* The file `app/routers/items.py` is inside a package, `app/routers/`, so, it's a submodule: `app.routers.items`.
* The same with `app/routers/users.py`, it's another submodule: `app.routers.users`.
* There's also a subdirectory `app/internal/` with another file `__init__.py`, so it's another "Python subpackage": `app.internal`.
* And the file `app/internal/admin.py` is another submodule: `app.internal.admin`.

* Das Gleiche gilt für `app/routers/users.py`, es ist ein weiteres Submodul: `app.routers.users`.
* Es gibt auch ein Unterverzeichnis `app/internal/` mit einer weiteren Datei `__init__.py`, es handelt sich also um ein weiteres „Python-Subpackage“: `app.internal`.
* Und die Datei `app/internal/admin.py` ist ein weiteres Submodul: `app.internal.admin`.

│   │   ├── items.py     # "items" submodule, e.g. import app.routers.items
│   │   └── users.py     # "users" submodule, e.g. import app.routers.users
│   └── internal         # "internal" is a "Python subpackage"
│       ├── __init__.py  # makes "internal" a "Python subpackage"
│       └── admin.py     # "admin" submodule, e.g. import app.internal.admin
```

## `APIRouter`

    {!> ../../../docs_src/body_nested_models/tutorial005.py!}
    ```

The string will be checked to be a valid URL, and documented in JSON Schema / OpenAPI as such.

## Attributes with lists of submodels

You can also use Pydantic models as subtypes of `list`, `set`, etc.:

=== "Python 3.10+"

    ```Python hl_lines="18"
    {!> ../../../docs_src/body_nested_models/tutorial006_py310.py!}
    ```

  include(":okhttp-android")
  include(":android-test")
  include(":android-test-app")
}

enableFeaturePreview("TYPESAFE_PROJECT_ACCESSORS")

/**
 * Avoid a crash in IntelliJ triggered by Android submodules.
 *
 * ```
 * java.lang.AssertionError: Can't find built-in class kotlin.Cloneable
 *   at org.jetbrains.kotlin.builtins.KotlinBuiltIns.getBuiltInClassByFqName(KotlinBuiltIns.java:217)

    `TF_Run`, `TF_SessionRun`, `TF_SetAttrTensor` etc.
*   Renamed `tf.image.per_image_whitening()` to
    `tf.image.per_image_standardization()`
*   Move Summary protobuf constructors to `tf.summary` submodule.
*   Deprecate `histogram_summary`, `audio_summary`, `scalar_summary`,
    `image_summary`, `merge_summary`, and `merge_all_summaries`.
*   Combined `batch_*` and regular version of linear algebra and FFT ops. The

        * When a `response_model` is declared, the same `response_model` type declaration won't be used as is, it will be "cloned" to create an new one (a cloned Pydantic `Field` with all the submodels cloned as well).