String version = "aVersion";
        String type = "jar";
        String classifier = "aClassifier";
        String downloadUrl = "http://somewhere.com/download";
        List<String> path = Arrays.asList("dependency1", "dependency2");
        String expected = "Missing artifact" + LS + LS + "  Try downloading the file manually from: " + LS

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

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;

/**

public final class StandardMutableDirectedGraphTest extends AbstractStandardDirectedGraphTest {

  @Parameters(name = "allowsSelfLoops={0}, incidentEdgeOrder={1}")
  public static Collection<Object[]> parameters() {
    return Arrays.asList(
        new Object[][] {
          {false, ElementOrder.unordered()},
          {true, ElementOrder.unordered()},
          {false, ElementOrder.stable()},
          {true, ElementOrder.stable()},
        });
  }

public final class StandardMutableDirectedGraphTest extends AbstractStandardDirectedGraphTest {

  @Parameters(name = "allowsSelfLoops={0}, incidentEdgeOrder={1}")
  public static Collection<Object[]> parameters() {
    return Arrays.asList(
        new Object[][] {
          {false, ElementOrder.unordered()},
          {true, ElementOrder.unordered()},
          {false, ElementOrder.stable()},
          {true, ElementOrder.stable()},
        });
  }

Точно так же эта база данных не может принять Pydantic-модель (объект с атрибутами), а только `dict`.

Для этого можно использовать функцию `jsonable_encoder`.

Она принимает объект, например, Pydantic-модель, и возвращает его версию, совместимую с JSON:

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

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

 * <p>
 * Example usage:
 * <pre>
 * public class CustomPackagingProvider implements PackagingProvider {
 *     public Collection&lt;Packaging&gt; provides() {
 *         return Arrays.asList(
 *             packaging("docker-image"),
 *             packaging("flatpak")
 *         );
 *     }
 * }
 * </pre>
 *
 * @see org.apache.maven.api.Packaging

### 使用 Pydantic 的 `exclude_unset` 参数

更新部分数据时，可以在 Pydantic 模型的 `.dict()` 中使用 `exclude_unset` 参数。

比如，`item.dict(exclude_unset=True)`。

这段代码生成的 `dict` 只包含创建 `item` 模型时显式设置的数据，而不包括默认值。

然后再用它生成一个只含已设置（在请求中所发送）数据，且省略了默认值的 `dict`：

{* ../../docs_src/body_updates/tutorial002.py hl[34] *}

### 使用 Pydantic 的 `update` 参数

接下来，用 `.copy()` 为已有模型创建调用 `update` 参数的副本，该参数为包含更新数据的 `dict`。

例如，`stored_item_model.copy(update=update_data)`：

import static com.google.common.testing.SerializableTester.reserialize;
import static com.google.common.truth.Truth.assertThat;
import static com.google.common.truth.Truth.assertWithMessage;
import static java.util.Arrays.asList;
import static java.util.Collections.singletonMap;

import com.google.common.annotations.GwtCompatible;
import com.google.common.annotations.GwtIncompatible;
import com.google.common.annotations.J2ktIncompatible;

The same way, this database wouldn't receive a Pydantic model (an object with attributes), only a `dict`.

You can use `jsonable_encoder` for that.

It receives an object, like a Pydantic model, and returns a JSON compatible version:

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

In this example, it would convert the Pydantic model to a `dict`, and the `datetime` to a `str`.

  abstract static class CachingAsList<E> extends ImmutableSet<E> {
    @LazyInit @RetainedWith private transient @Nullable ImmutableList<E> asList;

    @Override
    public ImmutableList<E> asList() {
      ImmutableList<E> result = asList;
      if (result == null) {
        return asList = createAsList();
      } else {
        return result;
      }
    }

    ImmutableList<E> createAsList() {