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Configuring the Analyzer Engine from file

Presidio uses AnalyzerEngineProvider to load AnalyzerEngine configuration from file. Configuration can be loaded in three different ways:

Using a single file

Create an AnalyzerEngineProvider using a single configuration file and set its path to analyzer_engine_conf_file, then create AnalyzerEngine based on it:

from presidio_analyzer import AnalyzerEngine, AnalyzerEngineProvider

analyzer_conf_file = "./analyzer/analyzer-config-all.yml"

provider = AnalyzerEngineProvider(
    analyzer_engine_conf_file=analyzer_conf_file
    )
analyzer = provider.create_engine()

results = analyzer.analyze(text="My name is Morris", language="en")
print(results)

An example configuration file:

supported_languages: 
- en
default_score_threshold: 0

nlp_configuration:
  nlp_engine_name: spacy
  models:
  -
    lang_code: en
    model_name: en_core_web_lg
  -
    lang_code: es
    model_name: es_core_news_md
  ner_model_configuration:
    model_to_presidio_entity_mapping:
      PER: PERSON
      PERSON: PERSON
      LOC: LOCATION
      LOCATION: LOCATION
      GPE: LOCATION
      ORG: ORGANIZATION
      DATE: DATE_TIME
      TIME: DATE_TIME
      NORP: NRP

    low_confidence_score_multiplier: 0.4
    low_score_entity_names:
    - ORGANIZATION
    - ORG
    default_score: 0.85

recognizer_registry:
  global_regex_flags: 26
  recognizers: 
  - name: CreditCardRecognizer
    supported_languages: 
      - en
    supported_entity: IT_FISCAL_CODE
    type: predefined

  - name: ItFiscalCodeRecognizer
    type: predefined

The configuration file contains the following parameters:

  • supported_languages: A list of supported languages that the analyzer will support.
  • default_score_threshold: A score that determines the minimal threshold for detection.
  • nlp_configuration: Configuration given to the NLP engine which will detect the PIIs and extract features for the downstream logic.
  • recognizer_registry: All the recognizers that will be used by the analyzer.

Note

supported_languages must be identical to the same field in recognizer_registry

Using multiple files

Create an AnalyzerEngineProvider using three different configuration files for each of the following components:

  • Analyzer
  • NLP Engine
  • Recognizer Registry

Note

Each of these parameters is optional and in case it's not set, the default configuration will be used. 

from presidio_analyzer import AnalyzerEngine, AnalyzerEngineProvider

analyzer_conf_file = "./analyzer/analyzer-config.yml"
nlp_engine_conf_file = "./analyzer/nlp-config.yml"
recognizer_registry_conf_file = "./analyzer/recognizers-config.yml"

provider = AnalyzerEngineProvider(
    analyzer_engine_conf_file=analyzer_conf_file,
    nlp_engine_conf_file=nlp_engine_conf_file,
    recognizer_registry_conf_file=recognizer_registry_conf_file,
    )
analyzer = provider.create_engine()

results = analyzer.analyze(text="My name is Morris", language="en")
print(results)

The structure of the configuration files is as follows:

Using the default configuration

Create an AnalyzerEngineProvider without any parameters. This will load the default configuration:

from presidio_analyzer import AnalyzerEngine, AnalyzerEngineProvider

provider = AnalyzerEngineProvider().create_engine()

results = analyzer.analyze(text="My name is Morris", language="en")
print(results)

The default configuration of AnalyzerEngine is defined in the following files: