*/
package org.codelibs.fess.suggest.index.writer;

import java.util.ArrayList;
import java.util.Collections;
import java.util.List;

/**
 * The SuggestWriterResult class is used to store and manage the results of a suggest writer operation.
 * It keeps track of any failures that occur during the operation.
 */
public class SuggestWriterResult {
    /**
     * Constructs a new {@link SuggestWriterResult}.
     */

                messages.addErrorsFailedToStartJob(GLOBAL, id);
            });
        });
        return asJson(new ApiResult.ApiStartJobResponse().jobLogId(jobLogId[0]).status(Status.OK).result());
    }

    /**
     * Stops a scheduled job by ID.
     *
     * @param id the ID of the scheduled job to stop
     * @return JSON response indicating success or failure
     */

    public T next() {
      Iterator<T> itr = stack.getLast(); // throws NSEE if empty
      T result = checkNotNull(itr.next());
      if (!itr.hasNext()) {
        stack.removeLast();
      }
      Iterator<T> childItr = children(result).iterator();
      if (childItr.hasNext()) {
        stack.addLast(childItr);
      }
      return result;
    }
  }

  /**

  @Override
  public void run() {
    T result = null;
    Throwable error = null;
    if (isDone()) {
      return;
    }
    try {
      result = runInterruptibly();
    } catch (Throwable t) {
      error = t;
    }
    if (error == null) {
      // The cast is safe because of the `run` and `error` checks.
      afterRanInterruptiblySuccess(uncheckedCastNullableTToT(result));
    } else {

        List<QuerySearchResult> shards = new ArrayList<>();
        for (int i = 0; i < candidateList.size(); i++) {
            QuerySearchResult result = new QuerySearchResult();
            result.setShardIndex(i);
            result.from(0);
            result.size(0);
            result.topDocs(
                new TopDocsAndMaxScore(

    tax: float | None = None


app = FastAPI()


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item, q: str | None = None):
    result = {"item_id": item_id, **item.model_dump()}
    if q:
        result.update({"q": q})

$(function() {
  var $result = $("#result");
  var $queryId = $("#queryId");
  var $favorites = $(".favorite", $result);
  var $searchButton = $("#searchButton");
  var contextPath = $("#contextPath").val();
  var IMG_LOADING_DELAY = 200;
  var IMG_LOADING_MAX = 0;
  var BUTTON_DISABLE_DURATION = 3000;
  var AJAX_TIMEOUT = 10000;
  var FADE_DURATION = 1000;

  var SUGGESTOR_CONFIG = {
    ajaxinfo: {

//     op for shape inference.
//   - The types need not be set in `input_shapes` as it is not used.
//   - The number of `input_tensors` should be the same as the number of items
//     in `input_shapes`.
//
// The results are returned in `output_shapes` and
// `output_resource_shapes_and_types`. The caller is responsible for freeing the
// memory in these buffers by calling `TF_DeleteShapeAndTypeList`.
TF_CAPI_EXPORT extern void TFE_InferShapes(

		{"config/iam/groups/foo/config.json", "config/iam/groups/", "config.json", "foo"},
	}
	for i, test := range specs {
		result := extractPathPrefixAndSuffix(test.path, test.prefix, test.suffix)
		if result != test.expected {
			t.Errorf("unexpected result on test[%v]: expected[%s] but had [%s]", i, test.expected, result)
		}
	}

    }

    @Override
    public int hashCode() {
        int result = hashCode;
        if (result == 0) {
            result = java.util.Objects.hash(lineNumber, columnNumber, source, locations, importedFrom);
            hashCode = result;
        }
        return result;
    }

    @Override
    public String toString() {