# Fauxdantic
A library for generating fake Pydantic models for testing. Fauxdantic makes it easy to create realistic test data for your Pydantic models. Pairs well with testing of fastapi endpoints.
## Installation
```bash
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
- Generate dictionaries of fake data without creating model instances
## Usage
### Basic Usage
```python
from pydantic import BaseModel
from fauxdantic import faux, faux_dict
class User(BaseModel):
name: str
age: int
email: str
is_active: bool
# Generate a fake user
fake_user = faux(User)
print(fake_user)
# Output: name='Smith' age=2045 email='smith@example.com' is_active=True
# Generate a dictionary of fake values
fake_dict = faux_dict(User)
print(fake_dict)
# Output: {'name': 'Smith', 'age': 2045, 'email': 'smith@example.com', 'is_active': True}
```
### Nested Models
```python
from pydantic import BaseModel
from fauxdantic import faux, faux_dict
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 = faux(User)
print(fake_user)
# Output: name='Smith' age=2045 address=Address(street='123 Main St', city='Anytown', zip_code='12345')
# Generate a dictionary with nested address
fake_dict = faux_dict(User)
print(fake_dict)
# Output: {'name': 'Smith', 'age': 2045, 'address': {'street': '123 Main St', 'city': 'Anytown', 'zip_code': '12345'}}
```
### Optional Fields
```python
from typing import Optional
from pydantic import BaseModel
from fauxdantic import faux, faux_dict
class User(BaseModel):
name: str
age: Optional[int]
email: Optional[str]
# Generate a fake user with optional fields
fake_user = faux(User)
print(fake_user)
# Output: name='Smith' age=None email='smith@example.com'
# Generate a dictionary with optional fields
fake_dict = faux_dict(User)
print(fake_dict)
# Output: {'name': 'Smith', 'age': None, 'email': 'smith@example.com'}
```
### Lists and Dicts
```python
from typing import List, Dict
from pydantic import BaseModel
from fauxdantic import faux, faux_dict
class User(BaseModel):
name: str
tags: List[str]
preferences: Dict[str, str]
# Generate a fake user with lists and dicts
fake_user = faux(User)
print(fake_user)
# Output: name='Smith' tags=['tag1', 'tag2'] preferences={'key1': 'value1', 'key2': 'value2'}
# Generate a dictionary with lists and dicts
fake_dict = faux_dict(User)
print(fake_dict)
# Output: {'name': 'Smith', 'tags': ['tag1', 'tag2'], 'preferences': {'key1': 'value1', 'key2': 'value2'}}
```
### Custom Values
```python
from pydantic import BaseModel
from fauxdantic import faux, faux_dict
class User(BaseModel):
name: str
age: int
email: str
# Generate a fake user with custom values
fake_user = faux(User, name="John Doe", age=30)
print(fake_user)
# Output: name='John Doe' age=30 email='smith@example.com'
# Generate a dictionary with custom values
fake_dict = faux_dict(User, name="John Doe", age=30)
print(fake_dict)
# Output: {'name': 'John Doe', 'age': 30, 'email': 'smith@example.com'}
```
### Unique String Generation
Fauxdantic supports generating truly unique string values using the `<unique>` pattern. This is useful for creating unique identifiers, route numbers, or any field that requires uniqueness.
```python
from typing import Optional
from pydantic import BaseModel, Field
from fauxdantic import faux
class Bus(BaseModel):
route_number: Optional[str] = Field(None, max_length=50)
# Generate buses with unique route numbers
bus1 = faux(Bus, route_number="SW<unique>")
bus2 = faux(Bus, route_number="SW<unique>")
bus3 = faux(Bus, route_number="EXPRESS<unique>")
print(bus1.route_number) # SW1753986564318970_793119f2
print(bus2.route_number) # SW1753986564319017_f33460cc
print(bus3.route_number) # EXPRESS1753986564319059_9f1de0da
```
#### Examples with Different Constraints
```python
class ShortBus(BaseModel):
route_number: Optional[str] = Field(None, max_length=10)
class MediumBus(BaseModel):
route_number: Optional[str] = Field(None, max_length=15)
class LongBus(BaseModel):
route_number: Optional[str] = Field(None, max_length=50)
# Different constraint lengths
short_bus = faux(ShortBus, route_number="SW<unique>") # SWf2830b (9 chars)
medium_bus = faux(MediumBus, route_number="SW<unique>") # SW208936f1 (11 chars)
long_bus = faux(LongBus, route_number="SW<unique>") # SW1753986564318970_793119f2 (28 chars)
```
### Enums
```python
from enum import Enum
from pydantic import BaseModel
from fauxdantic import faux, faux_dict
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 = faux(User)
print(fake_user)
# Output: name='Smith' role=<UserRole.ADMIN: 'admin'>
# Generate a dictionary with enum
fake_dict = faux_dict(User)
print(fake_dict)
# Output: {'name': 'Smith', 'role': 'admin'}
```
## Development
```bash
# 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.
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"description": "# Fauxdantic\n\nA library for generating fake Pydantic models for testing. Fauxdantic makes it easy to create realistic test data for your Pydantic models. Pairs well with testing of fastapi endpoints.\n\n## Installation\n\n```bash\npoetry add fauxdantic\n```\n\n## Features\n\n- Generate fake data for any Pydantic model\n- Support for nested models\n- Support for common Python types:\n - Basic types (str, int, float, bool)\n - Optional types\n - Lists\n - Dicts\n - UUIDs\n - Datetimes\n - Enums\n- Customizable values through keyword arguments\n- Generate dictionaries of fake data without creating model instances\n\n## Usage\n\n### Basic Usage\n\n```python\nfrom pydantic import BaseModel\nfrom fauxdantic import faux, faux_dict\n\nclass User(BaseModel):\n name: str\n age: int\n email: str\n is_active: bool\n\n# Generate a fake user\nfake_user = faux(User)\nprint(fake_user)\n# Output: name='Smith' age=2045 email='smith@example.com' is_active=True\n\n# Generate a dictionary of fake values\nfake_dict = faux_dict(User)\nprint(fake_dict)\n# Output: {'name': 'Smith', 'age': 2045, 'email': 'smith@example.com', 'is_active': True}\n```\n\n### Nested Models\n\n```python\nfrom pydantic import BaseModel\nfrom fauxdantic import faux, faux_dict\n\nclass Address(BaseModel):\n street: str\n city: str\n zip_code: str\n\nclass User(BaseModel):\n name: str\n age: int\n address: Address\n\n# Generate a fake user with nested address\nfake_user = faux(User)\nprint(fake_user)\n# Output: name='Smith' age=2045 address=Address(street='123 Main St', city='Anytown', zip_code='12345')\n\n# Generate a dictionary with nested address\nfake_dict = faux_dict(User)\nprint(fake_dict)\n# Output: {'name': 'Smith', 'age': 2045, 'address': {'street': '123 Main St', 'city': 'Anytown', 'zip_code': '12345'}}\n```\n\n### Optional Fields\n\n```python\nfrom typing import Optional\nfrom pydantic import BaseModel\nfrom fauxdantic import faux, faux_dict\n\nclass User(BaseModel):\n name: str\n age: Optional[int]\n email: Optional[str]\n\n# Generate a fake user with optional fields\nfake_user = faux(User)\nprint(fake_user)\n# Output: name='Smith' age=None email='smith@example.com'\n\n# Generate a dictionary with optional fields\nfake_dict = faux_dict(User)\nprint(fake_dict)\n# Output: {'name': 'Smith', 'age': None, 'email': 'smith@example.com'}\n```\n\n### Lists and Dicts\n\n```python\nfrom typing import List, Dict\nfrom pydantic import BaseModel\nfrom fauxdantic import faux, faux_dict\n\nclass User(BaseModel):\n name: str\n tags: List[str]\n preferences: Dict[str, str]\n\n# Generate a fake user with lists and dicts\nfake_user = faux(User)\nprint(fake_user)\n# Output: name='Smith' tags=['tag1', 'tag2'] preferences={'key1': 'value1', 'key2': 'value2'}\n\n# Generate a dictionary with lists and dicts\nfake_dict = faux_dict(User)\nprint(fake_dict)\n# Output: {'name': 'Smith', 'tags': ['tag1', 'tag2'], 'preferences': {'key1': 'value1', 'key2': 'value2'}}\n```\n\n### Custom Values\n\n```python\nfrom pydantic import BaseModel\nfrom fauxdantic import faux, faux_dict\n\nclass User(BaseModel):\n name: str\n age: int\n email: str\n\n# Generate a fake user with custom values\nfake_user = faux(User, name=\"John Doe\", age=30)\nprint(fake_user)\n# Output: name='John Doe' age=30 email='smith@example.com'\n\n# Generate a dictionary with custom values\nfake_dict = faux_dict(User, name=\"John Doe\", age=30)\nprint(fake_dict)\n# Output: {'name': 'John Doe', 'age': 30, 'email': 'smith@example.com'}\n```\n\n### Unique String Generation\n\nFauxdantic supports generating truly unique string values using the `<unique>` pattern. This is useful for creating unique identifiers, route numbers, or any field that requires uniqueness.\n\n```python\nfrom typing import Optional\nfrom pydantic import BaseModel, Field\nfrom fauxdantic import faux\n\nclass Bus(BaseModel):\n route_number: Optional[str] = Field(None, max_length=50)\n\n# Generate buses with unique route numbers\nbus1 = faux(Bus, route_number=\"SW<unique>\")\nbus2 = faux(Bus, route_number=\"SW<unique>\")\nbus3 = faux(Bus, route_number=\"EXPRESS<unique>\")\n\nprint(bus1.route_number) # SW1753986564318970_793119f2\nprint(bus2.route_number) # SW1753986564319017_f33460cc\nprint(bus3.route_number) # EXPRESS1753986564319059_9f1de0da\n```\n\n#### Examples with Different Constraints\n\n```python\nclass ShortBus(BaseModel):\n route_number: Optional[str] = Field(None, max_length=10)\n\nclass MediumBus(BaseModel):\n route_number: Optional[str] = Field(None, max_length=15)\n\nclass LongBus(BaseModel):\n route_number: Optional[str] = Field(None, max_length=50)\n\n# Different constraint lengths\nshort_bus = faux(ShortBus, route_number=\"SW<unique>\") # SWf2830b (9 chars)\nmedium_bus = faux(MediumBus, route_number=\"SW<unique>\") # SW208936f1 (11 chars)\nlong_bus = faux(LongBus, route_number=\"SW<unique>\") # SW1753986564318970_793119f2 (28 chars)\n```\n\n### Enums\n\n```python\nfrom enum import Enum\nfrom pydantic import BaseModel\nfrom fauxdantic import faux, faux_dict\n\nclass UserRole(str, Enum):\n ADMIN = \"admin\"\n USER = \"user\"\n GUEST = \"guest\"\n\nclass User(BaseModel):\n name: str\n role: UserRole\n\n# Generate a fake user with enum\nfake_user = faux(User)\nprint(fake_user)\n# Output: name='Smith' role=<UserRole.ADMIN: 'admin'>\n\n# Generate a dictionary with enum\nfake_dict = faux_dict(User)\nprint(fake_dict)\n# Output: {'name': 'Smith', 'role': 'admin'}\n```\n\n## Development\n\n```bash\n# Install dependencies\npoetry install\n\n# Run tests\npoetry run pytest\n\n# Format code\npoetry run black .\npoetry run isort .\n\n# Type checking\npoetry run mypy .\n```\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.\n\n## License\n\nThis project is licensed under the MIT License - see the LICENSE file for details. ",
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