## Pydantic

Toda la validación de datos se realiza internamente con <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a>, así que obtienes todos los beneficios de esta. Y sabes que estás en buenas manos.

Puedes usar las mismas declaraciones de tipo con `str`, `float`, `bool` y muchos otros tipos de datos complejos.

        These advantages can take
        [many forms](https://github.com/google/guava/wiki/PhilosophyExplained#utility), but taking
        the time to discuss them in detail will make it much clearer why this feature should be
        added to Guava.


        Please fill out the following fields to give us a better understanding of your proposed
        feature and its potential value for other Guava users.

title: "import/path: issue title"

body:
  - type: markdown
    attributes:
      value: |
        Thanks for helping us improve! 🙏 Please answer these questions and provide as much information as possible about your problem.

  - type: input
    id: go-version
    attributes:
      label: Go version
      description: |
        What version of Go are you using (`go version`)?

---

"_Honestamente, lo que has construido parece súper sólido y pulido. En muchos aspectos, es lo que quería que **Hug** fuera; es realmente inspirador ver a alguien construir eso._"

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. 😎

///

		// Unlock the 1st lock; ref=1 after this line
		nsLk.unlock("volume", "path", false)

		// Taking another lockMapMutex here allows queuing up additional lockers. This should
		// not be required but makes reproduction much easier.
		nsLk.lockMapMutex.Lock()

		// lk3 blocks.
		lk3ch := make(chan bool)
		go func() {
			lk3ch <- nsLk.lock(ctx, "volume", "path", "source", "opsID", false, 0)
		}()

		// lk4, blocks.

   */
  @JvmField val minimumConcurrentCalls: Int = 0,
  /** How long to wait to retry pre-emptive connection attempts that fail. */
  @JvmField val backoffDelayMillis: Long = 60 * 1000,
  /** How much jitter to introduce in connection retry backoff delays */
  @JvmField val backoffJitterMillis: Int = 100,

pkg debug/macho, type LoadCmd uint32
pkg debug/macho, type Nlist32 struct
pkg debug/macho, type Nlist32 struct, Desc uint16
pkg debug/macho, type Nlist32 struct, Name uint32
pkg debug/macho, type Nlist32 struct, Sect uint8
pkg debug/macho, type Nlist32 struct, Type uint8
pkg debug/macho, type Nlist32 struct, Value uint32
pkg debug/macho, type Nlist64 struct
pkg debug/macho, type Nlist64 struct, Desc uint16

/// note | Nota

`jsonable_encoder` es utilizado internamente por **FastAPI** para convertir datos. Pero es útil en muchos otros escenarios.

///

Y cuando devuelves una `Response`, **FastAPI** la pasará directamente.

No hará ninguna conversión de datos con los modelos de Pydantic, no convertirá los contenidos a ningún tipo, etc.

Esto te da mucha flexibilidad. Puedes devolver cualquier tipo de datos, sobrescribir cualquier declaración o validación de datos, etc.

## Usar el `jsonable_encoder` en una `Response`