"nlp_engine_name": "spacy",
    "models": [
        {"lang_code": "en", "model_name": "en_core_web_lg"},
        # {"lang_code": "de", "model_name": "de_core_news_md"},
        # {"lang_code": "es", "model_name": "es_core_news_md"},
        # ...
        # List of available models: https://spacy.io/usage/models
    ],
}
[docs]class PresidioAnonymizerBase(AnonymizerBase):
[docs]    def __init__(
        self,
        analyzed_fields: Optional[List[str]] = None,
        operators: Optional[Dict[str, OperatorConfig]] = None,
        languages_config: Dict = DEFAULT_LANGUAGES_CONFIG,
        add_default_faker_operators: bool = True,
        faker_seed: Optional[int] = None,
    ):
        """
        Args:
            analyzed_fields: List of fields to detect and then anonymize.
                Defaults to all entities supported by Microsoft Presidio.
            operators: Operators to use for anonymization.
                Operators allow for custom anonymization of detected PII.
                Learn more:
                https://microsoft.github.io/presidio/tutorial/10_simple_anonymization/
            languages_config: Configuration for the NLP engine.
                First language in the list will be used as the main language
                in self.anonymize(...) when no language is specified.
                Learn more:
                https://microsoft.github.io/presidio/analyzer/customizing_nlp_models/
            faker_seed: Seed used to initialize faker.
                Defaults to None, in which case faker will be seeded randomly
                and provide random values.
        """
        OperatorConfig = _import_operator_config()