ShadowData

A Python library for anonymizing, masking, and encrypting sensitive data with a small, focused API.

What it does today

• Text and pattern anonymization (free-form text replacement, IPv4, email, phone)
• Localized identifiers (US SSN, Brazil CPF/CNPJ)
• Symmetric encryption and decryption (Fernet)
• PII detection via spaCy (optional extra)

Planned: richer masking helpers and reversible transforms.

Installation

pip install shadow_data

Optional spaCy support:

pip install shadow_data[spacy]

spaCy models are downloaded automatically at runtime when needed. To install manually:

python -m spacy download en_core_web_trf

Quickstart

from shadow_data.anonymization import (
    EmailAnonymization,
    Ipv4Anonymization,
    PhoneNumberAnonymization,
    TextProcessor,
)
from shadow_data.cryptohash.symmetric_cipher import Symmetric
from shadow_data.l10n.usa import IdentifierAnonymizer

text = "Contact me at [email protected] or 415-555-0199. Server: 10.0.0.1"
anonymized_text = Ipv4Anonymization.anonymize_ipv4(text)
anonymized_text = TextProcessor.replace_text("Contact", "Reach", anonymized_text)
email = EmailAnonymization.anonymize_email("[email protected]")
phone = PhoneNumberAnonymization.anonymize_phone_number("415-555-0199")
print(anonymized_text, email, phone)

ssn = "Billy's SSN is 479-92-5042."
ssn_anonymizer = IdentifierAnonymizer(ssn)
ssn_anonymizer.anonymize()
print(ssn_anonymizer.cleaned_content)

symmetric = Symmetric()
key = symmetric.create_key()
ciphertext = symmetric.encrypt("hello")
plaintext = symmetric.decrypt(ciphertext)
print(key, ciphertext, plaintext)

Docs

• docs/README.md
• docs/usage.md
• docs/cryptography.md
• docs/pii.md

Examples

• examples/quickstart.py
• examples/anonymization.md
• examples/i10n_us.md
• examples/i10n_brazil.md
• examples/pii_nlp.md
• examples/symmetric_cipher.md

Testing

poetry run pytest -vvv

Contributing

1. Fork the repository.
2. Create a new branch for your feature (git checkout -b my-new-feature).
3. Commit your changes (git commit -am 'Add new feature').
4. Push the branch (git push origin my-new-feature).
5. Open a pull request.

License

This project is licensed under the MIT License - see LICENSE for details.