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.

!!! info
    <a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">Enumerations (or enums) are available in Python</a> since version 3.4.

!!! tip
    If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <abbr title="Technically, Deep Learning model architectures">models</abbr>.

### Declare a *path parameter*

```

!!! info "说明"

    Python 3.4 及之后版本支持<a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">枚举（即 enums）</a>。

!!! tip "提示"

    **AlexNet**、**ResNet**、**LeNet** 是机器学习<abbr title="技术上来说是深度学习模型架构">模型</abbr>。

### 声明*路径参数*

使用 Enum 类（`ModelName`）创建使用类型注解的*路径参数*：

```Python hl_lines="16"
{!../../../docs_src/path_params/tutorial005.py!}
```

    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

!!! tip "Consejo"
    Si lo estás dudando, "AlexNet", "ResNet", y "LeNet" son solo nombres de <abbr title="Técnicamente, arquitecturas de modelos de Deep Learning">modelos</abbr> de Machine Learning.

### Declara un *parámetro de path*

    <a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">Enumerations (ou enums) estão disponíveis no Python</a> desde a versão 3.4.

!!! tip "Dica"
	Se você está se perguntando, "AlexNet", "ResNet", e "LeNet" são apenas nomes de <abbr title="técnicamente, modelos de arquitetura de Deep Learning">modelos</abbr> de Machine Learning (aprendizado de máquina).

### Declare um *parâmetro de rota*

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":

    FastAPI will still be able to override it.

Then you can reset your overrides (remove them) by setting `app.dependency_overrides` to be an empty `dict`:

```Python
app.dependency_overrides = {}
```

!!! tip

```

A **context manager** in Python is something that you can use in a `with` statement, for example, `open()` can be used as a context manager:

```Python
with open("file.txt") as file:
    file.read()
```

In recent versions of Python, there's also an **async context manager**. You would use it with `async with`:

```Python
async with lifespan(app):
    await do_stuff()
```

@app.put("/user/{user_id}")
def put_user(user_id: str, name: str = Body(), db: dict = Depends(get_database)):
    db[user_id] = name
    return {"message": "OK"}


@pytest.fixture(autouse=True)
def reset_state_and_db():
    global fake_database
    global state
    fake_database = initial_fake_database.copy()
    state = initial_state.copy()


client = TestClient(app)


def test_dependency_gets_exception():