import os from typing import Iterator, List import pytest from . import is_libcublas_available @pytest.fixture(scope="module", autouse=True) def check_spacy_model() -> Iterator[None]: import spacy if not spacy.util.is_package("en_core_web_lg"): pytest.skip(reason="Spacy model 'en_core_web_lg' not installed") yield @pytest.fixture(scope="module", autouse=True) def check_libcublas() -> Iterator[None]: if not is_libcublas_available(): pytest.skip(reason="libcublas.so is not available") yield @pytest.mark.requires("presidio_analyzer", "presidio_anonymizer", "faker") @pytest.mark.parametrize( "analyzed_fields,should_contain", [(["PERSON"], False), (["PHONE_NUMBER"], True), (None, False)], ) def test_anonymize(analyzed_fields: List[str], should_contain: bool) -> None: """Test anonymizing a name in a simple sentence""" from langchain_experimental.data_anonymizer import PresidioReversibleAnonymizer text = "Hello, my name is John Doe." anonymizer = PresidioReversibleAnonymizer(analyzed_fields=analyzed_fields) anonymized_text = anonymizer.anonymize(text) assert ("John Doe" in anonymized_text) == should_contain @pytest.mark.requires("presidio_analyzer", "presidio_anonymizer", "faker") def test_anonymize_multiple() -> None: """Test anonymizing multiple items in a sentence""" from langchain_experimental.data_anonymizer import PresidioReversibleAnonymizer text = "John Smith's phone number is 313-666-7440 and email is johnsmith@gmail.com" anonymizer = PresidioReversibleAnonymizer() anonymized_text = anonymizer.anonymize(text) for phrase in ["John Smith", "313-666-7440", "johnsmith@gmail.com"]: assert phrase not in anonymized_text @pytest.mark.requires("presidio_analyzer", "presidio_anonymizer", "faker") def test_anonymize_with_custom_operator() -> None: """Test anonymize a name with a custom operator""" from presidio_anonymizer.entities import OperatorConfig from langchain_experimental.data_anonymizer import PresidioReversibleAnonymizer custom_operator = {"PERSON": OperatorConfig("replace", {"new_value": ""})} anonymizer = PresidioReversibleAnonymizer(operators=custom_operator) text = "Jane Doe was here." anonymized_text = anonymizer.anonymize(text) assert anonymized_text == " was here." @pytest.mark.requires("presidio_analyzer", "presidio_anonymizer", "faker") def test_add_recognizer_operator() -> None: """ Test add recognizer and anonymize a new type of entity and with a custom operator """ from presidio_analyzer import PatternRecognizer from presidio_anonymizer.entities import OperatorConfig from langchain_experimental.data_anonymizer import PresidioReversibleAnonymizer anonymizer = PresidioReversibleAnonymizer(analyzed_fields=[]) titles_list = ["Sir", "Madam", "Professor"] custom_recognizer = PatternRecognizer( supported_entity="TITLE", deny_list=titles_list ) anonymizer.add_recognizer(custom_recognizer) # anonymizing with custom recognizer text = "Madam Jane Doe was here." anonymized_text = anonymizer.anonymize(text) assert anonymized_text == " Jane Doe was here." # anonymizing with custom recognizer and operator custom_operator = {"TITLE": OperatorConfig("replace", {"new_value": "Dear"})} anonymizer.add_operators(custom_operator) anonymized_text = anonymizer.anonymize(text) assert anonymized_text == "Dear Jane Doe was here." @pytest.mark.requires("presidio_analyzer", "presidio_anonymizer", "faker") def test_deanonymizer_mapping() -> None: """Test if deanonymizer mapping is correctly populated""" from langchain_experimental.data_anonymizer import PresidioReversibleAnonymizer anonymizer = PresidioReversibleAnonymizer( analyzed_fields=["PERSON", "PHONE_NUMBER", "EMAIL_ADDRESS", "CREDIT_CARD"] ) anonymizer.anonymize("Hello, my name is John Doe and my number is 444 555 6666.") # ["PERSON", "PHONE_NUMBER"] assert len(anonymizer.deanonymizer_mapping.keys()) == 2 assert "John Doe" in anonymizer.deanonymizer_mapping.get("PERSON", {}).values() assert ( "444 555 6666" in anonymizer.deanonymizer_mapping.get("PHONE_NUMBER", {}).values() ) text_to_anonymize = ( "And my name is Jane Doe, my email is jane@gmail.com and " "my credit card is 4929 5319 6292 5362." ) anonymizer.anonymize(text_to_anonymize) # ["PERSON", "PHONE_NUMBER", "EMAIL_ADDRESS", "CREDIT_CARD"] assert len(anonymizer.deanonymizer_mapping.keys()) == 4 assert "Jane Doe" in anonymizer.deanonymizer_mapping.get("PERSON", {}).values() assert ( "jane@gmail.com" in anonymizer.deanonymizer_mapping.get("EMAIL_ADDRESS", {}).values() ) assert ( "4929 5319 6292 5362" in anonymizer.deanonymizer_mapping.get("CREDIT_CARD", {}).values() ) @pytest.mark.requires("presidio_analyzer", "presidio_anonymizer", "faker") def test_deanonymize() -> None: """Test deanonymizing a name in a simple sentence""" from langchain_experimental.data_anonymizer import PresidioReversibleAnonymizer text = "Hello, my name is John Doe." anonymizer = PresidioReversibleAnonymizer(analyzed_fields=["PERSON"]) anonymized_text = anonymizer.anonymize(text) deanonymized_text = anonymizer.deanonymize(anonymized_text) assert deanonymized_text == text @pytest.mark.requires("presidio_analyzer", "presidio_anonymizer", "faker") def test_save_load_deanonymizer_mapping() -> None: from langchain_experimental.data_anonymizer import PresidioReversibleAnonymizer anonymizer = PresidioReversibleAnonymizer(analyzed_fields=["PERSON"]) anonymizer.anonymize("Hello, my name is John Doe.") try: anonymizer.save_deanonymizer_mapping("test_file.json") assert os.path.isfile("test_file.json") anonymizer = PresidioReversibleAnonymizer() anonymizer.load_deanonymizer_mapping("test_file.json") assert "John Doe" in anonymizer.deanonymizer_mapping.get("PERSON", {}).values() finally: os.remove("test_file.json")