fauxdantic 0.1.0

A library for generating fake Pydantic models for testing and development purposes

Fauxdantic

A library for generating fake Pydantic models for testing and development purposes. Fauxdantic makes it easy to create realistic test data for your Pydantic models.

Installation

poetry add fauxdantic

Features

• Generate fake data for any Pydantic model
• Support for nested models
• Support for common Python types:
  • Basic types (str, int, float, bool)
  • Optional types
  • Lists
  • Dicts
  • UUIDs
  • Datetimes
  • Enums
• Customizable values through keyword arguments

Usage

Basic Usage

from pydantic import BaseModel
from fauxdantic import fake_model

class User(BaseModel):
    name: str
    age: int
    email: str
    is_active: bool

# Generate a fake user
fake_user = fake_model(User)
print(fake_user)
# Output: name='Smith' age=2045 email='[e-mail]' is_active=True

Nested Models

from pydantic import BaseModel
from fauxdantic import fake_model

class Address(BaseModel):
    street: str
    city: str
    zip_code: str

class User(BaseModel):
    name: str
    age: int
    address: Address

# Generate a fake user with nested address
fake_user = fake_model(User)
print(fake_user)
# Output: name='Smith' age=2045 address=Address(street='123 Main St', city='Anytown', zip_code='12345')

Optional Fields

from typing import Optional
from pydantic import BaseModel
from fauxdantic import fake_model

class User(BaseModel):
    name: str
    age: Optional[int]
    email: Optional[str]

# Generate a fake user with optional fields
fake_user = fake_model(User)
print(fake_user)
# Output: name='Smith' age=None email='[e-mail]'

Lists and Dicts

from typing import List, Dict
from pydantic import BaseModel
from fauxdantic import fake_model

class User(BaseModel):
    name: str
    tags: List[str]
    preferences: Dict[str, str]

# Generate a fake user with lists and dicts
fake_user = fake_model(User)
print(fake_user)
# Output: name='Smith' tags=['tag1', 'tag2'] preferences={'key1': 'value1', 'key2': 'value2'}

Custom Values

from pydantic import BaseModel
from fauxdantic import fake_model

class User(BaseModel):
    name: str
    age: int
    email: str

# Generate a fake user with custom values
fake_user = fake_model(User, name="John Doe", age=30)
print(fake_user)
# Output: name='John Doe' age=30 email='[e-mail]'

Enums

from enum import Enum
from pydantic import BaseModel
from fauxdantic import fake_model

class UserRole(str, Enum):
    ADMIN = "admin"
    USER = "user"
    GUEST = "guest"

class User(BaseModel):
    name: str
    role: UserRole

# Generate a fake user with enum
fake_user = fake_model(User)
print(fake_user)
# Output: name='Smith' role=<UserRole.ADMIN: 'admin'>

Development

# Install dependencies
poetry install

# Run tests
poetry run pytest

# Format code
poetry run black .
poetry run isort .

# Type checking
poetry run mypy .

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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