}
            }
        }

        private void visit(Reporting reporting) {
            if (reporting != null) {
                String org, val;
                // ExcludeDefaults
                org = reporting.getExcludeDefaults();
                val = interpolate(org);
                if (org != val) {
                    reporting.setExcludeDefaults(val);
                }

        if (src != null) {
            if (sourceDominant || target.getExcludeDefaults() == null) {
                target.setExcludeDefaults(src);
                target.setLocation("excludeDefaults", source.getLocation("excludeDefaults"));
            }
        }
    }

    protected void mergeReporting_Plugins(
            Reporting target, Reporting source, boolean sourceDominant, Map<Object, Object> context) {

        </codeSegment>
        <codeSegment>
          <version>4.0.0/4.0.99</version>
          <code>
            <![CDATA[
    public void setExcludeDefaults(boolean excludeDefaults) {
        setExcludeDefaults(String.valueOf(excludeDefaults));
    }

    /**
     * Reset the <code>reportPluginMap</code> field to <code>null</code>
     */
    @Deprecated
    public void flushReportPluginMap() {

        assertEquals(
                "excluded-build-plugin-dep", pom.getValue("build/plugins[1]/dependencies[1]/exclusions[1]/artifactId"));

        assertEquals(Boolean.TRUE, pom.getValue("reporting/excludeDefaults"));
        assertPathSuffixEquals("docs", pom.getValue("reporting/outputDirectory"));

        assertEquals(1, ((List<?>) pom.getValue("reporting/plugins")).size());

            by_alias=by_alias,
            exclude_unset=exclude_unset,
            exclude_none=exclude_none,
            exclude_defaults=exclude_defaults,
        )
        return jsonable_encoder(
            obj_dict,
            exclude_none=exclude_none,
            exclude_defaults=exclude_defaults,
            sqlalchemy_safe=sqlalchemy_safe,
        )
    if dataclasses.is_dataclass(obj):

    assert jsonable_encoder(model, exclude_unset=True) == {"foo": "foo", "bar": "bar"}
    assert jsonable_encoder(model, exclude_defaults=True) == {"foo": "foo"}
    assert jsonable_encoder(model, exclude_unset=True, exclude_defaults=True) == {
        "foo": "foo"
    }
    assert jsonable_encoder(model, include={"foo"}) == {"foo": "foo"}

            value,
            mode=mode,
            include=include,
            exclude=exclude,
            by_alias=by_alias,
            exclude_unset=exclude_unset,
            exclude_defaults=exclude_defaults,
            exclude_none=exclude_none,
        )

    def __hash__(self) -> int:
        # Each ModelField is unique for our purposes, to allow making a dict from

* `response_model_exclude_defaults=True`
* `response_model_exclude_none=True`

<a href="https://docs.pydantic.dev/latest/concepts/serialization/#modeldict" class="external-link" target="_blank">Pydantic 문서</a>에서 `exclude_defaults` 및 `exclude_none`에 대해 설명한 대로 사용할 수 있습니다.

///

#### 기본값이 있는 필드를 갖는 값의 데이터

하지만 모델의 필드가 기본값이 있어도 ID가 `bar`인 항목(items)처럼 데이터가 값을 갖는다면:

```Python hl_lines="3  5"
{
    "name": "Bar",

* `response_model_exclude_defaults=True`
* `response_model_exclude_none=True`

参考 <a href="https://docs.pydantic.dev/latest/concepts/serialization/#modeldict" class="external-link" target="_blank">Pydantic 文档</a> 中对 `exclude_defaults` 和 `exclude_none` 的描述。

///

#### 默认值字段有实际值的数据

但是，如果你的数据在具有默认值的模型字段中有实际的值，例如 ID 为 `bar` 的项：

```Python hl_lines="3  5"
{
    "name": "Bar",
    "description": "The bartenders",

* `response_model_exclude_none=True`

verwenden, wie in der <a href="https://docs.pydantic.dev/1.10/usage/exporting_models/#modeldict" class="external-link" target="_blank">Pydantic Dokumentation</a> für `exclude_defaults` und `exclude_none` beschrieben.

///

#### Daten mit Werten für Felder mit Defaultwerten { #data-with-values-for-fields-with-defaults }