> ## Documentation Index
> Fetch the complete documentation index at: https://docs.squarecloud.app/llms.txt
> Use this file to discover all available pages before exploring further.

# Using pydantic

> Learn how to use pydantic to data validation.

## What is pydantic?

Pydantic is an awesome and modern Python library for data validation using
type annotations. It enforces type constraints, ensuring data consistency and
providing clear error messages when validation fails. Pydantic is both
powerful and easy to use, making it a popular choice for developers working
with structured data.

## Installation

To use Pydantic with this SDK, you need to install the SDK with the pydantic
extra dependency, as it is not included by default:

```bash theme={null}
pip install "squarecloud[pydantic]"
```

## Features

In this SDK, Pydantic is used to cast an extra parameter from a dictionary
into a Pydantic model, allowing for more robust data
validation and manipulation.

```python theme={null}
import squarecloud as square
from squarecloud import Endpoint
from pydantic import BaseModel

class Animal(BaseModel):
    name: str
    age: int

@client.on_request(Endpoint.status())
async def get_extra_param(before, after, extra: Animal):
    print(extra.name)
    print(extra.age)

async def main():
    client = square.Client('your api key')
    await client.app_status('application_id', extra={'name': 'felix', 'age': 3})
```

In this example, the Animal class is a Pydantic model with two
fields: name and age. When a request is made to the status endpoint,
the extra parameter is automatically cast into an Animal instance, allowing
you to easily access and validate the data.