Vous pouvez retourner un dictionnaire (`dict`), une liste (`list`), des valeurs seules comme des chaines de caractères (`str`) et des entiers (`int`), etc.

Vous pouvez aussi retourner des models **Pydantic** (qui seront détaillés plus tard).

Il y a de nombreux autres objets et modèles qui seront automatiquement convertis en JSON. Essayez d'utiliser vos favoris, il est fort probable qu'ils soient déjà supportés.

## Récapitulatif

* Importez `FastAPI`.

 * <ol>
 * <li>success - in which case only the model field is set
 * <li>success with warnings - model field + non-error model problems
 * <li>error - no model, but diagnostics
 * <li>error - (partial) model and diagnostics
 * </ol>
 * Could encode these variants as subclasses, but kept in one for now
 *
 * @param <T> the model type
 * @deprecated use {@link org.apache.maven.api.services.ModelBuilder} instead

    private /* static */ long upperEight(byte[] bytes) {
      return Longs.fromBytes(
          bytes[15], bytes[14], bytes[13], bytes[12], bytes[11], bytes[10], bytes[9], bytes[8]);
    }
  };

  /**
   * Models a lock-free array of bits.
   *
   * <p>We use this instead of java.util.BitSet because we need access to the array of longs and we
   * need compare-and-swap.
   */
  static final class LockFreeBitArray {

/// note | "備考"

入力モデルがまだ検証されていることに注目してください。

そのため、すべての属性を省略できる部分的な変更を受け取りたい場合は、すべての属性をオプションとしてマークしたモデルを用意する必要があります（デフォルト値または`None`を使用して）。

**更新** のためのオプション値がすべて設定されているモデルと、**作成** のための必須値が設定されているモデルを区別するには、[追加モデル](extra-models.md){.internal-link target=_blank}で説明されている考え方を利用することができます。

///

/// tip

If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <abbr title="Technically, Deep Learning model architectures">models</abbr>.

///

### Declare a *path parameter*

Then create a *path parameter* with a type annotation using the enum class you created (`ModelName`):

```Python hl_lines="16"

from typing import Optional

from fastapi.openapi.models import APIKey, APIKeyIn
from fastapi.security.base import SecurityBase
from starlette.exceptions import HTTPException
from starlette.requests import Request
from starlette.status import HTTP_403_FORBIDDEN
from typing_extensions import Annotated, Doc


class APIKeyBase(SecurityBase):
    pass


class APIKeyQuery(APIKeyBase):
    """

/// info

Note that the `TestClient` receives data that can be converted to JSON, not Pydantic models.

If you have a Pydantic model in your test and you want to send its data to the application during testing, you can use the `jsonable_encoder` described in [JSON Compatible Encoder](encoder.md){.internal-link target=_blank}.

///

#### `RequestValidationError` 🆚 `ValidationError`

/// warning

👫 📡 ℹ 👈 👆 💪 🚶 🚥 ⚫️ 🚫 ⚠ 👆 🔜.

///

`RequestValidationError` 🎧-🎓 Pydantic <a href="https://docs.pydantic.dev/latest/concepts/models/#error-handling" class="external-link" target="_blank">`ValidationError`</a>.

**FastAPI** ⚙️ ⚫️ 👈, 🚥 👆 ⚙️ Pydantic 🏷 `response_model`, &amp; 👆 💽 ✔️ ❌, 👆 🔜 👀 ❌ 👆 🕹.

Это технические детали, которые можно пропустить, если они не важны для вас сейчас.

///

`RequestValidationError` является подклассом Pydantic <a href="https://docs.pydantic.dev/latest/concepts/models/#error-handling" class="external-link" target="_blank">`ValidationError`</a>.

from sqlmodel.main import default_registry

from tests.utils import needs_py39, needs_py310


def clear_sqlmodel():
    # Clear the tables in the metadata for the default base model
    SQLModel.metadata.clear()
    # Clear the Models associated with the registry, to avoid warnings
    default_registry.dispose()


@pytest.fixture(
    name="client",
    params=[
        "tutorial002",