{* ../../docs_src/metadata/tutorial001.py hl[3:16,19:32] *}

/// tip | Tipp

Sie können Markdown in das Feld `description` schreiben und es wird in der Ausgabe gerendert.

///

Mit dieser Konfiguration würde die automatische API-Dokumentation wie folgt aussehen:

<img src="/img/tutorial/metadata/image01.png">

## Lizenz-ID

                } else {
                    message += " from local repository";
                }
                getLogger().debug(message);
            } else {
                // Locally installed file is newer, don't use the resolved version
                getLogger().debug(artifact.getArtifactId() + ": using locally installed snapshot");
            }
        }
        return version;
    }

Der Teil mit `Union[str, None]` erlaubt es Ihrem Editor, Sie besser zu unterstützen, aber er sagt FastAPI nicht, dass dieser Parameter optional ist.

///

Jetzt können wir `Query` weitere Parameter übergeben. Fangen wir mit dem `max_length` Parameter an, der auf Strings angewendet wird:

```Python

{* ../../docs_src/body/tutorial001_py310.py hl[16] *}

... und deklarieren Sie seinen Typ als das Modell, welches Sie erstellt haben, `Item`.

## Resultate

Mit nur dieser Python-Typdeklaration, wird **FastAPI**:

* Den Requestbody als JSON lesen.
* Die entsprechenden Typen konvertieren (falls nötig).
* Diese Daten validieren.

	#   sessionToken: SESSION-TOKEN # Available when rotating credentials are used

  # optional flags based filtering criteria
  # for all source objects
  flags:
	filter:
	  newerThan: "7d" # match objects newer than this value (e.g. 7d10h31s)
	  olderThan: "7d" # match objects older than this value (e.g. 7d10h31s)
	  createdAfter: "date" # match objects created after "date"
	  createdBefore: "date" # match objects created before "date"

 * be an empty line at the end if the contents are terminated with a line separator.
 *
 * <p>Any {@link ByteSource} containing text encoded with a specific {@linkplain Charset character
 * encoding} may be viewed as a {@code CharSource} using {@link ByteSource#asCharSource(Charset)}.
 *
 * <p><b>Note:</b> In general, {@code CharSource} is intended to be used for "file-like" sources
 * that provide readers that are:
 *
 * <ul>

 * be an empty line at the end if the contents are terminated with a line separator.
 *
 * <p>Any {@link ByteSource} containing text encoded with a specific {@linkplain Charset character
 * encoding} may be viewed as a {@code CharSource} using {@link ByteSource#asCharSource(Charset)}.
 *
 * <p><b>Note:</b> In general, {@code CharSource} is intended to be used for "file-like" sources
 * that provide readers that are:
 *
 * <ul>

**FastAPI** proporciona las mismas `starlette.responses` como `fastapi.responses` solo como una conveniencia para ti, el desarrollador. Pero la mayoría de los responses disponibles vienen directamente de Starlette.

///

### Subidas de Múltiples Archivos con Metadatos Adicionales

Y de la misma manera que antes, puedes usar `File()` para establecer parámetros adicionales, incluso para `UploadFile`:

	fmt.Println(buf2.Cap())
	// Output:
	// 10
	// 10
}

func ExampleBuffer_Grow() {
	var b bytes.Buffer
	b.Grow(64)
	bb := b.Bytes()
	b.Write([]byte("64 bytes or fewer"))
	fmt.Printf("%q", bb[:b.Len()])
	// Output: "64 bytes or fewer"
}

func ExampleBuffer_Len() {
	var b bytes.Buffer
	b.Grow(64)
	b.Write([]byte("abcde"))
	fmt.Printf("%d", b.Len())
	// Output: 5
}

func ExampleBuffer_Next() {

scala> counts.saveAsTextFile("s3a://testbucket/wordcount")
```

Use one of the following approaches to view job output:

View output in the Scala shell:

```
scala> counts.count()
364
```

To view the output from MinIO exit the Scala shell. View WordCount job status:

```
hadoop fs -ls s3a://testbucket/wordcount
```

The output should be similar to the following: