# Metadaten und Dokumentations-URLs { #metadata-and-docs-urls }

Sie können mehrere Metadaten-Konfigurationen in Ihrer **FastAPI**-Anwendung anpassen.

## Metadaten für die API { #metadata-for-api }

Sie können die folgenden Felder festlegen, die in der OpenAPI-Spezifikation und in den Benutzeroberflächen der automatischen API-Dokumentation verwendet werden:

| Parameter | Typ | Beschreibung |
|------------|------|-------------|

# Metadata y URLs de Docs { #metadata-and-docs-urls }

Puedes personalizar varias configuraciones de metadata en tu aplicación **FastAPI**.

## Metadata para la API { #metadata-for-api }

Puedes establecer los siguientes campos que se usan en la especificación OpenAPI y en las interfaces automáticas de documentación de la API:

| Parámetro | Tipo | Descripción |
|------------|------|-------------|
| `title` | `str` | El título de la API. |

from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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


class User(BaseModel):
    username: str
    full_name: Union[str, None] = None


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

from datetime import datetime, time, timedelta
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: datetime = Body(),
    end_datetime: datetime = Body(),
    process_after: timedelta = Body(),
    repeat_at: time | None = Body(default=None),
):
    start_process = start_datetime + process_after

from enum import Enum

from fastapi import FastAPI


class ModelName(str, Enum):
    alexnet = "alexnet"
    resnet = "resnet"
    lenet = "lenet"


app = FastAPI()


@app.get("/models/{model_name}")
async def get_model(model_name: ModelName):
    if model_name is ModelName.alexnet:
        return {"model_name": model_name, "message": "Deep Learning FTW!"}

    if model_name.value == "lenet":

from typing import Annotated

from fastapi import FastAPI, Path, Query

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    *,
    item_id: Annotated[int, Path(title="The ID of the item to get", ge=0, le=1000)],
    q: str,
    size: Annotated[float, Query(gt=0, lt=10.5)],
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})
    if size:
        results.update({"size": size})

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",
            description="Query string for the items to search in the database that have a good match",
            min_length=3,
        ),
    ] = None,
):

import json

import pytest
from fastapi import BackgroundTasks, Depends, FastAPI
from fastapi.responses import StreamingResponse
from fastapi.testclient import TestClient

app = FastAPI()
state = {
    "/async": "asyncgen not started",
    "/sync": "generator not started",
    "/async_raise": "asyncgen raise not started",
    "/sync_raise": "generator raise not started",
    "context_a": "not started a",
    "context_b": "not started b",

Объявите нужные **query-параметры** в **Pydantic-модели**, а после аннотируйте параметр как `Query`:

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

**FastAPI извлечёт** данные соответствующие **каждому полю модели** из **query-параметров** запроса и выдаст вам объявленную Pydantic-модель заполненную ими.

## Проверьте Сгенерированную Документацию { #check-the-docs }

import importlib

import pytest
from dirty_equals import IsList
from fastapi.testclient import TestClient

from ...utils import needs_py310


@pytest.fixture(
    name="client",
    params=[
        pytest.param("tutorial001_py39"),
        pytest.param("tutorial001_py310", marks=needs_py310),
        pytest.param("tutorial002_py39"),
        pytest.param("tutorial002_py310", marks=needs_py310),
    ],
)