tuple of delegates"""
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@if_delegate_has_method(delegate=("sub_est", "better_sub_est"))
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def predict(self):
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pass
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class MetaEstTestList(MetaEst):
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"""A mock meta estimator to test passing a list of delegates"""
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@if_delegate_has_method(delegate=["sub_est", "better_sub_est"])
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def predict(self):
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pass
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class HasPredict:
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"""A mock sub-estimator with predict method"""
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def predict(self):
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pass
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class HasNoPredict:
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"""A mock sub-estimator with no predict method"""
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pass
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class HasPredictAsNDArray:
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"""A mock sub-estimator where predict is a NumPy array"""
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predict = np.ones((10, 2), dtype=np.int64)
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@pytest.mark.filterwarnings("ignore:if_delegate_has_method was deprecated")
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def test_if_delegate_has_method():
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assert hasattr(MetaEst(HasPredict()), "predict")
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assert not hasattr(MetaEst(HasNoPredict()), "predict")
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assert not hasattr(MetaEstTestTuple(HasNoPredict(), HasNoPredict()), "predict")
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assert hasattr(MetaEstTestTuple(HasPredict(), HasNoPredict()), "predict")
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assert not hasattr(MetaEstTestTuple(HasNoPredict(), HasPredict()), "predict")
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assert not hasattr(MetaEstTestList(HasNoPredict(), HasPredict()), "predict")
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assert hasattr(MetaEstTestList(HasPredict(), HasPredict()), "predict")
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class AvailableParameterEstimator:
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"""This estimator's `available` parameter toggles the presence of a method"""
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def __init__(self, available=True):
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self.available = available
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@available_if(lambda est: est.available)
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def available_func(self):
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"""This is a mock available_if function"""
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pass
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def test_available_if_docstring():
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assert "This is a mock available_if function" in str(
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AvailableParameterEstimator.__dict__["available_func"].__doc__
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)
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assert "This is a mock available_if function" in str(
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AvailableParameterEstimator.available_func.__doc__
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)
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assert "This is a mock available_if function" in str(
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AvailableParameterEstimator().available_func.__doc__
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)
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def test_available_if():
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assert hasattr(AvailableParameterEstimator(), "available_func")
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assert not hasattr(AvailableParameterEstimator(available=False), "available_func")
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def test_available_if_unbound_method():
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# This is a non regression test for:
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# https://github.com/scikit-learn/scikit-learn/issues/20614
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# to make sure that decorated functions can be used as an unbound method,
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# for instance when monkeypatching.
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est = AvailableParameterEstimator()
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AvailableParameterEstimator.available_func(est)
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est = AvailableParameterEstimator(available=False)
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with pytest.raises(
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AttributeError,
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match="This 'AvailableParameterEstimator' has no attribute 'available_func'",
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):
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AvailableParameterEstimator.available_func(est)
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@pytest.mark.filterwarnings("ignore:if_delegate_has_method was deprecated")
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def test_if_delegate_has_method_numpy_array():
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"""Check that we can check for an attribute that is a NumPy array.
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This is a non-regression test for:
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https://github.com/scikit-learn/scikit-learn/issues/21144
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"""
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estimator = MetaEst(HasPredictAsNDArray())
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assert hasattr(estimator, "predict")
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def test_if_delegate_has_method_deprecated():
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"""Check the deprecation warning of if_delegate_has_method"""
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# don't warn when creating the decorator
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with warnings.catch_warnings():
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warnings.simplefilter("error", FutureWarning)
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_ = if_delegate_has_method(delegate="predict")
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# Only when calling it
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with pytest.warns(FutureWarning, match="if_delegate_has_method was deprecated"):
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hasattr(MetaEst(HasPredict()), "predict")
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