{
  "settings": {
    "index": {
      "refresh_interval": "1s",
      "number_of_shards": 1,
      "number_of_replicas": 0,
      "auto_expand_replicas": "0-1"
    },
    "analysis": {
      "analyzer": {
        "standard_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": [
            "cjk_width",
            "asciifolding",
            "lowercase",
            "stop",

{
  "settings": {
    "index": {
      "refresh_interval": "1s",
      "number_of_shards": 1,
      "number_of_replicas": 0,
      "auto_expand_replicas": "0-1"
    },
    "analysis": {
      "analyzer": {
        "standard_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": [
            "cjk_width",
            "asciifolding",
            "lowercase",
            "stop",

   * <p>Returns without doing anything if another thread is currently loading the value for {@code
   * key}. If the cache loader associated with this cache performs refresh asynchronously then this
   * method may return before refresh completes.
   *
   * @since 11.0
   */
  void refresh(K key);

  /**
   * {@inheritDoc}
   *
   * <p><b>Note that although the view <i>is</i> modifiable, no method on the returned map will ever

    String[] getRoleNames();

    String[] getGroupNames();

    String[] getPermissions();

    default boolean isEditable() {
        return false;
    }

    default boolean refresh() {
        return false;
    }

高度なシナリオでは、「キャッシュされた」値を使うのではなく、同じリクエストの各ステップ（おそらく複数回）で依存関係を呼び出す必要があることがわかっている場合、`Depens`を使用する際に、`use_cache=False`というパラメータを設定することができます。

```Python hl_lines="1"
async def needy_dependency(fresh_value: str = Depends(get_value, use_cache=False)):
    return {"fresh_value": fresh_value}
```

## まとめ

ここで使われている派手な言葉は別にして、**依存性注入** システムは非常にシンプルです。

*path operation関数*と同じように見えるただの関数です。

しかし、それでも非常に強力で、任意の深くネストされた依存関係「グラフ」（ツリー）を宣言することができます。

在高级使用场景中，如果不想使用「缓存」值，而是为需要在同一请求的每一步操作（多次）中都实际调用依赖项，可以把 `Depends` 的参数 `use_cache` 的值设置为 `False` :

```Python hl_lines="1"
async def needy_dependency(fresh_value: str = Depends(get_value, use_cache=False)):
    return {"fresh_value": fresh_value}
```

## 小结

千万别被本章里这些花里胡哨的词藻吓倒了，其实**依赖注入**系统非常简单。

依赖注入无非是与*路径操作函数*一样的函数罢了。

但它依然非常强大，能够声明任意嵌套深度的「图」或树状的依赖结构。

!!! tip "提示"

	dm2 := NewDRWMutex(ds, "noot")

	dm1.Lock(id, source)
	dm2.Lock(id, source)
	dm1.Unlock(context.Background())
	dm2.Unlock(context.Background())
}

// Test refreshing lock - refresh should always return true
func TestSuccessfulLockRefresh(t *testing.T) {
	if testing.Short() {
		t.Skip("skipping test in short mode.")
	}

	dm := NewDRWMutex(ds, "aap")

                logger.debug("update script by id: {}", source);
            }
            final String refresh = StringUtil.isNotBlank(fessConfig.getIndexReindexRefresh()) ? fessConfig.getIndexReindexRefresh() : null;
            try (CurlResponse response = ComponentUtil.getCurlHelper().post("/" + index + "/_update_by_query").param("refresh", refresh)
                    .param("max_docs", "1").body(source).execute()) {

import org.codelibs.fess.thumbnail.ThumbnailManager;
import org.codelibs.fess.util.ComponentUtil;
import org.codelibs.fess.util.DocList;
import org.codelibs.fess.util.MemoryUtil;
import org.opensearch.action.admin.indices.refresh.RefreshResponse;
import org.opensearch.action.search.SearchResponse;
import org.opensearch.index.query.QueryBuilder;
import org.opensearch.index.query.QueryBuilders;

public class IndexingHelper {

      return false;
    }
  },

  /**
   * The entry itself was not actually removed, but its value was replaced by the user. This can
   * result from the user invoking {@link Cache#put}, {@link LoadingCache#refresh}, {@link Map#put},
   * {@link Map#putAll}, {@link ConcurrentMap#replace(Object, Object)}, or {@link
   * ConcurrentMap#replace(Object, Object, Object)}.
   */
  REPLACED {
    @Override
    boolean wasEvicted() {