Throughout this tutorial, we’ll walk you through the creation of a basic request to the analyzer and anonymizer components.
See Install Presidio for a tutorial on how to install Presidio.
Analysis could be performed either by using Presidio as a deployed service (Method 1), or using the presidio-analyzer
python package (Method 2).
First, we need to serve our model. We can do that very easily with (Takes about 10 seconds to load)
./presidio-analyzer serve
Now that our model is up and running, we can send PII text to it.
From another shell
./presidio-analyzer analyze --text "John Smith drivers license is AC432223" --fields "PERSON" "US_DRIVER_LICENSE"
The expected result is:
{
"analyzeResults": [
{
"text": "John Smith",
"field": {
"name": "PERSON"
},
"score": 0.8500000238418579,
"location": {
"end": 10,
"length": 10,
"start": 0
}
},
{
"text": "AC432223",
"field": {
"name": "US_DRIVER_LICENSE"
},
"score": 0.6499999761581421,
"location": {
"start": 30,
"end": 38,
"length": 8
}
}
]
}
Use the analyzer Python code by importing analyzer_engine.py
from presidio-analyzer/presidio_analyzer
from presidio_analyzer import AnalyzerEngine
analyzer = AnalyzerEngine()
results = analyzer.analyze(text="My phone number is 212-555-5555",
entities=["PHONE_NUMBER"],
language='en',
all_fields=False)
print(
["Entity: {ent}, score: {score}\n".format(ent=res.entity_type,
score=res.score)
for res in results])