/// 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:

   * occur when using {@link CacheBuilder#weakKeys}, {@link CacheBuilder#weakValues}, or {@link
   * CacheBuilder#softValues}.
   */
  COLLECTED {
    @Override
    boolean wasEvicted() {
      return true;
    }
  },

  /**
   * The entry's expiration timestamp has passed. This can occur when using {@link

Therefore, if you run a `tf.train.Server` in your network, anybody with access
to the network can execute arbitrary code with the privileges of the user
running the `tf.train.Server`.

## Untrusted inputs during training and prediction

TensorFlow supports a wide range of input data formats. For example it can
process images, audio, videos, and text. There are several modules specialized

$ python main.py

// Now it can read the environment variable

Hello Wade Wilson from Python
```

</div>

////

As environment variables can be set outside of the code, but can be read by the code, and don't have to be stored (committed to `git`) with the rest of the files, it's common to use them for configurations or **settings**.

///

## Learn More { #learn-more }

You can learn more about **GraphQL** in the [official GraphQL documentation](https://graphql.org/).

* Many PRs don't have tests, you can **remind** them to add tests, or you can even **suggest** some tests yourself. That's one of the things that consume most time and you can help a lot with that.

* Then also comment what you tried, that way I'll know that you checked it. 🤓

## Create a Pull Request { #create-a-pull-request }

# 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).

You can return a `RedirectResponse` directly:

{* ../../docs_src/custom_response/tutorial006_py310.py hl[2,9] *}

---

Or you can use it in the `response_class` parameter:


{* ../../docs_src/custom_response/tutorial006b_py310.py hl[2,7,9] *}

If you do that, then you can return the URL directly from your *path operation* function.

# Configure Swagger UI { #configure-swagger-ui }

You can configure some extra [Swagger UI parameters](https://swagger.io/docs/open-source-tools/swagger-ui/usage/configuration/).

To configure them, pass the `swagger_ui_parameters` argument when creating the `FastAPI()` app object or to the `get_swagger_ui_html()` function.

`swagger_ui_parameters` receives a dictionary with the configurations passed to Swagger UI directly.

Each section gradually builds on the previous ones, but it's structured to separate topics, so that you can go directly to any specific one to solve your specific API needs.

It is also built to work as a future reference so you can come back and see exactly what you need.

## Run the code { #run-the-code }

All the code blocks can be copied and used directly (they are actually tested Python files).