/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

So, you might still need to use Pydantic models.

But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

///

## Dataclasses in `response_model` { #dataclasses-in-response-model }

You can also use `dataclasses` in the `response_model` parameter:

Bedenken Sie, dass Datenklassen nicht alles können, was Pydantic-Modelle können.

Daher müssen Sie möglicherweise weiterhin Pydantic-Modelle verwenden.

Wenn Sie jedoch eine Menge Datenklassen herumliegen haben, ist dies ein guter Trick, um sie für eine Web-API mithilfe von FastAPI zu verwenden. 🤓

///

## Datenklassen als `response_model`

Sie können `dataclasses` auch im Parameter `response_model` verwenden:

```Python hl_lines="4  9-12  25-27"
from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):

### Advertencia sobre el reemplazo

Esto significa que si quieres actualizar el ítem `bar` usando `PUT` con un body que contenga:

```Python
{
    "name": "Barz",
    "price": 3,
    "description": None,
}
```

debido a que no incluye el atributo ya almacenado `"tax": 20.2`, el modelo de entrada tomaría el valor por defecto de `"tax": 10.5`.

### Warnung bezüglich des Ersetzens

Das bedeutet, dass, wenn Sie den Artikel `bar` aktualisieren wollen, mittels `PUT` und folgendem Body:

```Python
{
    "name": "Barz",
    "price": 3,
    "description": None,
}
```

das Eingabemodell nun den Defaultwert `"tax": 10.5` hat, weil Sie das bereits gespeicherte Attribut `"tax": 20.2` nicht mit übergeben haben.

### Aviso sobre a substituição

Isso significa que, se você quiser atualizar o item `bar` usando `PUT` com um corpo contendo:

```Python
{
    "name": "Barz",
    "price": 3,
    "description": None,
}
```

Como ele não inclui o atributo já armazenado `"tax": 20.2`, o modelo de entrada assumiria o valor padrão de `"tax": 10.5`.

E os dados seriam salvos com esse "novo" `tax` de `10.5`.

          return Lists.<LockGraphNode>newArrayListWithCapacity(3);
        }
      };

  /**
   * A Throwable used to record a stack trace that illustrates an example of a specific lock
   * acquisition ordering. The top of the stack trace is truncated such that it starts with the
   * acquisition of the lock in question, e.g.
   *
   * <pre>
   * com...ExampleStackTrace: LockB -&gt; LockC

例えば、上記のモデルは以下の様なJSON「`オブジェクト`」(もしくはPythonの `dict` ) を宣言しています:

```JSON
{
    "name": "Foo",
    "description": "An optional description",
    "price": 45.2,
    "tax": 3.5
}
```

...`description` と `tax` はオプショナル (デフォルト値は `None`) なので、以下のJSON「`オブジェクト`」も有効です:

```JSON
{
    "name": "Foo",
    "price": 45.2
}
```

## パラメータとして宣言

*パスオペレーション* に加えるために、パスパラメータやクエリパラメータと同じ様に宣言します:

                        this.sizeExpiration = currentTime + cacheTimeout;
                        log.trace("Retrieved size info in additional query: {}", this.size);
                    }
                } catch (CIFSException e) {
                    // Size query failed, but we have basic info - continue
                    log.trace("Size query failed, continuing with basic info", e);
                }
            }

 * resulting {@link HashCode} is dependent only on the bytes inserted, and the order in which they
 * were inserted, not how those bytes were chunked into discrete put() operations. For example, the
 * following three expressions all generate colliding hash codes:
 *
 * {@snippet :
 * newHasher().putByte(b1).putByte(b2).putByte(b3).hash()
 * newHasher().putByte(b1).putBytes(new byte[] { b2, b3 }).hash()