Metadata-Version: 2.3
Name: presidio_analyzer
Version: 2.2.359
Summary: Presidio Analyzer package
License: MIT
Keywords: presidio_analyzer
Author: Presidio
Author-email: presidio@microsoft.com
Requires-Python: >=3.9,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Provides-Extra: azure-ai-language
Provides-Extra: gliner
Provides-Extra: server
Provides-Extra: stanza
Provides-Extra: transformers
Requires-Dist: accelerate ; extra == "transformers"
Requires-Dist: azure-ai-textanalytics ; extra == "azure-ai-language"
Requires-Dist: azure-core ; extra == "azure-ai-language"
Requires-Dist: flask (>=1.1) ; extra == "server"
Requires-Dist: gliner (>=0.2.13,<1.0.0) ; (python_version >= "3.10") and (extra == "gliner")
Requires-Dist: gunicorn ; extra == "server"
Requires-Dist: huggingface_hub ; extra == "gliner"
Requires-Dist: huggingface_hub ; extra == "transformers"
Requires-Dist: onnxruntime (>=1.19) ; (python_version >= "3.10") and (extra == "gliner")
Requires-Dist: phonenumbers (>=8.12,<10.0.0)
Requires-Dist: pyyaml
Requires-Dist: regex
Requires-Dist: spacy (>=3.4.4,!=3.7.0,<4.0.0)
Requires-Dist: spacy_huggingface_pipelines ; extra == "transformers"
Requires-Dist: stanza (>=1.10.1,<2.0.0) ; extra == "stanza"
Requires-Dist: tldextract
Requires-Dist: transformers ; extra == "gliner"
Requires-Dist: transformers ; extra == "transformers"
Project-URL: Homepage, https://github.com/Microsoft/presidio
Description-Content-Type: text/markdown

# Presidio analyzer

## Description

The Presidio analyzer is a Python based service for detecting PII entities in text.

During analysis, it runs a set of different _PII Recognizers_,
each one in charge of detecting one or more PII entities using different mechanisms.

Presidio analyzer comes with a set of predefined recognizers,
but can easily be extended with other types of custom recognizers.
Predefined and custom recognizers leverage regex,
Named Entity Recognition and other types of logic to detect PII in unstructured text.

## Deploy Presidio analyzer to Azure

Use the following button to deploy presidio analyzer to your Azure subscription.

[![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2Fmicrosoft%2Fpresidio%2Fmain%2Fpresidio-analyzer%2Fdeploytoazure.json)

## Simple usage example

```python
from presidio_analyzer import AnalyzerEngine

# 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="My phone number is 212-555-5555",
                           entities=["PHONE_NUMBER"],
                           language='en')
print(results)

```

## Documentation

Additional documentation on installation, usage and extending the Analyzer can be found under the [Analyzer](https://microsoft.github.io/presidio/analyzer/) section of [Presidio Documentation](https://microsoft.github.io/presidio)

