## Lista de modelos { #list-of-models }

Da mesma forma, você pode declarar respostas de listas de objetos.

Para isso, use o padrão Python `list`:

{* ../../docs_src/extra_models/tutorial004_py310.py hl[18] *}

## Resposta com `dict` arbitrário { #response-with-arbitrary-dict }

			<integer>10</integer>
		</dict>
		<key>ResourceRules.plist</key>
		<dict>
			<key>omit</key>
			<true/>
			<key>weight</key>
			<integer>100</integer>
		</dict>
	</dict>
</dict>
</plist>

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.app.web.admin.dict;

import org.codelibs.fess.annotation.Secured;
import org.codelibs.fess.app.web.base.FessAdminAction;
import org.codelibs.fess.dict.DictionaryFile;
import org.codelibs.fess.dict.DictionaryItem;
import org.codelibs.fess.dict.DictionaryManager;
import org.codelibs.fess.util.RenderDataUtil;
import org.lastaflute.web.Execute;

    if (charsSkipped > 0) {
      int endIndex = destIndex + charsSkipped;
      if (dest.length < endIndex) {
        dest = growBuffer(dest, destIndex, endIndex);
      }
      s.getChars(unescapedChunkStart, end, dest, destIndex);
      destIndex = endIndex;
    }
    return new String(dest, 0, destIndex);
  }

  /**
   * Returns the Unicode code point of the character at the given index.
   *

## Liste von Modellen { #list-of-models }

Auf die gleiche Weise können Sie Responses von Listen von Objekten deklarieren.

Dafür verwenden Sie Pythons Standard-`list`:

{* ../../docs_src/extra_models/tutorial004_py310.py hl[18] *}

## Response mit beliebigem `dict` { #response-with-arbitrary-dict }

                else "validation"
            ),
            field._type_adapter.core_schema,
        )
        for field in list(fields) + list(unique_flat_model_fields)
    ]
    field_mapping, definitions = schema_generator.generate_definitions(inputs=inputs)
    for item_def in cast(dict[str, dict[str, Any]], definitions).values():
        if "description" in item_def:

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.dict.mapping;

import java.util.Date;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.codelibs.fess.dict.DictionaryCreator;
import org.codelibs.fess.dict.DictionaryFile;
import org.codelibs.fess.dict.DictionaryItem;

import jakarta.annotation.PostConstruct;

/**

# JSON-сумісний кодувальник { #json-compatible-encoder }

Існують випадки, коли вам може знадобитися перетворити тип даних (наприклад, модель Pydantic) на щось сумісне з JSON (наприклад, `dict`, `list` тощо).

Наприклад, якщо вам потрібно зберегти це в базі даних.

Для цього **FastAPI** надає функцію `jsonable_encoder()`.

## Використання `jsonable_encoder` { #using-the-jsonable-encoder }

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.dict.kuromoji;

import java.util.Date;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.codelibs.fess.dict.DictionaryCreator;
import org.codelibs.fess.dict.DictionaryFile;
import org.codelibs.fess.dict.DictionaryItem;

import jakarta.annotation.PostConstruct;

/**

// Parse get data type from dialector
func Parse(dest interface{}, cacheStore *sync.Map, namer Namer) (*Schema, error) {
	return ParseWithSpecialTableName(dest, cacheStore, namer, "")
}

// ParseWithSpecialTableName get data type from dialector with extra schema table
func ParseWithSpecialTableName(dest interface{}, cacheStore *sync.Map, namer Namer, specialTableName string) (*Schema, error) {
	if dest == nil {