You will learn more about adding extra information later in the docs, when learning to declare examples.

!!! warning
    Extra keys passed to `Field` will also be present in the resulting OpenAPI schema for your application.

    * Check that it has a required attribute `price` that has to be a `float`.
    * Check that it has an optional attribute `is_offer`, that should be a `bool`, if present.
    * All this would also work for deeply nested JSON objects.
* Convert from and to JSON automatically.
* Document everything with OpenAPI, that can be used by:
    * Interactive documentation systems.

    assert response.status_code == 200
    assert response.json() == {"model_name": "lenet", "message": "LeCNN all the images"}


def test_get_enums_resnet():
    response = client.get("/models/resnet")
    assert response.status_code == 200
    assert response.json() == {"model_name": "resnet", "message": "Have some residuals"}


def test_get_enums_invalid():
    response = client.get("/models/foo")
    assert response.status_code == 422

async def set_up_request_state_dependency():
    request_state = {"user": "deadpond"}
    contextvar_token = legacy_request_state_context_var.set(request_state)
    yield request_state
    legacy_request_state_context_var.reset(contextvar_token)


@app.middleware("http")
async def custom_middleware(
    request: Request, call_next: Callable[[Request], Awaitable[Response]]
):
    response = await call_next(request)

    <a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">Enumerationen (oder kurz Enums)</a> gibt es in Python seit Version 3.4.

!!! tip "Tipp"
    Falls Sie sich fragen, was „AlexNet“, „ResNet“ und „LeNet“ ist, das sind Namen von <abbr title="Genau genommen, Deep-Learning-Modellarchitekturen">Modellen</abbr> für maschinelles Lernen.

### Deklarieren Sie einen *Pfad-Parameter*

As Python advances, **newer versions** come with improved support for these type annotations and in many cases you won't even need to import and use the `typing` module to declare the type annotations.

If you can choose a more recent version of Python for your project, you will be able to take advantage of that extra simplicity.

In all the docs there are examples compatible with each version of Python (when there's a difference).

C'est du travail "synchrone", vous être "synchronisés" avec le serveur/cuisinier 👨‍🍳. Vous devez attendre 🕙 et être présent au moment exact où le serveur/cuisinier 👨‍🍳 finira les burgers 🍔 et vous les donnera, sinon quelqu'un risque de vous les prendre.

    * Revisar si tiene un atributo requerido `price` que debe ser un `float`.
    * Revisar si tiene un atributo opcional `is_offer`, que debe ser un `bool`si está presente.
    * Todo esto funcionaría para objetos JSON profundamente anidados.
* Convertir de y a JSON automáticamente.
* Documentar todo con OpenAPI que puede ser usado por:
    * Sistemas de documentación interactiva.

* Fix incorrect `Request` class import. PR [#493](https://github.com/tiangolo/fastapi/pull/493) by [@kamalgill](https://github.com/kamalgill).

## 0.38.0

* Add recent articles to [External Links](https://fastapi.tiangolo.com/external-links/) and recent opinions. PR [#490](https://github.com/tiangolo/fastapi/pull/490).

from enum import Enum

from fastapi import FastAPI


class ModelName(str, Enum):
    alexnet = "alexnet"
    resnet = "resnet"
    lenet = "lenet"


app = FastAPI()


@app.get("/models/{model_name}")
async def get_model(model_name: ModelName):
    if model_name is ModelName.alexnet:
        return {"model_name": model_name, "message": "Deep Learning FTW!"}

    if model_name.value == "lenet":