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chore: import upstream snapshot with attribution
2026-07-13 13:35:45 +08:00

57 行
2.5 KiB
Python

# Copyright 2025 Collate
# Licensed under the Collate Community License, Version 1.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# https://github.com/open-metadata/OpenMetadata/blob/main/ingestion/LICENSE
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import inspect
from typing import Iterable, Tuple # noqa: UP035
from metadata.pii.algorithms.classifiers import ColumnClassifier, HeuristicPIIClassifier
from metadata.pii.algorithms.tags import PIITag
from metadata.pii.algorithms.utils import get_top_classes
from .data import pii_samples # noqa: TID252
from .data.pii_samples import LabeledData # noqa: TID252
def get_sample_data() -> Iterable[Tuple[str, LabeledData]]: # noqa: UP006
# Add the samples you want to test
# get all attributes of the module that ends with _data
suffix = "_data"
for name, obj in inspect.getmembers(pii_samples):
if name.endswith(suffix):
yield name, obj
def run_test_on_pii_classifier(pii_classifier: ColumnClassifier[PIITag]) -> str:
"""Apply the classifier to the data and check the results"""
tested_datasets = 0
for name, column_data in get_sample_data():
predicted_scores = pii_classifier.predict_scores(
sample_data=column_data["sample_data"],
column_name=column_data["column_name"],
column_data_type=column_data["column_data_type"],
)
expected_classes = set(column_data["pii_tags"])
selected_classes = get_top_classes(predicted_scores, len(expected_classes), 0.0)
predicted_classes = set(selected_classes)
assert predicted_classes == expected_classes, (
f"Failed on dataset {name}: {expected_classes} but got {predicted_classes} with scores {predicted_scores}"
)
tested_datasets += 1
return f"PII Classifier {pii_classifier.__class__.__name__} tested with {tested_datasets} datasets."
def test_pii_heuristic_classifier(pii_test_logger):
"""Test the PII heuristic classifier"""
heuristic_classifier = HeuristicPIIClassifier()
results = run_test_on_pii_classifier(heuristic_classifier)
pii_test_logger.info(results)