///

## Another module with `APIRouter` { #another-module-with-apirouter }

Let's say you also have the endpoints dedicated to handling "items" from your application in the module at `app/routers/items.py`.

You have *path operations* for:

* `/items/`
* `/items/{item_id}`

It's all the same structure as with `app/routers/users.py`.

But we want to be smarter and simplify the code a bit.

                    type: array
                    items:
                      type: string
                    example: ["aaa"]
                  related_contents:
                    type: array
                    items:
                      type: string
                    example: []
                  data:
                    type: array
                    items:
                      type: object

이 경우, 아래로 이동하면:

```
http://127.0.0.1:8000/items/foo?short=1
```

또는

```
http://127.0.0.1:8000/items/foo?short=True
```

또는

```
http://127.0.0.1:8000/items/foo?short=true
```

또는

```
http://127.0.0.1:8000/items/foo?short=on
```

또는

```
http://127.0.0.1:8000/items/foo?short=yes
```

from fastapi import FastAPI

app = FastAPI()


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}
```

### Dockerfile { #dockerfile }

Ahora, en el mismo directorio del proyecto, crea un archivo `Dockerfile` con:

```{ .dockerfile .annotate }

		Number2 uint64     `gorm:"default:NULL"`
		Number3 float64    `gorm:"default:NULL"`
		Now     *time.Time `gorm:"default:NULL"`
		Item1Id string
		Item1   *QueryResetItem `gorm:"references:ID"`
		Item2Id string
		Item2   *QueryResetItem `gorm:"references:ID"`
	}

	DB.Migrator().DropTable(&QueryResetNullValue{}, &QueryResetItem{})
	DB.AutoMigrate(&QueryResetNullValue{}, &QueryResetItem{})

from fastapi import FastAPI

app = FastAPI()


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}
```

### Dockerfile { #dockerfile }

Agora, no mesmo diretório do projeto, crie um arquivo `Dockerfile` com:

```{ .dockerfile .annotate }

        }
        RenderDataUtil.register(data, "fileConfigItems", itemList);
    }

    /**
     * Creates a dropdown item with label and value.
     *
     * @param label the item label
     * @param value the item value
     * @return map containing the item
     */
    protected Map<String, String> createItem(final String label, final String value) {
        final Map<String, String> map = new HashMap<>(2);

                    readings[0] = l.toArray(String[]::new);

                    if (items == null) {
                        items = new ArrayList<>(text.length() * fields.length / field.length());
                    }

                    final String[] langs = lang == null ? new String[] {} : new String[] { lang };
                    items.add(new SuggestItem(words, readings, new String[] { field }, 1L, 0, -1, tags, roles, langs,

And Python has a special data type for sets of unique items, the `set`.

Then we can declare `tags` as a set of strings:

{* ../../docs_src/body_nested_models/tutorial003_py310.py hl[12] *}

With this, even if you receive a request with duplicate data, it will be converted to a set of unique items.

And whenever you output that data, even if the source had duplicates, it will be output as a set of unique items.

async def read_users_me(
    current_user: Annotated[User, Depends(get_current_active_user)],
):
    return current_user


@app.get("/users/me/items/")
async def read_own_items(
    current_user: Annotated[User, Depends(get_current_active_user)],
):