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* 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>
43 lines
1.5 KiB
Python
43 lines
1.5 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 pytest
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from metadata.pii.algorithms.preprocessing import convert_to_str, preprocess_values
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@pytest.mark.parametrize(
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"input_value,expected",
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[
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("hello", "hello"),
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(123, "123"),
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(123.45, "123.45"),
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(b"hello", "hello"),
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(None, None),
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({"key": "value"}, '{"key": "value"}'),
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({1, 2, 3}, None), # Sets cannot be converted to JSON
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],
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)
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def test_converts_various_types_to_string(input_value, expected):
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assert convert_to_str(input_value) == expected
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@pytest.mark.parametrize(
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"input_values,expected",
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[
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(["hello", 123, None, b"world", "", " "], ["hello", "123", "world"]),
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([], []),
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([None, "", " "], []),
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([{"key": "value"}, [1, 2, 3]], ['{"key": "value"}', "[1, 2, 3]"]),
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],
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)
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def test_preprocesses_sequences_correctly(input_values, expected):
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assert preprocess_values(input_values) == expected
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