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(min_length=3, max_length=50, pattern="^fixedquery$")
    ] = None,
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

from fastapi import FastAPI
from fastapi.encoders import jsonable_encoder
from pydantic import BaseModel

fake_db = {}


class Item(BaseModel):
    title: str
    timestamp: datetime
    description: str | None = None


app = FastAPI()


@app.put("/items/{id}")
def update_item(id: str, item: Item):
    json_compatible_item_data = jsonable_encoder(item)

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)

/// note | Заметка

FastAPI понимает, что значение `q` не является обязательным из-за значения по умолчанию `= None`.

Аннотации типов `str | None` (Python 3.10+) или `Union[str, None]` (Python 3.9+) не используются FastAPI для определения обязательности; он узнает, что параметр не обязателен, потому что у него есть значение по умолчанию `= None`.

Но добавление аннотаций типов позволит вашему редактору кода лучше вас поддерживать и обнаруживать ошибки.

from typing import Annotated, Union

from fastapi import FastAPI
from fastapi.temp_pydantic_v1_params import Body
from pydantic.v1 import BaseModel


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    size: float


app = FastAPI()


@app.post("/items/")
async def create_item(item: Annotated[Item, Body(embed=True)]) -> Item:

        *,
        endpoint_ctx: Optional[EndpointContext] = None,
    ) -> None:
        super().__init__(errors, endpoint_ctx=endpoint_ctx)


class ResponseValidationError(ValidationException):
    def __init__(
        self,
        errors: Sequence[Any],
        *,
        body: Any = None,
        endpoint_ctx: Optional[EndpointContext] = None,
    ) -> None:
        super().__init__(errors, endpoint_ctx=endpoint_ctx)

from fastapi import FastAPI, Path, Query

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    item_id: int = Path(title="The ID of the item to get"),
    q: Union[str, None] = Query(default=None, alias="item-query"),
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

# Without aliases


@app.post("/optional-str", operation_id="optional_str")
async def read_optional_str(p: Annotated[Optional[str], Body(embed=True)] = None):
    return {"p": p}


class BodyModelOptionalStr(BaseModel):
    p: Optional[str] = None


@app.post("/model-optional-str", operation_id="model_optional_str")
async def read_model_optional_str(p: BodyModelOptionalStr):
    return {"p": p.p}

   * segments, each governed by its own write lock. The segment lock is taken once for each explicit
   * write, and twice for each cache loading computation (once prior to loading the new value, and
   * once after loading completes). Much internal cache management is performed at the segment