"tax": 3.2,
            "tags": ["foo", "bar", "foo"],
        },
    )
    assert response.status_code == 200, response.text
    assert response.json() == {
        "item_id": 123,
        "item": {
            "name": "Foo",
            "description": "A very nice Item",
            "price": 35.4,
            "tax": 3.2,
            "tags": tags_expected,
        },
    }

        "price": 50.2,
        "tax": 10.5,
        "tags": [],
    }


def test_put(client: TestClient):
    response = client.put(
        "/items/bar", json={"name": "Barz", "price": 3, "description": None}
    )
    assert response.json() == {
        "name": "Barz",
        "description": None,
        "price": 3,
        "tax": 10.5,
        "tags": [],
    }

    return f"{route.tags[0]}-{route.name}"


app = FastAPI(generate_unique_id_function=custom_generate_unique_id)


class Item(BaseModel):
    name: str
    price: float


class ResponseMessage(BaseModel):
    message: str


class User(BaseModel):
    username: str
    email: str


@app.post("/items/", response_model=ResponseMessage, tags=["items"])
async def create_item(item: Item):

    ],
)

tf_cuda_cc_test(
    name = "gradients_test",
    size = "small",
    srcs = [
        "gradients_test.cc",
    ],
    args = ["--heap_check="],
    tags = tf_cuda_tests_tags() + ["nomac"],
    deps = [
        ":abstract_context",
        ":abstract_tensor_handle",
        ":c_api_experimental",
        ":c_api_test_util",
        ":c_api_unified_internal",

from fastapi import FastAPI

app = FastAPI()


@app.get("/items/", tags=["items"])
async def read_items():
    return [{"name": "Foo", "price": 42}]


@app.get("/users/", tags=["users"])
async def read_users():
    return [{"username": "johndoe"}]


@app.get("/elements/", tags=["items"], deprecated=True)
async def read_elements():

servers:
  - url: http://localhost:8080/api/v1
tags:
  - name: search
    description: Search operations
  - name: popularword
    description: Popular word operations
  - name: monitor
    description: Monitoring operations
  - name: suggest
    description: Suggest operations
  - name: favorite
    description: Favorite operations
paths:
  /documents:
    get:
      tags:
        - search

  # any targets in ignored packages. Combine this list of targets into a bazel
  # query list (e.g. the list becomes "target+target2+target3")
  bazel cquery --keep_going 'kind(py_test, //tensorflow/python/...) - attr("tags", "no_pip|manual", //tensorflow/python/...)' | grep -v -f $BATS_TEST_TMPDIR/ignore_deps_for_these_packages | paste -sd "+" - > $BATS_TEST_TMPDIR/deps
  # Find all one-step dependencies of those tests which are from //tensorflow

@app.post("/items/", response_model=ResponseMessage, tags=["items"])
async def create_item(item: Item):
    return {"message": "Item received"}


@app.get("/items/", response_model=list[Item], tags=["items"])
async def get_items():
    return [
        {"name": "Plumbus", "price": 3},
        {"name": "Portal Gun", "price": 9001},
    ]


@app.post("/users/", response_model=ResponseMessage, tags=["users"])
async def create_user(user: User):

## Documentation Tags - OpenAPI { #documentation-tags-openapi }

To add tags to your *path operations*, and group them in the docs UI, read the docs for [Tutorial - Path Operation Configurations - Tags](../tutorial/path-operation-configuration.md#tags).

## Documentation Summary and Description - OpenAPI { #documentation-summary-and-description-openapi }

So, in our example, we can make `tags` be specifically a "list of strings":

{* ../../docs_src/body_nested_models/tutorial002_py310.py hl[12] *}

## Set types { #set-types }

But then we think about it, and realize that tags shouldn't repeat, they would probably be unique strings.

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

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