monkeypatch.setenv("ADMIN_EMAIL", "admin@example.com")
    from docs_src.settings.tutorial001_pv1 import app

    client = TestClient(app)
    response = client.get("/info")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "app_name": "Awesome API",
        "admin_email": "admin@example.com",
        "items_per_user": 50,

    if log.is_file():
        os.remove(log)  # pragma: no cover
    response = client.post("/send-notification/foo@example.com")
    assert response.status_code == 200, response.text
    assert response.json() == {"message": "Notification sent in the background"}
    with open("./log.txt") as f:

In this example, when the client requests an item by an ID that doesn't exist, raise an exception with a status code of `404`:

```Python hl_lines="11"
{!../../../docs_src/handling_errors/tutorial001.py!}
```

### The resulting response

## Use Case

Let's start with an example **use case** and then see how to solve it with this.

Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖

  optional k8s.io.apimachinery.pkg.apis.meta.v1.GroupVersionKind kind = 2;

  // Resource is the fully-qualified resource being requested (for example, v1.pods)
  optional k8s.io.apimachinery.pkg.apis.meta.v1.GroupVersionResource resource = 3;

  // SubResource is the subresource being requested, if any (for example, "status" or "scale")
  // +optional

from ...utils import needs_py310


@pytest.fixture(name="client")
def get_client():
    from docs_src.schema_extra_example.tutorial004_an_py310 import app

    client = TestClient(app)
    return client


# Test required and embedded body parameters with no bodies sent
@needs_py310
def test_post_body_example(client: TestClient):
    response = client.put(
        "/items/5",
        json={
            "name": "Foo",

1. The id_token is an identifier that is hard to guess. For example, a randomly generated string of sufficient length, that the server handling the protected resource can use to lookup the associated authorization information.
2. The id_token self-contains the authorization information in a manner that can be verified. For example, by encoding authorization information along with a signature into the token.

* Convert the copied model to something that can be stored in your DB (for example, using the `jsonable_encoder`).
    * This is comparable to using the model's `.model_dump()` method again, but it makes sure (and converts) the values to data types that can be converted to JSON, for example, `datetime` to `str`.
* Save the data to your DB.
* Return the updated model.

=== "Python 3.10+"

 * shared resources.
 *
 * @param <K> the most general type of keys this listener can listen for; for example {@code Object}
 *     if any key is acceptable
 * @param <V> the most general type of values this listener can listen for; for example {@code
 *     Object} if any key is acceptable
 * @author Charles Fry
 * @since 10.0
 */
@GwtCompatible
@ElementTypesAreNonnullByDefault

For example, if you need to store it in a database.

For that, **FastAPI** provides a `jsonable_encoder()` function.

## Using the `jsonable_encoder`

Let's imagine that you have a database `fake_db` that only receives JSON compatible data.

For example, it doesn't receive `datetime` objects, as those are not compatible with JSON.