That means that, clients using your API don't have to check if the value exists or not, they can **assume the field will always be there**, but just that in some cases it will have the default value of `None`.

The way to describe this in OpenAPI, is to mark that field as **required**, because it will always be there.

Because of that, the JSON Schema for a model can be different depending on if it's used for **input or output**:

### Qué es un Programa { #what-is-a-program }

La palabra **programa** se usa comúnmente para describir muchas cosas:

* El **código** que escribes, los **archivos Python**.
* El **archivo** que puede ser **ejecutado** por el sistema operativo, por ejemplo: `python`, `python.exe` o `uvicorn`.

## En savoir plus { #learn-more }

Vous pouvez en apprendre davantage sur **GraphQL** dans la [documentation officielle de GraphQL](https://graphql.org/).

TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

Note that the file `__init__.py` in the TensorFlow source code tree is actually
only a placeholder to enable test cases to run. The TensorFlow build replaces

// metrics group.
func (mg *MetricsGroup) IsBucketMetricsGroup() bool {
	return mg.bucketLoader != nil
}

// Describe - implements prometheus.Collector interface.
func (mg *MetricsGroup) Describe(ch chan<- *prometheus.Desc) {
	for _, desc := range mg.Descriptors {
		ch <- desc.toPromDesc(mg.CollectorPath.metricPrefix(), mg.ExtraLabels)
	}
}

   * value that are {@linkplain Range#isConnected connected} to this range.
   *
   * <p>The behavior of {@link #get(Comparable) get(k)} after calling this method is identical to
   * the behavior described in {@link #put(Range, Object) put(range, value)}, however the ranges
   * returned from {@link #asMapOfRanges} will be different if there were existing entries which
   * connect to the given range and value.
   *

* `description`: un `str` con una breve descripción de la etiqueta. Puede tener Markdown y se mostrará en la interfaz de documentación.
* `externalDocs`: un `dict` que describe documentación externa con:
    * `description`: un `str` con una breve descripción para la documentación externa.
    * `url` (**requerido**): un `str` con la URL para la documentación externa.

Você pode adicionar um `summary` e uma `description`:

{* ../../docs_src/path_operation_configuration/tutorial003_py310.py hl[17:18] *}

## Descrição do docstring { #description-from-docstring }

### Container Images

All container images are available as manifest lists and support the described
architectures. It is also possible to pull a specific architecture directly by
adding the "-$ARCH" suffix  to the container image name.

name | architectures
---- | -------------

- Upgrades functionality of `kubectl kustomize` as described at
  https://github.com/kubernetes-sigs/kustomize/releases/tag/kustomize%2Fv4.2.0 ([#103419](https://github.com/kubernetes/kubernetes/pull/103419), [@natasha41575](https://github.com/natasha41575)) [SIG CLI]