Skip to main content

anonymize sensitive data in pydantic models

Project description

pydantic-anonymizer

PyPI version Python 3.10+ License MIT Status

anonymize sensitive data in pydantic models


                 ,--.                  ,--.  ,--.       
 ,---.,--. ,--.,-|  | ,--,--.,--,--, ,-'  '-.`--' ,---. 
| .-. |\  '  /' .-. |' ,-.  ||      \'-.  .-',--.| .--' 
| '-' ' \   ' \ `-' |\ '-'  ||  ||  |  |  |  |  |\ `--. 
|  |-'.-'  /   `---'  `--`--'`--''--'  `--'  `--' `---' 
`--'  `---'                                             
                                                                            
                                                  ,--.                      
 ,--,--.,--,--,  ,---. ,--,--, ,--. ,--.,--,--,--.`--',-----. ,---. ,--.--. 
' ,-.  ||      \| .-. ||      \ \  '  / |        |,--.`-.  / | .-. :|  .--' 
\ '-'  ||  ||  |' '-' '|  ||  |  \   '  |  |  |  ||  | /  `-.\   --.|  |    
 `--`--'`--''--' `---' `--''--'.-'  /   `--`--`--'`--'`-----' `----'`--'    
                               `---'                                        

📦 installation

pip install pydantic-anonymizer

📑 quick start

from pydantic import BaseModel, Field
from pydantic_anonymizer import Anonymizer

class UserProfile(BaseModel, Anonymizer):
    username: str
    email: str = Field(json_schema_extra={"anonymize": True})
    card_number: str = Field(json_schema_extra={"anonymize": "card"})
    phone_number: str = Field(json_schema_extra={"anonymize": "phone"})

user = UserProfile(
    username="ivan_dev",
    email="ivan@mail.com",
    card_number="4242111122223333",
    phone_number="+380500223785"
)

print(user.model_dump())
# {'username': 'ivan_dev', 'email': 'ivan@mail.com', 'card_number': '4242111122223333', 'phone_number': '+380500223785'}

print(user.model_dump_anonymized())
# {'username': 'ivan_dev', 'email': 'i***@***.com', 'card_number': '4242-****-****-3333', 'phone_number': '+380 (***) ***-**-85'}

🧩 features

  • 🔐 automatic masking - configure via json_schema_extra in model fields
  • 🎭 decorator - alternative to mixin via @Anonymize
  • 📧 email masking - partial mask for emails (i***@***.com)
  • 💳 card masking - format 4242-****-****-3333
  • 📱 phone masking - correct country code parsing with phonenumbers
  • 🌐 IP masking - 192.168.1.100192.168.***.***
  • 🎂 date masking - 15.03.1990**.**.****
  • 👤 name masking - John DoeJ*** D**
  • 🏦 IBAN masking - UA213996...6712UA**...****6712
  • 🏗️ nested models - recursive processing of nested Pydantic models
  • 📋 lists - support for list[Model] with masking of each element
  • 🛠️ custom strategies - your own masking functions via MaskRegistry
  • 📝 logging integration - AnonymizedFormatter for automatic masking in logs
  • async support - model_dump_anonymized_async() with async mask function support
  • reliable - 105 tests covering all scenarios (99% coverage)
  • 🪶 minimal dependencies - only pydantic>=2.0 and phonenumbers>=8.13

📖 usage

basic usage

from pydantic import BaseModel, Field
from pydantic_anonymizer import Anonymizer

class User(BaseModel, Anonymizer):
    name: str
    email: str = Field(json_schema_extra={"anonymize": True})

user = User(name="ivan", email="ivan@mail.com")

# original data
user.model_dump()  # {'name': 'ivan', 'email': 'ivan@mail.com'}

# masked data
user.model_dump_anonymized()  # {'name': 'ivan', 'email': 'i***@***.com'}

# JSON string
user.model_dump_json_anonymized()  # '{"name": "ivan", "email": "i***@***.com"}'

nested models

from pydantic import BaseModel, Field
from pydantic_anonymizer import Anonymizer

class Address(BaseModel, Anonymizer):
    city: str
    street: str = Field(json_schema_extra={"anonymize": True})

class UserProfile(BaseModel, Anonymizer):
    name: str
    address: Address

user = UserProfile(
    name="ivan",
    address=Address(city="Moscow", street="Lenina 1")
)

result = user.model_dump_anonymized()
# {'name': 'ivan', 'address': {'city': 'Moscow', 'street': 'L***a 1'}}

lists of models

from pydantic import BaseModel, Field
from pydantic_anonymizer import Anonymizer

class Card(BaseModel, Anonymizer):
    number: str = Field(json_schema_extra={"anonymize": "card"})

class Wallet(BaseModel, Anonymizer):
    cards: list[Card]

wallet = Wallet(cards=[
    Card(number="4242111122223333"),
    Card(number="5555666677778888")
])

result = wallet.model_dump_anonymized()
# {'cards': [{'number': '4242-****-****-3333'}, {'number': '5555-****-****-8888'}]}

custom strategies

from pydantic import BaseModel, Field
from pydantic_anonymizer import Anonymizer, MaskRegistry

# register your own masking function
def mask_ssn(value: str) -> str:
    return "***-**-" + value[-4:]

MaskRegistry.register("ssn", mask_ssn)

class Person(BaseModel, Anonymizer):
    ssn: str = Field(json_schema_extra={"anonymize": "ssn"})

person = Person(ssn="123-45-6789")
person.model_dump_anonymized()  # {'ssn': '***-**-6789'}

@Anonymize decorator

alternative to mixin - decorator adds model_dump_anonymized() without inheritance:

from pydantic import BaseModel
from pydantic_anonymizer import Anonymize

@Anonymize(email=True, card="card", phone="phone")
class Payment(BaseModel):
    email: str
    card: str
    phone: str

payment = Payment(email="a@b.com", card="4242111122223333", phone="+380500223785")
payment.model_dump_anonymized()
# {'email': 'a***@***.com', 'card': '4242-****-****-3333', 'phone': '+380 (***) ***-**-85'}

async support

async methods support both sync and async mask functions:

import asyncio
from pydantic import BaseModel, Field
from pydantic_anonymizer import Anonymizer, MaskRegistry

# async mask function (e.g., external API call)
async def mask_external(value: str) -> str:
    # masking logic with async I/O
    return "MASKED:" + value[:2] + "***"

MaskRegistry.register("external", mask_external)

class User(BaseModel, Anonymizer):
    email: str = Field(json_schema_extra={"anonymize": "external"})

async def process():
    user = User(email="test@mail.com")
    data = await user.model_dump_anonymized_async()
    json_str = await user.model_dump_json_anonymized_async()

asyncio.run(process())

🎭 built-in strategies

Strategy Field Input Output
True / "email" email ivan@mail.com i***@***.com
"card" card number 4242111122223333 4242-****-****-3333
"phone" phone +380500223785 +380 (***) ***-**-85
"ip" IP address 192.168.1.100 192.168.***.***
"birthdate" date of birth 15.03.1990 **.**.****
"name" full name John Doe J*** D**
"iban" IBAN UA213996...6712 UA**...****6712

country code support

phone masking works correctly with any country codes:

Country Code Example
Ukraine +380 +380500223785+380 (***) ***-**-85
USA +1 +14155552671+1 (***) ***-**-71
UK +44 +447911123456+44 (***) ***-**-56
Russia +7 +79161234567+7 (***) ***-**-67
Germany +49 +4915112345678+49 (***) ***-**-78
China +86 +8613812345678+86 (***) ***-**-78

📝 examples

FastAPI logging

from fastapi import FastAPI
from pydantic import BaseModel, Field
from pydantic_anonymizer import Anonymizer

app = FastAPI()

class UserCreate(BaseModel, Anonymizer):
    username: str
    email: str = Field(json_schema_extra={"anonymize": True})
    card_number: str = Field(json_schema_extra={"anonymize": "card"})

@app.post("/users")
def create_user(user: UserCreate):
    # log with masking
    print(user.model_dump_anonymized())
    # {'username': 'admin', 'email': 'a***@***.com', 'card_number': '4242-****-****-3333'}

    # original data for processing
    return user.model_dump()

safe logging

import logging
from pydantic import BaseModel, Field
from pydantic_anonymizer import Anonymizer

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Payment(BaseModel, Anonymizer):
    card_number: str = Field(json_schema_extra={"anonymize": "card"})
    amount: float

def process_payment(payment: Payment):
    # safe to log - card number is masked
    logger.info("payment: %s", payment.model_dump_anonymized())

    # work with original data
    charge_card(payment.card_number, payment.amount)

automatic masking in logs (AnonymizedFormatter)

import logging
from pydantic import BaseModel, Field
from pydantic_anonymizer import Anonymizer, AnonymizedFormatter

handler = logging.StreamHandler()
handler.setFormatter(AnonymizedFormatter("%(message)s"))

logger = logging.getLogger(__name__)
logger.addHandler(handler)
logger.setLevel(logging.INFO)

class User(BaseModel, Anonymizer):
    email: str = Field(json_schema_extra={"anonymize": True})

# automatically masks model in logs
logger.info("User: %s", User(email="ivan@mail.com"))
# outputs: User: {'email': 'i***@***.com'}

🧪 tests and coverage

# install dev dependencies
pip install -e ".[dev]"

# run tests
pytest

# run tests with coverage
pytest --cov=pydantic_anonymizer --cov-report=term-missing

📜 license

MIT

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

pydantic_anonymizer-0.3.0.tar.gz (17.2 kB view details)

Uploaded Source

Built Distribution

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

pydantic_anonymizer-0.3.0-py3-none-any.whl (9.8 kB view details)

Uploaded Python 3

File details

Details for the file pydantic_anonymizer-0.3.0.tar.gz.

File metadata

  • Download URL: pydantic_anonymizer-0.3.0.tar.gz
  • Upload date:
  • Size: 17.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.6

File hashes

Hashes for pydantic_anonymizer-0.3.0.tar.gz
Algorithm Hash digest
SHA256 a0916c1cfccefa2e747c487a9dfb54ee77e55abecd0d4c9aa90bcbf5534e762d
MD5 8004196a8b502ce0db600d7411b79b3b
BLAKE2b-256 be4c23b43752ff4a475d36d754df4748a48d72711faf4b452d46af497bb0b20d

See more details on using hashes here.

File details

Details for the file pydantic_anonymizer-0.3.0-py3-none-any.whl.

File metadata

File hashes

Hashes for pydantic_anonymizer-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 426cc35566cbc1a801f40fc4d412b9f990be362b8f3c38f589b05e8ed63bcf46
MD5 6d034c67e75fdcb5f25c6b7581b84f8c
BLAKE2b-256 93fada1db1bbd66233c58d1fe9000692d077ad4d5aec9067e583970cdb54046b

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