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Recent changes broke types #1396
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Hi @tonyhammainen, we really do have a duplicate on the |
Hi @omri374, thanks for the reply! The intended pattern is to use both libraries sequentially, first getting recognized PII out of analyzer, and inputting that for the anonymizer to anonymize. Or have I misunderstood? If so, this means that we are inputting Tbh, I don't see why you are not including analyzer as a dependency of anonymizer, given the main usage pattern for anonymizer relies on analyzer? If I have misunderstood how anonymizer package should be used do enlighten me! |
I can confirm the issue with pyright (pylance) by using the first example from the quickstart: https://microsoft.github.io/presidio/getting_started/ If the libraries MUST be independent, then the conversion between the two classes should be done by the user. For example this way: from presidio_analyzer import AnalyzerEngine
from presidio_anonymizer import AnonymizerEngine, RecognizerResult
text = "My phone number is 212-555-5555"
# Set up the engine, loads the NLP module (spaCy model by default)
# and other PII recognizers
analyzer = AnalyzerEngine()
# Call analyzer to get results
results = analyzer.analyze(text=text, entities=["PHONE_NUMBER"], language="en")
print(results)
# Convert recognizer results to RecognizerResult objects from presidio_anonymizer
results = [
RecognizerResult(
entity_type=result.entity_type,
start=result.start,
end=result.end,
score=result.score,
)
for result in results
]
# Analyzer results are passed to the AnonymizerEngine for anonymization
anonymizer = AnonymizerEngine()
anonymized_text = anonymizer.anonymize(text=text, analyzer_results=results)
print(anonymized_text) Over time, the difference between Another approach might be to refactor the anonymizer so that it depends on the protocol of the Additionally, I'd suggest deprecating one of the |
Hi @eicca, thanks for your suggestions. We should also think of backward compatibilty here. In my view, the optimal solution is to have a shared library. One option is to have the anonymizer as a dependency of the analyzer. The second is to create a presidio-core library which is used by both. |
Thanks for your reply @omri374!
This totally makes sense to me, especially since it won't bring a lot of unnecessary dependencies for people who want to use only analyzer (in fact, just
This also makes sense. This can also be done at a later time after the previous step is done. |
Thanks! A PR adding the anonymizer to the analyzer sounds great. |
Describe the bug
As of
2.2.33
I was not getting any type-related errors, but upgrading to the latest2.2.354
resulted in getting them.error: Call to untyped function "AnonymizerEngine" in typed context [no-untyped-call]
^ Initializing the AnonymizerEngine throws an error. I believe it is because the class has no typed init function
error: Argument "ad_hoc_recognizers" to "analyze" of "AnalyzerEngine" has incompatible type "list[PatternRecognizer]"; expected "list[EntityRecognizer] | None" [arg-type]
^ I do not understand why mypy is not picking the fact that
PatternRecognizer
is a child class ofEntityRecognizer
Argument "analyzer_results" to "anonymize" of "AnonymizerEngine" has incompatible type "list[presidio_analyzer.recognizer_result.RecognizerResult]"; expected "list[presidio_anonymizer.entities.engine.recognizer_result.RecognizerResult]" [arg-type]
^ I believe the above is a result of the
RecognizerResult
class inpresidio-anonymizer
being a copy of the class inpresidio-analyzer
, and mypy doesn't understand their equivalencyTo Reproduce
Steps to reproduce the behavior:
AnonymizerEngine()
Expected behavior
No mypy errors when using the library as expected
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