def test_inspector_adult_easy_str_pipeline():
"""
Tests whether the str version of the inspector works
"""
with open(ADULT_SIMPLE_PY) as file:
code = file.read()
inspector_result = PipelineInspector\
.on_pipeline_from_string(code)\
.add_required_inspection(MaterializeFirstOutputRows(5)) \
.add_check(NoBiasIntroducedFor(['race'])) \
.add_check(NoIllegalFeatures()) \
.execute()
extracted_dag = inspector_result.dag
expected_dag = get_expected_dag_adult_easy("<string-source>")
compare(networkx.to_dict_of_dicts(extracted_dag),
networkx.to_dict_of_dicts(expected_dag))
assert HistogramForColumns(['race']) in list(
inspector_result.dag_node_to_inspection_results.values())[0]
check_to_check_results = inspector_result.check_to_check_results
assert check_to_check_results[NoBiasIntroducedFor(
['race'])].status == CheckStatus.SUCCESS
assert check_to_check_results[
NoIllegalFeatures()].status == CheckStatus.FAILURE
def test_no_illegal_features():
"""
Tests whether NoIllegalFeatures works for joins
"""
test_code = cleandoc("""
import pandas as pd
from sklearn.preprocessing import label_binarize, StandardScaler, OneHotEncoder
from sklearn.compose import ColumnTransformer
from sklearn.pipeline import Pipeline
from sklearn.tree import DecisionTreeClassifier
data = pd.DataFrame({'age': [1, 2, 10, 5], 'B': ['cat_a', 'cat_b', 'cat_a', 'cat_c'],
'C': ['cat_a', 'cat_b', 'cat_a', 'cat_c'], 'target': ['no', 'no', 'yes', 'yes']})
column_transformer = ColumnTransformer(transformers=[
('numeric', StandardScaler(), ['age']),
('categorical', OneHotEncoder(sparse=False), ['B', 'C'])
])
income_pipeline = Pipeline([
('features', column_transformer),
('classifier', DecisionTreeClassifier())])
labels = label_binarize(data['target'], classes=['no', 'yes'])
income_pipeline.fit(data, labels)
""")
inspector_result = PipelineInspector \
.on_pipeline_from_string(test_code) \
.add_check(NoIllegalFeatures(['C'])) \
.execute()
check_result = inspector_result.check_to_check_results[NoIllegalFeatures(
['C'])]
# pylint: disable=anomalous-backslash-in-string
expected_result = NoIllegalFeaturesResult(
NoIllegalFeatures(['C']), CheckStatus.FAILURE,
StringComparison("Used illegal columns\: .*"),
SequenceComparison('C', 'age', ordered=False))
compare(check_result, expected_result)
def test_inspector_adult_easy_ipynb_pipeline():
"""
Tests whether the .ipynb version of the inspector works
"""
inspector_result = PipelineInspector\
.on_pipeline_from_ipynb_file(ADULT_SIMPLE_IPYNB)\
.add_required_inspection(MaterializeFirstOutputRows(5)) \
.add_check(NoBiasIntroducedFor(['race'])) \
.add_check(NoIllegalFeatures()) \
.execute()
extracted_dag = inspector_result.dag
expected_dag = get_expected_dag_adult_easy_ipynb()
compare(networkx.to_dict_of_dicts(extracted_dag),
networkx.to_dict_of_dicts(expected_dag))
assert HistogramForColumns(
['race']) in inspector_result.inspection_to_annotations
check_to_check_results = inspector_result.check_to_check_results
assert check_to_check_results[NoBiasIntroducedFor(
['race'])].status == CheckStatus.SUCCESS
assert check_to_check_results[
NoIllegalFeatures()].status == CheckStatus.FAILURE