return item

    @app.get("/items/")
    def read_items() -> list[Item]:
        return [
            Item(
                name="Portal Gun",
                description="Device to travel through the multi-rick-verse",
                sub=SubItem(subname="subname"),
            ),
            Item(name="Plumbus"),
        ]

    @app.post("/with-computed-field/")
    def create_with_computed_field(

@app.post("/items/")
def create_item(item: Item):
    return item


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),

Et comme la plupart du temps d'exécution est pris par du "vrai" travail (et non de l'attente), et que le travail dans un ordinateur est fait par un <abbr title="Central Processing Unit">CPU</abbr>, ce sont des problèmes dits "CPU bound".

---

Des exemples communs d'opérations "CPU bounds" sont les procédés qui requièrent des traitements mathématiques complexes.

Par exemple :

utilisez.

Vous pouvez **déployer un serveur** vous-même en utilisant une combinaison d'outils, vous pouvez utiliser un **service
cloud** qui fait une partie du travail pour vous, ou encore d'autres options possibles.

Je vais vous montrer certains des principaux concepts que vous devriez probablement avoir à l'esprit lors du déploiement

    /**
     * When potential deadlock is detected, this policy results in the throwing of the {@code
     * PotentialDeadlockException} indicating the potential deadlock, which includes stack traces
     * illustrating the cycle in lock acquisition order.
     */
    THROW {
      @Override
      public void handlePotentialDeadlock(PotentialDeadlockException e) {
        throw e;
      }
    },

    response = client.get("/items/")
    assert response.status_code == 200, response.text
    assert response.json() == [
        {
            "name": "Portal Gun",
            "description": "Device to travel through the multi-rick-verse",
        },
        {"name": "Plumbus", "description": None},
    ]


def test_openapi_schema(client: TestClient) -> None:
    response = client.get("/openapi.json")

Mas aqui está a parte divertida. ✨

A maneira "oficial" de acessar a aplicação seria através do proxy com o prefixo de path que definimos. Então, como esperaríamos, se você tentar a interface de documentação servida diretamente pelo Uvicorn, sem o prefixo de path no URL, ela não funcionará, porque espera ser acessada através do proxy.

     * The username of the user who last updated this label type.
     * Used for audit trail purposes to track who made changes.
     */
    @Size(max = 1000)
    public String updatedBy;

    /**
     * The timestamp when this label type was last updated.
     * Stored as a long value representing milliseconds since epoch.
     * Used for audit trail and concurrency control.
     */
    @ValidateTypeFailure
    public Long updatedTime;

    /**
     * The username of the user who last updated this role.
     * Used for audit trail purposes to track who made changes.
     */
    @Size(max = 1000)
    public String updatedBy;

    /**
     * The timestamp when this role was last updated.
     * Stored as a long value representing milliseconds since epoch.
     * Used for audit trail and concurrency control.
     */
    @ValidateTypeFailure
    public Long updatedTime;

### Requests simples { #simple-requests }

Cualquier request con un header `Origin`. En este caso, el middleware pasará el request a través de lo normal, pero incluirá los headers CORS adecuados en el response.

## Más info { #more-info }