pseudonymizer-uk 0.1.3

A Python library for pseudonymizing Ukrainian text using Presidio analyzer with Ukrainian NER model

Ukrainian Text Pseudonymizer

A Python library for pseudonymizing Ukrainian text using the Presidio analyzer framework with a Ukrainian NER model. This tool can identify and anonymize various types of entities in Ukrainian text, including:

• Person names
• Job titles
• Locations
• Organizations
• Date/Time expressions
• Email addresses
• Credit card numbers
• URLs
• Phone numbers

Requirements

• Python 3.8
• Git LFS (for model download)

Installation

1. Install the package using uv:

uv pip install pseudonymizer-uk

2. Install Git LFS (required for model download):

git lfs install

3. Download the Ukrainian NER model:

git clone https://huggingface.co/dchaplinsky/uk_ner_web_trf_13class

Usage

from pseudonymizer_uk import UkPseudonymizer

# Initialize the pseudonymizer with the path to the downloaded model
pseudonymizer = UkPseudonymizer(path_to_model="./uk_ner_web_trf_13class")

# Pseudonymize text
text = "Іван Франко народився в селі Нагуєвичі"
anonymized_text = pseudonymizer.pseudonymize(text)

Supported Entity Types

By default, the pseudonymizer recognizes the following entity types:

• PERSON
• JOB
• LOCATION
• ORGANIZATION
• DATE_TIME

You can customize which entities to recognize by passing the entities parameter:

pseudonymizer = UkPseudonymizer(
    path_to_model="uk_ner_web_trf_13class",
    entities=['PERSON', 'LOCATION']  # Only recognize persons and locations
)

Custom Recognizers and Operators

You can extend the functionality by adding custom recognizers and operators:

from presidio_analyzer import EntityRecognizer
from presidio_anonymizer import OperatorConfig

# Add custom recognizer
pseudonymizer.add_custom_recognizer(your_custom_recognizer)

# Add custom operator
pseudonymizer.add_custom_operator(
    "CUSTOM_ENTITY",
    OperatorConfig("custom", {"param": "value"})
)

Development

To set up the development environment:

1. Clone the repository:

git clone https://github.com/fox-rudie/pseudonymizer-uk.git
cd pseudonymizer-uk

2. Create a virtual environment and install dependencies using uv:

uv venv
source .venv/bin/activate  # On Unix/macOS
# or
.venv\Scripts\activate  # On Windows

uv pip install -e ".[dev]"

3. Install pre-commit hooks (optional):

uv pip install pre-commit
pre-commit install

Publishing

To publish a new version to PyPI:

1. Update version in pyproject.toml and __init__.py

2. Build the package:

uv pip install build
python -m build

3. Upload to PyPI:

uv pip install twine
python -m twine upload dist/*

License

MIT License