```Python hl_lines="12"
{!../../../docs_src/body_nested_models/tutorial001.py!}
```

これにより、各項目の型は宣言されていませんが、`tags`はある項目のリストになります。

## タイプパラメータを持つリストのフィールド

しかし、Pythonには型や「タイプパラメータ」を使ってリストを宣言する方法があります:

### typingの`List`をインポート

まず、Pythonの標準の`typing`モジュールから`List`をインポートします:

```Python hl_lines="1"
{!../../../docs_src/body_nested_models/tutorial002.py!}
```

### タイプパラメータを持つ`List`の宣言

Moustapha Sall <******@****.***> 1704810933 -0500

    pass


def test_invalid_response_model_raises():
    with pytest.raises(FastAPIError):
        app = FastAPI()

        @app.get("/", response_model=NonPydanticModel)
        def read_root():
            pass  # pragma: nocover


def test_invalid_response_model_sub_type_raises():
    with pytest.raises(FastAPIError):
        app = FastAPI()

        @app.get("/", response_model=List[NonPydanticModel])

@app.get(
    "/items/coerce-exclude-unset",
    response_model=Item,
    response_model_exclude_unset=True,
)
def get_coerce_exclude_unset():
    return Item(aliased_name="coerce", price="1.0")


@app.get(
    "/items/validlist-exclude-unset",
    response_model=List[Item],
    response_model_exclude_unset=True,
)
def get_validlist_exclude_unset():
    return [

# Build state model

The Gradle daemon tracks state for various elements. These are arranged in a hierarchy:

```mermaid
  graph TD

  process["build process"]
  
  session["build session"]
  process --> session
  
  build_tree["build tree"]
  session --> build_tree
  
  build1["root build"]
  build_tree --> build1
  
  project1["root project"]
  build1 --> project1
  
  project2["project"]
  build1 --> project2

              <velocityBasedir>${project.basedir}/../../src/mdo</velocityBasedir>
              <version>2.0.0</version>
              <models>
                <model>src/main/mdo/plugin.mdo</model>
              </models>
              <templates>
                <template>model.vm</template>
              </templates>
              <params>
                <param>packageModelV4=org.apache.maven.api.plugin.descriptor</param>

under the License.
-->

<project>
    <!-- once we move past supporting modelVersion 4.0.0 we should update this version -->
    <modelVersion>3.9.9</modelVersion>
    <groupId>tests.project</groupId>
    <artifactId>past-model-version</artifactId>
    <version>1</version>

        "info": {"title": "FastAPI", "version": "0.1.0"},
        "paths": {
            "/models/{model_name}": {
                "get": {
                    "summary": "Get Model",
                    "operationId": "get_model_models__model_name__get",
                    "parameters": [
                        {
                            "required": True,

## Create the Pydantic models

Now let's check the file `sql_app/schemas.py`.

!!! tip
    To avoid confusion between the SQLAlchemy *models* and the Pydantic *models*, we will have the file `models.py` with the SQLAlchemy models, and the file `schemas.py` with the Pydantic models.

    These Pydantic models define more or less a "schema" (a valid data shape).

                        },
                    },
                }
            },
            "/tuple-of-models/": {
                "post": {
                    "summary": "Post Tuple Of Models",
                    "operationId": "post_tuple_of_models_tuple_of_models__post",
                    "requestBody": {
                        "content": {
                            "application/json": {