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a7e2f33adc
* Add PII Tag and Sensitivity Level enums. * Add feature-extraction for PII classification tasks * Add faker as test dependency * Add unit tests for presidio tag extractor * Add PIISensitivityTags enum and update sensitivity mapping logic * Add Presidio utility functions for PII analysis * Extend column name regexs for PII * Add colum name split * Move pii algorithms to dedicated package * Add tests for PAN, NIF, SSN entities * Fix linting * Add comment on why we need to set specific lanaguage to Presidio recognizers, as per PR suggestion. * Fix version of faker to prevent flaky tests. Fix failing tests. * Fix wrong import --------- Co-authored-by: Pere Menal <pere.menal@getcollate.io>
55 lines
2.2 KiB
Python
55 lines
2.2 KiB
Python
# Copyright 2025 Collate
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# Licensed under the Collate Community License, Version 1.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# https://github.com/open-metadata/OpenMetadata/blob/main/ingestion/LICENSE
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import inspect
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from typing import Iterable, Tuple
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from metadata.pii.algorithms.classifiers import ColumnClassifier, HeuristicPIIClassifier
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from metadata.pii.algorithms.tags import PIITag
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from .data import pii_samples
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from .data.pii_samples import LabeledData
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def get_sample_data() -> Iterable[Tuple[str, LabeledData]]:
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# Add the samples you want to test
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# get all attributes of the module that ends with _data
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suffix = "_data"
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for name, obj in inspect.getmembers(pii_samples):
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if name.endswith(suffix):
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yield name, obj
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def run_test_on_pii_classifier(pii_classifier: ColumnClassifier[PIITag]) -> str:
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"""Apply the classifier to the data and check the results"""
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tested_datasets = 0
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for name, column_data in get_sample_data():
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predicted_scores = pii_classifier.predict_scores(
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sample_data=column_data["sample_data"],
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column_name=column_data["column_name"],
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column_data_type=column_data["column_data_type"],
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)
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predicted_classes = set(predicted_scores)
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expected_classes = set(column_data["pii_tags"])
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assert (
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predicted_classes == expected_classes
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), f"Failed on dataset {name}: {expected_classes} but got {predicted_classes} with scores {predicted_scores}"
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tested_datasets += 1
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return f"PII Classifier {pii_classifier.__class__.__name__} tested with {tested_datasets} datasets."
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def test_pii_heuristic_classifier(pii_test_logger):
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"""Test the PII heuristic classifier"""
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heuristic_classifier = HeuristicPIIClassifier()
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results = run_test_on_pii_classifier(heuristic_classifier)
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pii_test_logger.info(results)
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