* JSON.
    * Path parameters.
    * Query parameters.
    * Cookies.
    * Headers.
    * Forms.
    * Files.
* <dfn title="also known as: serialization, parsing, marshalling">Conversion</dfn> of output data: converting from Python data and types to network data (as JSON):
    * Convert Python types (`str`, `int`, `float`, `bool`, `list`, etc).
    * `datetime` objects.
    * `UUID` objects.
    * Database models.

Sie erhalten eine Response wie:

```json
{
  "description": "Some data",
  "content": "hello"
}
```

## Pydantic `bytes` für Ausgabedaten { #pydantic-bytes-for-output-data }

Sie können in der Modellkonfiguration für Ausgabedaten auch `bytes`-Felder mit `ser_json_bytes` verwenden; Pydantic wird die Bytes bei der Erzeugung der JSON-Response als base64 *serialisieren*.

Recibirás una response como:

```json
{
  "description": "Some data",
  "content": "hello"
}
```

## Pydantic `bytes` para datos de salida { #pydantic-bytes-for-output-data }

También puedes usar campos `bytes` con `ser_json_bytes` en la configuración del modelo para datos de salida, y Pydantic serializará los bytes como base64 al generar la response JSON.

			paxHdrs[paxSize] = strconv.FormatInt(hdr.Size, 10)
			delete(paxHdrs, paxPath) // Recorded by paxGNUSparseName
		}
	*/
	_ = realSize

	// Write PAX records to the output.
	isGlobal := hdr.Typeflag == TypeXGlobalHeader
	if len(paxHdrs) > 0 || isGlobal {
		// Write each record to a buffer.
		var buf strings.Builder
		// Sort keys for deterministic ordering.

        processor.started(testDesciptorInternal, testStartEvent)
        then:
        1 * delegate.started(testDesciptorInternal, testStartEvent)

        when:
        processor.output(testId, testOutputEvent)
        then:
        1 * delegate.output(testId, testOutputEvent)

        when:
        processor.completed(testId, testCompleteEvent)
        then:
        1 * delegate.completed(testId, testCompleteEvent)
    }

Vous recevrez une réponse comme :

```json
{
  "description": "Some data",
  "content": "hello"
}
```

## Pydantic `bytes` pour les données de sortie { #pydantic-bytes-for-output-data }

Vous pouvez également utiliser des champs `bytes` avec `ser_json_bytes` dans la configuration du modèle pour les données de sortie ; Pydantic sérialisera alors les octets en base64 lors de la génération de la réponse JSON.

- Fix a panic when using invalid output format in kubectl create secret command ([#107346](https://github.com/kubernetes/kubernetes/pull/107346), [@rikatz](https://github.com/rikatz)) [SIG CLI]

   *
   * <p>Like the {@link #toArray()} method, this method acts as bridge between array-based and
   * collection-based APIs. Further, this method allows precise control over the runtime type of the
   * output array, and may, under certain circumstances, be used to save allocation costs.
   *
   * <p>Suppose {@code x} is a queue known to contain only strings. The following code can be used

///

## Bir output modeli ekleyin { #add-an-output-model }

Bunun yerine, plaintext password içeren bir input modeli ve password’ü içermeyen bir output modeli oluşturabiliriz:

{* ../../docs_src/response_model/tutorial003_py310.py hl[9,11,16] *}

### CLI
- Fixed kubectl endpointslice output for get requests ([#82603](https://github.com/kubernetes/kubernetes/pull/82603), [@robscott](https://github.com/robscott))