from typing import Annotated

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: Annotated[str | None, Query(title="Query string", min_length=3)] = None,
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

from typing import Annotated

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    hidden_query: Annotated[str | None, Query(include_in_schema=False)] = None,
):
    if hidden_query:
        return {"hidden_query": hidden_query}
    else:

from typing import Union

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    hidden_query: Union[str, None] = Query(default=None, include_in_schema=False),
):
    if hidden_query:
        return {"hidden_query": hidden_query}
    else:

from typing import Optional

from fastapi.openapi.models import OpenIdConnect as OpenIdConnectModel
from fastapi.security.base import SecurityBase
from starlette.exceptions import HTTPException
from starlette.requests import Request
from starlette.status import HTTP_403_FORBIDDEN
from typing_extensions import Annotated, Doc


class OpenIdConnect(SecurityBase):
    """
    OpenID Connect authentication class. An instance of it would be used as a

from typing import Annotated, Union

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: Annotated[Union[str, None], Query(title="Query string", min_length=3)] = None,
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

### Importe `List` do typing

Primeiramente, importe `List` do módulo `typing` que já vem por padrão no Python:

```Python hl_lines="1"
{!../../../docs_src/body_nested_models/tutorial002.py!}
```

### Declare a `List` com um parâmetro de tipo

Para declarar tipos que têm parâmetros de tipo(tipos internos), como `list`, `dict`, `tuple`:

* Importe os do modulo `typing`

from typing import Annotated, Union

from fastapi import Cookie, Depends, FastAPI

app = FastAPI()


def query_extractor(q: Union[str, None] = None):
    return q


def query_or_cookie_extractor(
    q: Annotated[str, Depends(query_extractor)],
    last_query: Annotated[Union[str, None], Cookie()] = None,
):
    if not q:
        return last_query
    return q


@app.get("/items/")
async def read_query(

from datetime import datetime, time, timedelta
from typing import Annotated
from uuid import UUID

from fastapi import Body, FastAPI

app = FastAPI()


@app.put("/items/{item_id}")
async def read_items(
    item_id: UUID,
    start_datetime: Annotated[datetime, Body()],
    end_datetime: Annotated[datetime, Body()],
    process_after: Annotated[timedelta, Body()],
    repeat_at: Annotated[time | None, Body()] = None,
):

import re
import warnings
from dataclasses import is_dataclass
from typing import (
    TYPE_CHECKING,
    Any,
    Dict,
    MutableMapping,
    Optional,
    Set,
    Type,
    Union,
    cast,
)
from weakref import WeakKeyDictionary

import fastapi
from fastapi._compat import (
    PYDANTIC_V2,
    BaseConfig,
    ModelField,
    PydanticSchemaGenerationError,
    Undefined,
    UndefinedType,

from datetime import datetime, time, timedelta
from typing import Annotated, Union
from uuid import UUID

from fastapi import Body, FastAPI

app = FastAPI()


@app.put("/items/{item_id}")
async def read_items(
    item_id: UUID,
    start_datetime: Annotated[datetime, Body()],
    end_datetime: Annotated[datetime, Body()],
    process_after: Annotated[timedelta, Body()],
    repeat_at: Annotated[Union[time, None], Body()] = None,
):