Source          string // Contains line, function and filename requesting the lock.
	Group           bool   // indicates if it was a group lock.
	Owner           string // Owner represents the UUID of the owner who originally requested the lock.
	Quorum          int    // Quorum represents the quorum required for this lock to be active.
	idx             int    `msg:"-"` // index of the lock in the lockMap.
}

          .put(TimeUnit.class, SECONDS)
          .put(Charset.class, UTF_8)
          .put(Currency.class, Currency.getInstance(Locale.US))
          .put(Locale.class, Locale.US)
          .put(UUID.class, UUID.randomUUID())
          // common.base
          .put(CharMatcher.class, CharMatcher.none())
          .put(Joiner.class, Joiner.on(','))
          .put(Splitter.class, Splitter.on(','))

Por ejemplo, no puedes poner un modelo de Pydantic en un `JSONResponse` sin primero convertirlo a un `dict` con todos los tipos de datos (como `datetime`, `UUID`, etc.) convertidos a tipos compatibles con JSON.

Para esos casos, puedes usar el `jsonable_encoder` para convertir tus datos antes de pasarlos a un response:

{* ../../docs_src/response_directly/tutorial001.py hl[6:7,21:22] *}

Sie können beispielsweise kein Pydantic-Modell in eine `JSONResponse` einfügen, ohne es zuvor in ein `dict` zu konvertieren, bei dem alle Datentypen (wie `datetime`, `UUID`, usw.) in JSON-kompatible Typen konvertiert wurden.

In diesen Fällen können Sie den `jsonable_encoder` verwenden, um Ihre Daten zu konvertieren, bevor Sie sie an eine Response übergeben:

	}

	// After heal the meta file should be as expected.
	if !fileInfoPreHeal.Equals(fileInfoPostHeal) {
		t.Fatal("HealObject failed")
	}

	uuid, _ := uuid2.NewRandom()
	for _, drive := range fsDirs {
		dir := path.Join(drive, bucket, object, uuid.String())
		err = os.MkdirAll(dir, os.ModePerm)
		if err != nil {
			t.Fatal(err)
		}
		err = os.WriteFile(pathJoin(dir, "part.1"), []byte("some data"), os.ModePerm)

								Inline []byte `json:"x-minio-internal-inline-data"`
							}
						}
					}
					var ei erasureInfo
					if err := json.Unmarshal(buf.Bytes(), &ei); err == nil && ei.V2Obj != nil {
						verID := uuid.UUID(header.VersionID).String()
						if verID == "00000000-0000-0000-0000-000000000000" {
							// If the version ID is all zeros, use the signature as version ID.
							verID = fmt.Sprintf("null/%08x", header.Signature)

			uploadIDPath := pathJoin(shaDir, uploadIDDir)
			var modTime time.Time
			// Upload IDs are of the form base64_url(<UUID>x<UnixNano>), we can extract the time from the UUID.
			if b64, err := base64.RawURLEncoding.DecodeString(uploadIDDir); err == nil {
				if split := strings.Split(string(b64), "x"); len(split) == 2 {
					t, err := strconv.ParseInt(split[1], 10, 64)

그리고 지금까지와 같은 기능들을 여전히 사용할 수 있습니다.

* 훌륭한 편집기 지원.
* 들어오는 요청의 데이터 변환.
* 응답 데이터의 데이터 변환.
* 데이터 검증.
* 자동 어노테이션과 문서화.

## 다른 데이터 자료형

아래의 추가적인 데이터 자료형을 사용할 수 있습니다:

* `UUID`:
    * 표준 "범용 고유 식별자"로, 많은 데이터베이스와 시스템에서 ID로 사용됩니다.
    * 요청과 응답에서 `str`로 표현됩니다.
* `datetime.datetime`:
    * 파이썬의 `datetime.datetime`.
    * 요청과 응답에서 `2008-09-15T15:53:00+05:00`와 같은 ISO 8601 형식의 `str`로 표현됩니다.

Par exemple, vous ne pouvez pas mettre un modèle Pydantic dans une `JSONResponse` sans d'abord le convertir en un `dict` avec tous les types de données (comme `datetime`, `UUID`, etc.) convertis en types compatibles avec JSON.

Pour ces cas, vous pouvez spécifier un appel à `jsonable_encoder` pour convertir vos données avant de les passer à une réponse :

    private val objectMapper = ObjectMapper().registerKotlinModule()
    private val buckets: Map<TestCoverage, List<BuildTypeBucket>> by lazy {
        val uuidToTestCoverage = model.stages.flatMap { it.functionalTests }.associateBy { it.uuid }
        val testCoverageAndBuckets: List<Map<String, Any>> = objectMapper.readValue(testBucketsJson.readText())
        testCoverageAndBuckets.associate { testCoverageAndBucket ->