builder.append(' ');
        builder.append(name);
        builder.append('(');
        for (int i = 0; i < parameters.size(); i++) {
            ParameterMetaData param = parameters.get(i);
            if (i > 0) {
                builder.append(", ");
            }
            builder.append(param.getSignature());
        }
        builder.append(')');
        return builder.toString();

                int offset = 0;
                for (int i = 0; i < readingTokenList.size(); i++) {
                    final String term = termTokenList.get(i).getTerm();
                    String reading = readingTokenList.get(i).getTerm();
                    if (Strings.isNullOrEmpty(reading)) {
                        reading = term;
                    }

  @Override
  public boolean addAll(int index, Collection<? extends E> elements) {
    return delegate().addAll(index, elements);
  }

  @Override
  @ParametricNullness
  public E get(int index) {
    return delegate().get(index);
  }

  @Override
  public int indexOf(@CheckForNull Object element) {
    return delegate().indexOf(element);
  }

  @Override

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(q: str = Query(min_length=3)):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

from fastapi import FastAPI

app = FastAPI()


@app.on_event("shutdown")
def shutdown_event():
    with open("log.txt", mode="a") as log:
        log.write("Application shutdown")


@app.get("/items/")
async def read_items():

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":

        extra = "forbid"

    limit: int = Field(100, gt=0, le=100)
    offset: int = Field(0, ge=0)
    order_by: Literal["created_at", "updated_at"] = "created_at"
    tags: List[str] = []


@app.get("/items/")
async def read_items(filter_query: FilterParams = Query()):

version: 2
updates:
  # Go configuration for master branch
  - package-ecosystem: "gomod"
    directory: "/"
    schedule:
      interval: "daily"
    # Limit number of open PRs to 0 so that we only get security updates
    # See https://docs.github.com/en/code-security/dependabot/dependabot-security-updates/configuring-dependabot-security-updates
    open-pull-requests-limit: 0
    labels:

elif _tf_api_dir not in __path__:
  __path__.append(_tf_api_dir)

# Hook external TensorFlow modules.
# Import compat before trying to import summary from tensorboard, so that
# reexport_tf_summary can get compat from sys.modules. Only needed if using
# lazy loading.
_current_module.compat.v2  # pylint: disable=pointless-statement

# Load tensorflow-io-gcs-filesystem if enabled

class Item(BaseModel):
    name: str
    description: Optional[str] = None


app = FastAPI(separate_input_output_schemas=False)


@app.post("/items/")
def create_item(item: Item):
    return item


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),