assert response.status_code == 200
        assert response.json() == {"message": "all good?"}


def test_broken_return_finishes():
    client = TestClient(app, raise_server_exceptions=False)
    response = client.get("/broken")
    assert response.status_code == 200

// Opts contains options for the cache.
type Opts struct {
	// When set to true, return the last cached value
	// even if updating the value errors out.
	// Returns the last good value AND the error.
	ReturnLastGood bool

	// If NoWait is set, Get() will return the last good value,
	// if TTL has expired but 2x TTL has not yet passed,
	// but will fetch a new value in the background.
	NoWait bool
}

@app.get("/items/")
async def read_items(
    q: Annotated[
        str | None,
        Query(
            title="Query string",
            description="Query string for the items to search in the database that have a good match",
            min_length=3,
        ),
    ] = None,
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

## Pydantic { #pydantic }

All the data validation is performed under the hood by <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a>, so you get all the benefits from it. And you know you are in good hands.

You can use the same type declarations with `str`, `float`, `bool` and many other complex data types.

    q: Annotated[
        str | None,
        Query(
            alias="item-query",
            title="Query string",
            description="Query string for the items to search in the database that have a good match",
            min_length=3,
            max_length=50,
            pattern="^fixedquery$",
            deprecated=True,
        ),
    ] = None,
):

                    "operationId": "read_items_items__get",
                    "parameters": [
                        {
                            "description": "Query string for the items to search in the database that have a good match",
                            "required": False,
                            "schema": {
                                "anyOf": [
                                    {

    # to support it as a first class "feature"
    assert is_bytes_sequence_annotation(Union[list[str], list[bytes]])


def test_is_uploadfile_sequence_annotation():
    # For coverage
    # TODO: in theory this would allow declaring types that could be lists of UploadFile
    # and other types, but I'm not even sure it's a good idea to support it as a first
    # class "feature"

Wenn der Client beispielsweise versucht, ein `santa_tracker`-Cookie mit einem Wert von `good-list-please` zu senden, erhält der Client eine **Error-Response**, die ihm mitteilt, dass das `santa_tracker` <abbr title="Santa beschwert sich über den Mangel an Cookies. 🎅 Okay, keine Cookie-Witze mehr.">Cookie nicht erlaubt ist</abbr>:

如果客户尝试发送一些**额外的 cookie**，他们将收到**错误**响应。

可怜的 cookie 通知条，费尽心思为了获得您的同意，却被<abbr title="这又是一个笑话，别管我了，给您的小饼干（cookie）配上点咖啡吧。☕">API 拒绝了</abbr>。🍪

例如，如果客户端尝试发送一个值为 `good-list-please` 的 `santa_tracker` cookie，客户端将收到一个**错误**响应，告知他们 `santa_tracker` <abbr title="圣诞老人（Santa）不赞成没有小饼干（cookie）。🎅 好吧，不会再开 cookie 的玩笑了。">cookie 是不允许的</abbr>：

```json
{
    "detail": [
        {

Por exemplo, se o cliente tentar enviar um cookie `santa_tracker` com o valor de `good-list-please`, o cliente receberá uma resposta de **erro** informando que o `santa_tracker` <abbr title="O papai noel desaprova a falta de biscoitos. 🎅 Ok, chega de piadas com os cookies.">cookie não é permitido</abbr>:

```json
{