// similar attributes and is identified by a pair of strings: the name of the FlowSchema and a "flow distinguisher".
message FlowSchema {
  // `metadata` is the standard object's metadata.
  // More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadata
  // +optional
  optional k8s.io.apimachinery.pkg.apis.meta.v1.ObjectMeta metadata = 1;

                    return Lists.newArrayList(Sets.newTreeSet(insertionOrder));
                  }
                })
            .named("ForwardingSortedSet[SafeTreeSet] with standard implementations")
            .withFeatures(
                CollectionSize.ANY,
                CollectionFeature.KNOWN_ORDER,
                CollectionFeature.GENERAL_PURPOSE)
            .createTestSuite());

# GraphQL

As **FastAPI** is based on the **ASGI** standard, it's very easy to integrate any **GraphQL** library also compatible with ASGI.

You can combine normal FastAPI *path operations* with GraphQL on the same application.

/// tip

**GraphQL** solves some very specific use cases.

It has **advantages** and **disadvantages** when compared to common **web APIs**.

		APICode: "kms:NotSupported",
		Err:     "requested functionality is not supported",
	}
)

// Error is a KMS error that can be translated into an S3 API error.
//
// It does not implement the standard error Unwrap interface for
// better error log messages.
type Error struct {
	Code    int    // The HTTP status code returned to the client
	APICode string // The API error code identifying the error

		"Invalid storage class value",
		"Please check the value",
		`MINIO_STORAGE_CLASS_STANDARD: Format "EC:<Default_Parity_Standard_Class>" (e.g. "EC:3"). This sets the number of parity drives for MinIO server in Standard mode. Objects are stored in Standard mode, if storage class is not defined in Put request

Isso é provavelmente o que você faria quando você quisesse lançar sua aplicação em produção:

```
pip install fastapi
```

Também instale o `uvicorn` para funcionar como servidor:

```
pip install "uvicorn[standard]"
```

E o mesmo para cada dependência opcional que você quiser usar.

///

## Guia Avançado de Usuário

Há também um **Guia Avançado de Usuário** que você pode ler após esse **Tutorial - Guia de Usuário**.

Falcon est un autre framework Python haute performance, il est conçu pour être minimal, et est utilisé comme fondation pour d'autres frameworks comme Hug.

Il utilise le standard précédent pour les frameworks web Python (WSGI) qui est synchrone, donc il ne peut pas gérer les WebSockets et d'autres cas d'utilisation. Néanmoins, il offre de très bonnes performances.

     * {@code <groupId>:<artifactId>[:<extension>[:<classifier>]]:<version>}
     *
     * @param session the session.
     * @param coordinatesString the string having "standard" coordinates.
     * @return an {@code ArtifactCoordinates}, never {@code null}
     * @throws IllegalArgumentException if {@code session} is null or invalid
     */
    @Nonnull

./mc mb sitea/testbucket

./mc version enable sitea/testbucket

./mc put --quiet README.md sitea/testbucket/file
etag1=$(./mc cat sitea/testbucket/file | md5sum --tag | awk {'print $4'})

./mc cp --quiet --storage-class "STANDARD" sitea/testbucket/file sitea/testbucket/file
etag2=$(./mc cat sitea/testbucket/file | md5sum --tag | awk {'print $4'})
if [ $etag1 != $etag2 ]; then
	echo "expected $etag1, got $etag2"
	exit 1
fi

echo "SUCCESS:"

   * R*R)} of the population standard deviation of {@code y}, where {@code R} is the Pearson's
   * correlation coefficient (as given by {@link #pearsonsCorrelationCoefficient()}).
   *
   * <p>The corresponding root-mean-square error in {@code x} as a function of {@code y} is a
   * fraction {@code sqrt(1/(R*R) - 1)} of the population standard deviation of {@code x}. This fit