mysto - Data Anonymization in Python

Requires

This project was built and tested with Python 3.6 and later versions. It requires the pycryptodome and ff3 libraries:

pip3 install pycryptodome pip3 install ff3

Installation

Install this project with pip:

pip3 install mysto

Usage

The Mysto toolkit provides an integrated de-identification solution, including:

• Date generalization
• Format-preserving encryption (FPE) for alphanumerics
• Masking, including customized rules for US SSN
• HIPAA compliant date and zip code rules

Code Example

The code example below can help you get started:

import pandas as pd
from datetime import date
import main 

d = {'SSN': ['938-49-5100', '976-52-7639'], 'date': [date(1994,2,22), date(2000,10,10)]}
df = pd.DataFrame(data=d)
rules = [ '{"column" : "SSN", "type" : "Mask", "format" : "5" }',  '{"column" : "date", "type" : "Generalize.Date"}' ]
out_df = main.anonymize(df, rules)
print(out_df)

Testing

To run unit tests on this implementation:

1. python3 rules_test.py

Implementation Notes

Author

Brad Schoening

License

This project is licensed under the terms of the Server Side Pubic License.