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# Pydantic-Factories
This library offers powerful mock data generation capabilities for [pydantic](https://github.com/samuelcolvin/pydantic)
based models, `dataclasses` and `TypeDict`s. It can also be used with other libraries that use pydantic as a foundation.
Check out [the documentation 📚](https://starlite-api.github.io/pydantic-factories/).
## Installation
```shell
pip install pydantic-factories
```
## Example
```python
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!](CONTRIBUTING.md)
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"description": "<!-- markdownlint-disable -->\n<img alt=\"Starlite logo\" src=\"docs/images/starlite-banner.svg\" width=\"100%\" height=\"auto\">\n<!-- markdownlint-restore -->\n\n<!-- markdownlint-disable -->\n<div align=\"center\">\n\n\n\n\n[](https://lgtm.com/projects/g/Goldziher/pydantic-factories/context:python)\n[](https://lgtm.com/projects/g/Goldziher/pydantic-factories/alerts/)\n[](https://sonarcloud.io/summary/new_code?id=starlite-api_pydantic-factories)\n[](https://sonarcloud.io/summary/new_code?id=starlite-api_pydantic-factories)\n[](https://sonarcloud.io/summary/new_code?id=starlite-api_pydantic-factories)\n[](https://sonarcloud.io/summary/new_code?id=starlite-api_pydantic-factories)\n\n[](https://discord.gg/X3FJqy8d2j)\n\n</div>\n<!-- markdownlint-restore -->\n\n# Pydantic-Factories\n\nThis library offers powerful mock data generation capabilities for [pydantic](https://github.com/samuelcolvin/pydantic)\nbased models, `dataclasses` and `TypeDict`s. It can also be used with other libraries that use pydantic as a foundation.\n\nCheck out [the documentation \ud83d\udcda](https://starlite-api.github.io/pydantic-factories/).\n\n## Installation\n\n```shell\npip install pydantic-factories\n```\n\n## Example\n\n```python\nfrom datetime import date, datetime\nfrom typing import List, Union\n\nfrom pydantic import BaseModel, UUID4\n\nfrom pydantic_factories import ModelFactory\n\n\nclass Person(BaseModel):\n id: UUID4\n name: str\n hobbies: List[str]\n age: Union[float, int]\n birthday: Union[datetime, date]\n\n\nclass PersonFactory(ModelFactory):\n __model__ = Person\n\n\nresult = PersonFactory.build()\n```\n\nThat's it - with almost no work, we are able to create a mock data object fitting the `Person` class model definition.\n\nThis is possible because of the typing information available on the pydantic model and model-fields, which are used as a\nsource of truth for data generation.\n\nThe factory parses the information stored in the pydantic model and generates a dictionary of kwargs that are passed to\nthe `Person` class' init method.\n\n## Features\n\n- \u2705 supports both built-in and pydantic types\n- \u2705 supports pydantic field constraints\n- \u2705 supports complex field types\n- \u2705 supports custom model fields\n- \u2705 supports dataclasses\n\n## Why This Library?\n\n- \ud83d\udcaf powerful\n- \ud83d\udcaf extensible\n- \ud83d\udcaf simple\n- \ud83d\udcaf rigorously tested\n\n## Contributing\n\nThis library is open to contributions - in fact we welcome it. [Please see the contribution guide!](CONTRIBUTING.md)\n",
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