type BatchKeyRotateFilter struct {
	NewerThan     time.Duration `yaml:"newerThan,omitempty" json:"newerThan"`
	OlderThan     time.Duration `yaml:"olderThan,omitempty" json:"olderThan"`
	CreatedAfter  time.Time     `yaml:"createdAfter,omitempty" json:"createdAfter"`
	CreatedBefore time.Time     `yaml:"createdBefore,omitempty" json:"createdBefore"`
	Tags          []BatchJobKV  `yaml:"tags,omitempty" json:"tags"`

docker pull docker.io/minio/mint:edge

docker-compose -f minio-${MODE}.yaml up -d
sleep 1m

docker system prune -f || true
docker volume prune -f || true
docker volume rm $(docker volume ls -q -f dangling=true) || true

# Stop two nodes, one of each pool, to check that all S3 calls work while quorum is still there
[ "${MODE}" == "pools" ] && docker-compose -f minio-${MODE}.yaml stop minio2

	}{
		{
			config:      "testdata/config/1.yaml",
			expectedErr: false,
			hash:        "hash:02bf70285dc71f76",
		},
		{
			config:      "testdata/config/2.yaml",
			expectedErr: false,
			hash:        "hash:676d2da00f71f205",
		},
		{
			config:      "testdata/config/invalid.yaml",
			expectedErr: true,
		},
		{
			config:      "testdata/config/invalid-types.yaml",
			expectedErr: true,
		},
		{

    delay: 500ms # least amount of delay between each retry
`
	var job BatchJobRequest
	err := yaml.Unmarshal([]byte(expireYaml), &job)
	if err != nil {
		t.Fatal("Failed to parse batch-job-expire yaml", err)
	}
	if !slices.Equal(job.Expire.Prefix.F(), []string{"myprefix"}) {
		t.Fatal("Failed to parse batch-job-expire yaml")
	}

	multiPrefixExpireYaml := `
expire: # Expire objects that match a condition
  apiVersion: v1

{* ../../docs_src/path_operation_advanced_configuration/tutorial007.py hl[17:22,24] *}

Néanmoins, bien que nous n'utilisions pas la fonctionnalité par défaut, nous utilisons toujours un modèle Pydantic pour générer manuellement le schéma JSON pour les données que nous souhaitons recevoir en YAML.

Dann verwenden wir den Request direkt und extrahieren den Body als `bytes`. Das bedeutet, dass FastAPI nicht einmal versucht, den Request-Payload als JSON zu parsen.

Und dann parsen wir in unserem Code diesen YAML-Inhalt direkt und verwenden dann wieder dasselbe Pydantic-Modell, um den YAML-Inhalt zu validieren:

//// tab | Pydantic v2

## 2. Run Distributed MinIO on Docker Compose

             docker-compose -f ${GITHUB_WORKSPACE}/.github/workflows/mint/minio-${mode}.yaml rm || true
          done

          docker-compose -f ${GITHUB_WORKSPACE}/.github/workflows/multipart/docker-compose-site1.yaml rm -s -f || true
          docker-compose -f ${GITHUB_WORKSPACE}/.github/workflows/multipart/docker-compose-site2.yaml rm -s -f || true

Luego usamos el request directamente, y extraemos el cuerpo como `bytes`. Esto significa que FastAPI ni siquiera intentará parsear la carga útil del request como JSON.

Y luego en nuestro código, parseamos ese contenido YAML directamente, y nuevamente estamos usando el mismo modelo Pydantic para validar el contenido YAML:

//// tab | Pydantic v2

        OutputStream jsonOutput = SearchEngineUtil.getXContentBuilderOutputStream(callback, XContentType.JSON);
        assertNotNull(jsonOutput);

        // Test with YAML
        OutputStream yamlOutput = SearchEngineUtil.getXContentBuilderOutputStream(callback, XContentType.YAML);
        assertNotNull(yamlOutput);
    }

    public void test_getXContentOutputStream_success() {
        ToXContent xContent = new ToXContent() {