// XferStats has transfer stats for replication
type XferStats struct {
	Curr    float64          `json:"currRate" msg:"cr"`
	Avg     float64          `json:"avgRate" msg:"av"`
	Peak    float64          `json:"peakRate" msg:"p"`
	N       int64            `json:"n" msg:"n"`
	measure *rateMeasurement `json:"-"`
	sma     *SMA             `json:"-"`
}

// Clone returns a copy of XferStats
func (rx *XferStats) Clone() *XferStats {

**FastAPI** prendra le modèle Pydantic à partir de là, générera le `JSON Schema` et le placera au bon endroit.

Le bon endroit est :

* Dans la clé `content`, qui a pour valeur un autre objet JSON (`dict`) qui contient :
    * Une clé avec le type de support, par ex. `application/json`, qui contient comme valeur un autre objet JSON, qui contient :
        * Une clé `schema`, qui a pour valeur le schéma JSON du modèle, voici le bon endroit.

        if (testToken != null) {
            return;
        }
        given().contentType("application/json").delete(getEsUrl() + "/fess_config.access_token/_doc/" + DEFAULT_TEST_TOKEN_ID);
    }

    public static void refresh() {
        given().contentType("application/json").post(getEsUrl() + "/_refresh");
    }

    public static String getFessUrl() {

		path, prefix, suffix string
		expected             string
	}{
		{"config/iam/groups/foo.json", "config/iam/groups/", ".json", "foo"},
		{"config/iam/groups/./foo.json", "config/iam/groups/", ".json", "foo"},
		{"config/iam/groups/foo/config.json", "config/iam/groups/", "/config.json", "foo"},
		{"config/iam/groups/foo/config.json", "config/iam/groups/", "config.json", "foo"},
	}
	for i, test := range specs {

And you could do this even if the data type in the request is not JSON.

For example, in this application we don't use FastAPI's integrated functionality to extract the JSON Schema from Pydantic models nor the automatic validation for JSON. In fact, we are declaring the request content type as YAML, not JSON:

//// tab | Pydantic v2

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

						if err != nil {
							return err
						}
						// Quote string...
						b, _ := json.Marshal(file.Name)
						b2, err := decode(r, file.Name)
						if err != nil {
							return err
						}
						var tmp map[string]any
						if err := json.Unmarshal(b2, &tmp); err == nil {
							if b3, err := json.Marshal(tmp); err == nil {
								b2 = b3
							}
						}

type StringsSlice []string

func (l StringsSlice) Value() (driver.Value, error) {
	bytes, err := json.Marshal(l)
	return string(bytes), err
}

func (l *StringsSlice) Scan(input interface{}) error {
	switch value := input.(type) {
	case string:
		return json.Unmarshal([]byte(value), l)
	case []byte:
		return json.Unmarshal(value, l)
	default:
		return errors.New("not supported")
	}
}

  private val MOSHI =
    Moshi
      .Builder()
      .add(
        object : Any() {
          @ToJson fun byteStringToJson(byteString: ByteString) = byteString.hex()

          @FromJson fun byteStringFromJson(json: String) = json.decodeHex()
        },
      ).add(KotlinJsonAdapterFactory())
      .build()
  private val STORY_JSON_ADAPTER = MOSHI.adapter(Story::class.java)

  private val fileSystem = FileSystem.SYSTEM

Entonces, el frontend (que se ejecuta en el navegador) trataría de alcanzar `/openapi.json` y no podría obtener el esquema de OpenAPI.

Porque tenemos un proxy con un prefijo de path de `/api/v1` para nuestra aplicación, el frontend necesita obtener el esquema de OpenAPI en `/api/v1/openapi.json`.

```mermaid
graph LR

browser("Navegador")

            logAsText(entry); // Fallback to text
        } finally {
            returnStringBuilder(json);
        }
    }

    private void buildJsonEntry(StringBuilder json, AuditEntry entry) {
        json.append("{");
        json.append("\"timestamp\":\"").append(escapeJson(entry.timestamp.toString())).append("\",");