$liEle = $("<li/>");
                  $liEle.html(str);
                  $liEle.click(function() {
                    var str = $(this).html();
                    suggestor.fixList();
                    $textArea.val(str);
                    if (typeof $settingSearchForm !== "undefined") {
                      $settingSearchForm.submit();

from pydantic_settings import BaseSettings


class Settings(BaseSettings):
    app_name: str = "Awesome API"
    admin_email: str

from fastapi import FastAPI, Form

app = FastAPI()


@app.post("/login/")
async def login(username: str = Form(), password: str = Form()):

from fastapi.encoders import jsonable_encoder
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: Union[str, None] = None
    description: Union[str, None] = None
    price: Union[float, None] = None
    tax: float = 10.5
    tags: list[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},

    std::string name = "Conj_Exp_Grad";
    TF_RETURN_IF_ERROR(SafeConj(ctx, exp_.get(), &conj_output, name.c_str()));
    AbstractTensorHandlePtr conj_output_releaser(conj_output);

    name = "Mul_Exp_Grad";
    TF_RETURN_IF_ERROR(
        Mul(ctx, conj_output, grad_outputs[0], &grad_inputs[0], name.c_str()));
    return absl::OkStatus();
  }
  ~ExpGradientFunction() override {}

 private:

from fastapi import FastAPI
from pydantic import BaseModel, EmailStr

app = FastAPI()


class UserIn(BaseModel):
    username: str
    password: str
    email: EmailStr
    full_name: Union[str, None] = None


class UserOut(BaseModel):
    username: str
    email: EmailStr
    full_name: Union[str, None] = None


@app.post("/user/", response_model=UserOut)
async def create_user(user: UserIn) -> Any:

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


class User(BaseModel):
    username: str
    full_name: str | None = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item, user: User):

from pydantic import BaseModel, HttpUrl

app = FastAPI()


class Image(BaseModel):
    url: HttpUrl
    name: str


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None
    tags: Set[str] = set()
    image: Union[Image, None] = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item):

from pydantic import BaseModel, HttpUrl

app = FastAPI()


class Image(BaseModel):
    url: HttpUrl
    name: str


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None
    tags: set[str] = set()
    image: Union[Image, None] = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item):

```

O uso de `Opcional [str]` em vez de apenas `str` permitirá que o editor o ajude a detectar erros, onde você pode estar assumindo que um valor é sempre um `str`, quando na verdade também pode ser `None`.

#### Tipos genéricos

Esses tipos que usam parâmetros de tipo entre colchetes, como:

* `List`
* `Tuple`
* `Set`
* `Dict`
* `Opcional`
* ...e outros.