pydantic-factories 1.13.0

Mock data generation for pydantic based models and python dataclasses

Pydantic-Factories

This library offers powerful mock data generation capabilities for pydantic based models, dataclasses and TypeDicts. It can also be used with other libraries that use pydantic as a foundation.

Check out the documentation 📚.

Installation

pip install pydantic-factories

Example

from datetime import date, datetime
from typing import List, Union

from pydantic import BaseModel, UUID4

from pydantic_factories import ModelFactory


class Person(BaseModel):
    id: UUID4
    name: str
    hobbies: List[str]
    age: Union[float, int]
    birthday: Union[datetime, date]


class PersonFactory(ModelFactory):
    __model__ = Person


result = PersonFactory.build()

That's it - with almost no work, we are able to create a mock data object fitting the Person class model definition.

This is possible because of the typing information available on the pydantic model and model-fields, which are used as a source of truth for data generation.

The factory parses the information stored in the pydantic model and generates a dictionary of kwargs that are passed to the Person class' init method.

Features

• ✅ supports both built-in and pydantic types
• ✅ supports pydantic field constraints
• ✅ supports complex field types
• ✅ supports custom model fields
• ✅ supports dataclasses

Why This Library?

• 💯 powerful
• 💯 extensible
• 💯 simple
• 💯 rigorously tested

Contributing

This library is open to contributions - in fact we welcome it. Please see the contribution guide!