Muchos, muchos usuarios, pero el servidor está esperando 🕙 el envío de las peticiones ya que su conexión no es buena.

Y luego esperando 🕙 nuevamente a que las respuestas retornen.

Esta "espera" 🕙 se mide en microsegundos, pero aun así, sumando todo, al final es mucha espera.

Es por eso que tiene mucho sentido usar código asíncrono ⏸🔀⏯ para las API web.

* Muchas características extra (gracias a Starlette) como:
    * **WebSockets**
    * **GraphQL**
    * pruebas extremadamente fáciles con HTTPX y `pytest`
    * **CORS**
    * **Cookie Sessions**
    * ...y mucho más.

## Rendimiento

pkg debug/macho, const FlagBindsToWeak uint32
pkg debug/macho, const FlagCanonical = 16384
pkg debug/macho, const FlagCanonical uint32
pkg debug/macho, const FlagDeadStrippableDylib = 4194304
pkg debug/macho, const FlagDeadStrippableDylib uint32
pkg debug/macho, const FlagDyldLink = 4
pkg debug/macho, const FlagDyldLink uint32
pkg debug/macho, const FlagForceFlat = 256
pkg debug/macho, const FlagForceFlat uint32

   *
   * <p><b>{@code Stream} equivalent:</b> {@code stream.filter(predicate).findFirst()}.
   */
  public final Optional<@NonNull E> firstMatch(Predicate<? super E> predicate) {
    // Unsafe, but we can't do much about it now.
    return Iterables.<@NonNull E>tryFind((Iterable<@NonNull E>) getDelegate(), predicate);
  }

  /**
   * Returns a fluent iterable that applies {@code function} to each element of this fluent

Esto también significa que en muchos casos puedes pasar el mismo objeto que obtuviste de un request **directamente a la base de datos**, dado que todo es validado automáticamente.

Lo mismo aplica para el sentido contrario. En muchos casos puedes pasar el objeto que obtienes de la base de datos **directamente al cliente**.

Having the return model ensure that a value is always available and always `int` (not `None`) is very useful for the API clients, they can write much simpler code having this certainty.

Also, **automatically generated clients** will have simpler interfaces, so that the developers communicating with your API can have a much better time working with your API. 😎

///

* Ensure traffic between mesh workloads is securely encrypted with an Istio identity.
* Be lightweight enough to not limit adoption.
  * This puts a much tighter budget on CPU, memory, latency, and throughput requirements than traditional Istio sidecars.

Ztunnel was not designed to be a feature-rich data plane.

    assert response.status_code == 200, response.text
    assert response.json() == data


def test_model_with_tuple_invalid():
    data = {"items": [["foo", "bar"], ["baz", "whatelse", "too", "much"]]}
    response = client.post("/model-with-tuple/", json=data)
    assert response.status_code == 422, response.text

    data = {"items": [["foo", "bar"], ["baz"]]}
    response = client.post("/model-with-tuple/", json=data)

### Summary

I used to say I didn't like history that much... and look at me now giving "tech history" lessons. 😅

      // timed out. e.g. if we weren't event able to grab the lock within the timeout we would never
      // even check the guard. I don't think we care too much about this use case but it could lead
      // to a confusing error message.
      throw new TimeoutException("Timed out waiting for " + this + " to reach the RUNNING state.");
    }
  }

  @Override