from typing import Union

from fastapi import Depends, FastAPI

app = FastAPI()


async def common_parameters(
    q: Union[str, None] = None, skip: int = 0, limit: int = 100
):
    return {"q": q, "skip": skip, "limit": limit}


@app.get("/items/")
async def read_items(commons: dict = Depends(common_parameters)):
    return commons


@app.get("/users/")
async def read_users(commons: dict = Depends(common_parameters)):

app = FastAPI()


@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})

Your response model could have default values, like:

{* ../../docs_src/response_model/tutorial004_py310.py hl[9,11:12] *}

* `description: Union[str, None] = None` (or `str | None = None` in Python 3.10) has a default of `None`.
* `tax: float = 10.5` has a default of `10.5`.
* `tags: List[str] = []` has a default of an empty list: `[]`.

Seu modelo de resposta pode ter valores padrão, como:

{* ../../docs_src/response_model/tutorial004_py310.py hl[9,11:12] *}

* `description: Union[str, None] = None` (ou `str | None = None` no Python 3.10) tem um padrão de `None`.
* `tax: float = 10.5` tem um padrão de `10.5`.
* `tags: List[str] = []` tem um padrão de uma lista vazia: `[]`.

 *
 */
public interface BeanConfigurationRequest {

    /**
     * Gets the bean to configure. Eventually, a valid request must have a bean set.
     *
     * @return The bean to configure, or {@code null} if none.
     */
    Object getBean();

    /**
     * Sets the bean to configure. Eventually, a valid request must have a bean set.
     *
     * @param bean The bean to configure, may be {@code null}.

            "axisLabel": "",
            "axisPlacement": "auto",
            "barAlignment": 0,
            "drawStyle": "line",
            "fillOpacity": 10,
            "gradientMode": "none",
            "hideFrom": {
              "legend": false,
              "tooltip": false,
              "viz": false
            },
            "insertNulls": false,
            "lineInterpolation": "linear",

from pydantic import BaseModel, WithJsonSchema

app = FastAPI()


class Item(BaseModel):
    name: str

    description: Annotated[
        Optional[str], WithJsonSchema({"type": ["string", "null"]})
    ] = None

    model_config = {
        "json_schema_extra": {
            "x-something-internal": {"level": 4},
        }
    }


@app.get("/foo", response_model=Item)
def foo():
    return {"name": "Foo item"}

from fastapi.testclient import TestClient
from pydantic.dataclasses import dataclass

app = FastAPI()


@dataclass
class Item:
    name: str
    price: Optional[float] = None
    owner_ids: Optional[list[int]] = None


@app.get("/items/invalid", response_model=Item)
def get_invalid():
    return {"name": "invalid", "price": "foo"}


@app.get("/items/innerinvalid", response_model=Item)

    assert response.json() == {
        "item_id": 5,
        "item": {
            "name": "Foo",
            "description": None,
            "price": 35.4,
            "tax": None,
            "tags": [],
            "images": None,
        },
    }


def test_put_empty_body(client: TestClient):
    response = client.put(
        "/items/5",
        json={},
    )

async def read_items(
    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,
):