def __init__(self,
registry=None,
nlp_engine=None,
app_tracer=None,
enable_trace_pii=False,
default_score_threshold=None,
use_recognizer_store=False,
default_language="en"):
"""
AnalyzerEngine class: Orchestrating the detection of PII entities
and all related logic
:param registry: instance of type RecognizerRegistry
:param nlp_engine: instance of type NlpEngine
(for example SpacyNlpEngine)
:param app_tracer: instance of type AppTracer,
used to trace the logic used during each request
:param enable_trace_pii: bool,
defines whether PII values should be traced or not.
:param default_score_threshold: Minimum confidence value
for detected entities to be returned
:param use_recognizer_store Whether to call the
Presidio Recognizer Store on every request to gather
responses from custom recognizers as well
(only applicable for the full Presidio service)
"""
if not nlp_engine:
logger.info("nlp_engine not provided. Creating new "
"SpacyNlpEngine instance")
nlp_engine = NLP_ENGINES["spacy"]()
if not registry:
logger.info("Recognizer registry not provided. "
"Creating default RecognizerRegistry instance")
if use_recognizer_store:
recognizer_store_api = RecognizerStoreApi()
else:
recognizer_store_api = None
registry = RecognizerRegistry(
recognizer_store_api=recognizer_store_api)
if not app_tracer:
app_tracer = AppTracer()
# load nlp module
self.nlp_engine = nlp_engine
# prepare registry
self.registry = registry
# load all recognizers
if not registry.recognizers:
registry.load_predefined_recognizers()
self.app_tracer = app_tracer
self.enable_trace_pii = enable_trace_pii
self.default_score_threshold = default_score_threshold \
if default_score_threshold \
else 0.0
self.default_language = default_language
def __init__(self,
registry=None,
nlp_engine=None,
app_tracer=None,
enable_trace_pii=False,
default_score_threshold=None):
"""
AnalyzerEngine class: Orchestrating the detection of PII entities
and all related logic
:param registry: instance of type RecognizerRegistry
:param nlp_engine: instance of type NlpEngine
(for example SpacyNlpEngine)
:param app_tracer: instance of type AppTracer,
used to trace the logic used during each request
:param enable_trace_pii: bool,
defines whether PII values should be traced or not.
:param default_score_threshold: Minimum confidence value
for detected entities to be returned
"""
if not nlp_engine:
logger.info("nlp_engine not provided. Creating new "
"SpacyNlpEngine instance")
from presidio_analyzer.nlp_engine import SpacyNlpEngine
nlp_engine = SpacyNlpEngine()
if not registry:
logger.info("Recognizer registry not provided. "
"Creating default RecognizerRegistry instance")
from presidio_analyzer import RecognizerRegistry
registry = RecognizerRegistry()
if not app_tracer:
app_tracer = AppTracer()
# load nlp module
self.nlp_engine = nlp_engine
# prepare registry
self.registry = registry
# load all recognizers
if not registry.recognizers:
registry.load_predefined_recognizers()
self.app_tracer = app_tracer
self.enable_trace_pii = enable_trace_pii
if default_score_threshold is None:
self.default_score_threshold = 0
else:
self.default_score_threshold = default_score_threshold
def test_when_add_recognizer_then_also_outputs_others(nlp_engine):
pattern = Pattern("rocket pattern", r"\W*(rocket)\W*", 0.8)
pattern_recognizer = PatternRecognizer(
"ROCKET",
name="Rocket recognizer",
patterns=[pattern],
supported_language="en",
)
registry = RecognizerRegistry()
registry.add_recognizer(pattern_recognizer)
registry.load_predefined_recognizers()
assert len(registry.recognizers) > 1
analyzer = AnalyzerEngine(registry=registry, nlp_engine=nlp_engine)
text = "Michael Jones has a rocket"
results = analyzer.analyze(text=text, language="en")
assert len(results) == 2
def __init__(
self,
registry: RecognizerRegistry = None,
nlp_engine: NlpEngine = None,
app_tracer: AppTracer = None,
log_decision_process: bool = False,
default_score_threshold: float = 0,
supported_languages: List[str] = None,
):
if not supported_languages:
supported_languages = ["en"]
if not nlp_engine:
logger.info("nlp_engine not provided, creating default.")
provider = NlpEngineProvider()
nlp_engine = provider.create_engine()
if not registry:
logger.info("registry not provided, creating default.")
registry = RecognizerRegistry()
if not app_tracer:
app_tracer = AppTracer()
self.app_tracer = app_tracer
self.supported_languages = supported_languages
self.nlp_engine = nlp_engine
self.registry = registry
# load all recognizers
if not registry.recognizers:
registry.load_predefined_recognizers(
nlp_engine=self.nlp_engine, languages=self.supported_languages
)
self.log_decision_process = log_decision_process
self.default_score_threshold = default_score_threshold