Skip to main content

Privacy-first text anonymization tool with enterprise-grade accuracy for removing PII from documents

Project description

🕵️ Anon - Privacy-First Text Anonymizer

CI PyPI Python Version

A powerful, offline-first text anonymization tool that removes personal identifiable information (PII) from text while keeping all data on your machine. Built with enterprise-grade accuracy using spaCy NER models and Microsoft Presidio.

✨ Features

  • 🔒 100% Offline - All processing happens on your machine
  • 🎯 High Accuracy - Advanced NER using spaCy large models + Presidio
  • 🖥️ Multiple Interfaces - Modern GUI, Web API, and CLI
  • 🚀 Background Processing - CLIs run detached with proper logging
  • 📦 Easy Installation - One-command install with automatic model setup
  • 🏢 Cross-Platform - Windows, macOS, and Linux support

🚀 Quick Start

Installation

pip install simple-anonymizer

The installation will automatically download the required spaCy model (en_core_web_lg) for optimal accuracy.

GUI Application

Launch the modern GUI interface:

anon-gui

The GUI runs in background - you can close the terminal after launch

📝 Logs available at ~/.anonymizer/gui_YYYYMMDD_HHMMSS.log

Web Interface

Start the web server:

anon-web start

Server runs in background - accessible at http://127.0.0.1:8080

📝 Comprehensive logging and process management

Web Server Management

# Start server (custom host/port)
anon-web start --host 0.0.0.0 --port 5000

# Check server status
anon-web status

# View recent logs
anon-web logs

# Stop server
anon-web stop

# Clean old log files
anon-web clean

Python API

from anonymizer_core import redact

# Basic anonymization
result = redact("John Doe works at Microsoft in Seattle.")
print(result.anonymized_text)
# Output: "<REDACTED> works at <REDACTED> in <REDACTED>."

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

simple_anonymizer-0.1.10.tar.gz (325.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

simple_anonymizer-0.1.10-py3-none-any.whl (50.0 kB view details)

Uploaded Python 3

File details

Details for the file simple_anonymizer-0.1.10.tar.gz.

File metadata

  • Download URL: simple_anonymizer-0.1.10.tar.gz
  • Upload date:
  • Size: 325.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.3 CPython/3.13.5 Darwin/24.5.0

File hashes

Hashes for simple_anonymizer-0.1.10.tar.gz
Algorithm Hash digest
SHA256 402c83398169e14659f523b5a2110a8eb04244f31eba76af1c93509e8b333721
MD5 573742684dc510da05b025d00780caff
BLAKE2b-256 b361c4a9dd5deeec554cfd8fa9cba909701f0cace810b58a66a143aacd66bf78

See more details on using hashes here.

File details

Details for the file simple_anonymizer-0.1.10-py3-none-any.whl.

File metadata

  • Download URL: simple_anonymizer-0.1.10-py3-none-any.whl
  • Upload date:
  • Size: 50.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.3 CPython/3.13.5 Darwin/24.5.0

File hashes

Hashes for simple_anonymizer-0.1.10-py3-none-any.whl
Algorithm Hash digest
SHA256 c5ca2609121ffe5c6444f7e69ebf9c74f7e1553c988e0e5bf0b9fbf931f8d5d1
MD5 976efd2775dbf71c85ab6cc7b1f028c1
BLAKE2b-256 be1b32e3814b5dee0b9bc9f33afe4e8a2df1316e696e758a22a83c83f953a7de

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page