* governing permissions and limitations under the License.
 */
package org.codelibs.fess.mylasta.direction.sponsor;

import org.lastaflute.core.json.JsonMappingOption;
import org.lastaflute.core.json.JsonMappingOption.JsonFieldNaming;
import org.lastaflute.core.json.JsonResourceProvider;

public class FessJsonResourceProvider implements JsonResourceProvider {
    @Override
    public boolean isNullsSuppressed() {

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] *}

    public HtmlResponse index() {
        throw new UnsupportedOperationException();
    }

    /**
     * Starts a scheduled job by ID.
     *
     * @param id the ID of the scheduled job to start
     * @return JSON response indicating success or failure
     */
    // PUT /api/admin/scheduler/{id}/start
    @Execute(urlPattern = "{}/@word")
    public JsonResponse<ApiResult> put$start(final String id) {

:

{* ../../docs_src/body_multiple_params/tutorial005.py hl[17] *}

👉 💼 **FastAPI** 🔜 ⌛ 💪 💖:

```JSON hl_lines="2"
{
    "item": {
        "name": "Foo",
        "description": "The pretender",
        "price": 42.0,
        "tax": 3.2
    }
}
```

↩️:

```JSON
{
    "name": "Foo",
    "description": "The pretender",
    "price": 42.0,
    "tax": 3.2
}
```

  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

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")
	}
}

sleep 30s

nprefix=$(./mc ilm rule list siteb/bucket --json | jq '.config.Rules[0].Filter.And.Prefix' | sed 's/"//g')
ntagName1=$(./mc ilm rule list siteb/bucket --json | jq '.config.Rules[0].Filter.And.Tags[0].Key' | sed 's/"//g')
ntagVal1=$(./mc ilm rule list siteb/bucket --json | jq '.config.Rules[0].Filter.And.Tags[0].Value' | sed 's/"//g')
ntagName2=$(./mc ilm rule list siteb/bucket --json | jq '.config.Rules[0].Filter.And.Tags[1].Key' | sed 's/"//g')

            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("\",");

{* ../../docs_src/encoder/tutorial001_py310.py hl[4,21] *}

В данном примере она преобразует Pydantic модель в `dict`, а `datetime` - в `str`.

Результатом её вызова является объект, который может быть закодирован с помощью функции из стандартной библиотеки Python – <a href="https://docs.python.org/3/library/json.html#json.dumps" class="external-link" target="_blank">`json.dumps()`</a>.

{* ../../docs_src/encoder/tutorial001_py310.py hl[4,21] *}

In diesem Beispiel wird das Pydantic-Modell in ein `dict`, und das `datetime`-Objekt in ein `str` konvertiert.

Das Resultat dieses Aufrufs ist etwas, das mit Pythons Standard-<a href="https://docs.python.org/3/library/json.html#json.dumps" class="external-link" target="_blank">`json.dumps()`</a> kodiert werden kann.