* O arquivo `app/routers/items.py` está dentro de um pacote, `app/routers/`, portanto, é um "submódulo": `app.routers.items`.
* O mesmo com `app/routers/users.py`,  ele é outro submódulo: `app.routers.users`.
* Há também um subdiretório `app/internal/` com outro arquivo `__init__.py`, então ele é outro "subpacote Python":`app.internal`.
* E o arquivo `app/internal/admin.py` é outro submódulo: `app.internal.admin`.

<img src="/img/tutorial/bigger-applications/package.svg">

{!> ../../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.:

//// tab | Python 3.10+

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

////

from fastapi import FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()


class SubModel(BaseModel):
    a: Optional[str] = "foo"


class Model(BaseModel):
    x: Optional[int] = None
    sub: SubModel


class ModelSubclass(Model):
    y: int
    z: int = 0
    w: Optional[int] = None


class ModelDefaults(BaseModel):

  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)

    assert response.status_code == 200, response.text
    assert response.json() == {
        "sub_items": [{"name": "subitem", "sub_items": []}],
        "name": "item",
    }

    response = client.get("/items/recursive-submodel")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "name": "item",
        "sub_items1": [
            {
                "name": "subitem",
                "sub_items2": [

@app.get("/items/recursive", response_model=RecursiveItem)
def get_recursive():
    return {"name": "item", "sub_items": [{"name": "subitem", "sub_items": []}]}


@app.get("/items/recursive-submodel", response_model=RecursiveItemViaSubmodel)
def get_recursive_submodel():
    return {
        "name": "item",
        "sub_items1": [
            {
                "name": "subitem",
                "sub_items2": [

@app.get("/items/recursive", response_model=RecursiveItem)
def get_recursive():
    return {"name": "item", "sub_items": [{"name": "subitem", "sub_items": []}]}


@app.get("/items/recursive-submodel", response_model=RecursiveItemViaSubmodel)
def get_recursive_submodel():
    return {
        "name": "item",
        "sub_items1": [
            {
                "name": "subitem",
                "sub_items2": [

    assert response.status_code == 200, response.text
    assert response.json() == {
        "sub_items": [{"name": "subitem", "sub_items": []}],
        "name": "item",
    }

    response = client.get("/items/recursive-submodel")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "name": "item",
        "sub_items1": [
            {
                "name": "subitem",
                "sub_items2": [

                }
            },
            "/response_model_filtering_model-annotation_submodel-return_submodel": {
                "get": {
                    "summary": "Response Model Filtering Model Annotation Submodel Return Submodel",
                    "operationId": "response_model_filtering_model_annotation_submodel_return_submodel_response_model_filtering_model_annotation_submodel_return_submodel_get",
                    "responses": {

    `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