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https://github.com/data-privacy-stack/presidio.git
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40 lines
1.5 KiB
Python
40 lines
1.5 KiB
Python
from presidio_analyzer import AnalyzerEngine
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from presidio_anonymizer import AnonymizerEngine
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from presidio_anonymizer.entities.engine.operator_config import OperatorConfig
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from faker import Faker
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from faker.providers import internet
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def reverse_string(x):
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return x[::-1]
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def anonymize_reverse_lambda(analyzer_results, text_to_anonymize):
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anonymized_results = anonymizer.anonymize(
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text=text_to_anonymize,
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analyzer_results=analyzer_results,
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operators={"EMAIL_ADDRESS": OperatorConfig("custom", {"lambda": lambda x: x[::-1]})}
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)
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return anonymized_results
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def anonymize_faker_lambda(analyzer_results, text_to_anonymize):
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anonymized_results = anonymizer.anonymize(
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text=text_to_anonymize,
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analyzer_results=analyzer_results,
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operators={"EMAIL_ADDRESS": OperatorConfig("custom", {"lambda": lambda x: fake.safe_email()})}
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)
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return anonymized_results
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fake = Faker('en_US')
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fake.add_provider(internet)
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analyzer = AnalyzerEngine()
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anonymizer = AnonymizerEngine()
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text = 'The user has the following two emails: email1@contoso.com and email2@contoso.com'
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analyzer_results = analyzer.analyze(text=text, entities=["EMAIL_ADDRESS"], language='en')
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print("Origina Text: ", text)
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print("Analyzer result:", analyzer_results, '\n')
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print("Reverse lambda result: ",anonymize_reverse_lambda(analyzer_results, text).text, '\n')
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print("Faker lambda result: ",anonymize_faker_lambda(analyzer_results, text).text, '\n') |