{* ../../docs_src/response_model/tutorial003_py310.py hl[24] *}

...`response_model` olarak, password’ü içermeyen `UserOut` modelimizi declare ettik:

{* ../../docs_src/response_model/tutorial003_py310.py hl[22] *}

Dolayısıyla **FastAPI**, output model’de declare edilmemiş tüm verileri (Pydantic kullanarak) filtrelemekle ilgilenir.

### `response_model` mi Return Type mı? { #response-model-or-return-type }

```

Em alguns casos, é até possível ter modelos Pydantic v1 e v2 na mesma **operação de rota** na sua aplicação FastAPI:

{* ../../docs_src/pydantic_v1_in_v2/tutorial003_an_py310.py hl[2:3,6,12,21:22] *}

No exemplo acima, o modelo de entrada é um modelo Pydantic v1, e o modelo de saída (definido em `response_model=ItemV2`) é um modelo Pydantic v2.

### Parâmetros do Pydantic v1 { #pydantic-v1-parameters }

    // Check with modifiable copies of the list
    new PeekingIteratorTester<T>(list).test();

    // Check with unmodifiable lists
    new IteratorTester<T>(
        list.size() * 2 + 2, UNMODIFIABLE, list, IteratorTester.KnownOrder.KNOWN_ORDER) {
      @Override
      protected Iterator<T> newTargetIterator() {
        Iterator<T> iterator = unmodifiableList(list).iterator();

`perf` is generally available via `apg-get install perf` or `pacman -S perf`. FCML is a little more involved. This worked
on 2020-08-01:

```
wget https://github.com/swojtasiak/fcml-lib/releases/download/v1.2.2/fcml-1.2.2.tar.gz
tar xf fcml*
cd fcml*
./configure
make
cd example/hsdis
make
sudo cp .libs/libhsdis.so.0.0.0 /usr/lib/jvm/java-14-adoptopenjdk/lib/hsdis-amd64.so
```

{* ../../docs_src/response_model/tutorial003_py310.py hl[24] *}

...hemos declarado el `response_model` para ser nuestro modelo `UserOut`, que no incluye la contraseña:

{* ../../docs_src/response_model/tutorial003_py310.py hl[22] *}

Entonces, **FastAPI** se encargará de filtrar todos los datos que no estén declarados en el modelo de salida (usando Pydantic).

### `response_model` o Tipo de Retorno { #response-model-or-return-type }

ｫ => オ
ｬ => ヤ
ｭ => ユ
ｮ => ヨ
ﾞ => ゛
ﾟ => ゜
ｰ => ー
･ => ・

０ => 0
１ => 1
２ => 2
３ => 3
４ => 4
５ => 5
６ => 6
７ => 7
８ => 8
９ => 9

① => 1\u0020
② => 2\u0020
③ => 3\u0020
④ => 4\u0020
⑤ => 5\u0020
⑥ => 6\u0020
⑦ => 7\u0020
⑧ => 8\u0020
⑨ => 9\u0020

！ => !
？ => ?
＃ => #
％ => %
＆ => &
＠ => @
＋ => +
－ => -
＊ => *

... haben wir deklariert, dass `response_model` das Modell `UserOut` ist, welches das Passwort nicht enthält:

{* ../../docs_src/response_model/tutorial003_py310.py hl[22] *}

Darum wird **FastAPI** sich darum kümmern, dass alle Daten, die nicht im Ausgabemodell deklariert sind, herausgefiltert werden (mittels Pydantic).

### `response_model` oder Rückgabewert { #response-model-or-return-type }

  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteTensor(t);
  TF_DeleteStatus(status);
  return th;
}

TFE_TensorHandle* DoubleTestMatrixTensorHandle(TFE_Context* ctx) {
  int64_t dims[] = {2, 2};
  double data[] = {1.0, 2.0, 3.0, 4.0};
  TF_Status* status = TF_NewStatus();
  TF_Tensor* t = TFE_AllocateHostTensor(ctx, TF_DOUBLE, &dims[0],
                                        sizeof(dims) / sizeof(int64_t), status);

<img src="/img/tutorial/path-operation-advanced-configuration/image01.png">

Y si ves el OpenAPI resultante (en `/openapi.json` en tu API), verás tu extensión como parte de la *path operation* específica también:

```JSON hl_lines="22"
{
    "openapi": "3.1.0",
    "info": {
        "title": "FastAPI",
        "version": "0.1.0"
    },
    "paths": {
        "/items/": {
            "get": {

```

Dans certains cas, il est même possible d'avoir des modèles Pydantic v1 et v2 dans le même **chemin d'accès** de votre application FastAPI :

{* ../../docs_src/pydantic_v1_in_v2/tutorial003_an_py310.py hl[2:3,6,12,21:22] *}

Dans l'exemple ci-dessus, le modèle d'entrée est un modèle Pydantic v1 et le modèle de sortie (défini dans `response_model=ItemV2`) est un modèle Pydantic v2.

### Paramètres Pydantic v1 { #pydantic-v1-parameters }