You can configure the two documentation user interfaces included:

* **Swagger UI**: served at `/docs`.
    * You can set its URL with the parameter `docs_url`.
    * You can disable it by setting `docs_url=None`.
* **ReDoc**: served at `/redoc`.
    * You can set its URL with the parameter `redoc_url`.
    * You can disable it by setting `redoc_url=None`.

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

So, you might still need to use Pydantic models.

But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

///

## Dataclasses in `response_model` { #dataclasses-in-response-model }

You can also use `dataclasses` in the `response_model` parameter:

# Response Cookies { #response-cookies }

## Use a `Response` parameter { #use-a-response-parameter }

You can declare a parameter of type `Response` in your *path operation function*.

And then you can set cookies in that *temporal* response object.

{* ../../docs_src/response_cookies/tutorial002_py310.py hl[1, 8:9] *}

And then you can return any object you need, as you normally would (a `dict`, a database model, etc).

For those cases, you can use a `Response` parameter.

## Use a `Response` parameter { #use-a-response-parameter }

You can declare a parameter of type `Response` in your *path operation function* (as you can do for cookies and headers).

And then you can set the `status_code` in that *temporal* response object.

      value: >
        Comparing two approaches to a use case side by side can make it easier to examine the
        differences between them.


        Additionally, it's very useful to us if you can provide a "straw API" — what the
        method signatures would look like, for example, even if the method and class names are still
        in flux. This can make the feature you're suggesting much clearer to us.

  - type: textarea

You can use the same dependency *functions* you use normally.

### Dependency requirements { #dependency-requirements }

They can declare request requirements (like headers) or other sub-dependencies:

{* ../../docs_src/dependencies/tutorial006_an_py310.py hl[8,13] *}

### Raise exceptions { #raise-exceptions }

These dependencies can `raise` exceptions, the same as normal dependencies:

# Body - Updates { #body-updates }

## Update replacing with `PUT` { #update-replacing-with-put }

To update an item you can use the [HTTP `PUT`](https://developer.mozilla.org/en-US/docs/Web/HTTP/Methods/PUT) operation.

You can use the `jsonable_encoder` to convert the input data to data that can be stored as JSON (e.g. with a NoSQL database). For example, converting `datetime` to `str`.

{* ../../docs_src/body_updates/tutorial001_py310.py hl[28:33] *}

}
```

## Recap { #recap }

You can add multiple body parameters to your *path operation function*, even though a request can only have a single body.

But **FastAPI** will handle it, give you the correct data in your function, and validate and document the correct schema in the *path operation*.

You can also declare singular values to be received as part of the body.

Additional classes for handling WebSockets.

Provided directly by Starlette, but you can import it from `fastapi`:

```python
from fastapi.websockets import WebSocketDisconnect, WebSocketState
```

::: fastapi.websockets.WebSocketDisconnect

When a client disconnects, a `WebSocketDisconnect` exception is raised, you can catch it.

You can import it directly form `fastapi`:

```python
from fastapi import WebSocketDisconnect

# Declare Request Example Data { #declare-request-example-data }

You can declare examples of the data your app can receive.

Here are several ways to do it.

## Extra JSON Schema data in Pydantic models { #extra-json-schema-data-in-pydantic-models }

You can declare `examples` for a Pydantic model that will be added to the generated JSON Schema.

{* ../../docs_src/schema_extra_example/tutorial001_py310.py hl[13:24] *}