ModTime:   timeSentinel1970,
			}, nil
		}
		inData = xlMeta.data
		fi, err = xlMeta.ToFileInfo(volume, path, versionID, opts.InclFreeVersions, true)
	}
	if !opts.Data || err != nil {
		return fi, err
	}
	versionID = fi.VersionID
	if versionID == "" {
		versionID = nullVersionID
	}

	fi.Data = inData.find(versionID)
	if len(fi.Data) == 0 {
		// PR #11758 used DataDir, preserve it

    extends AbstractTableReadTest<C> {

  protected void populate(Table<String, Integer, C> table, @Nullable Object... data) {
    checkArgument(data.length % 3 == 0);
    for (int i = 0; i < data.length; i += 3) {
      table.put(
          (String) data[i], (Integer) data[i + 1], nullableCellValue((Character) data[i + 2]));
    }
  }

  protected boolean supportsRemove() {
    return true;
  }

Lambda

MinIO's Object Lambda implementation allows for transforming your data to serve unique data format requirements for each application. For example, a dataset created by an ecommerce application might include personally identifiable information (PII). When the same data is processed for analytics, PII should be redacted. However, if the same dataset is used for a marketing campaign, you might need to enrich the data with additional details, such as information from the customer loyalty database....

   * data, and vertical if there is variance in the {@code y} data but not the {@code x} data.
   *
   * <p>This fit minimizes the root-mean-square error in {@code y} as a function of {@code x}. This
   * error is defined as the square root of the mean of the squares of the differences between the
   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}

func Test_metaCacheEntries_filterRecursiveRoot(t *testing.T) {
	data := loadMetacacheSampleEntries(t)
	data.filterRecursiveEntries("", slashSeparator)
	got := data.entries().names()
	want := []string{}
	if !reflect.DeepEqual(want, got) {
		t.Errorf("got unexpected result: %#v", got)
	}
}

func Test_metaCacheEntries_filterRecursiveRootSep(t *testing.T) {
	data := loadMetacacheSampleEntries(t)

        }
        final byte[] data = accessResultData.getData();
        if (data == null) {
            return null;
        }
        return new ByteArrayInputStream(data);
    }

  });
  if (pr_resp.status != 200 || pr_resp.data.state != 'closed') {
    console.log(`PR:{pr_number} is not found or closed.  Not a valid condition to create an issue.`);
    console.log(pr_resp);
    throw `PR:{pr_number} needs to be valid and closed (merged)`;
  }
  const pr_title = pr_resp.data.title;
  // Assign to PR owner and reviewers
  const assignees = pr_resp.data.assignees.concat(pr_resp.data.requested_reviewers);

                                            <c:forEach var="data" varStatus="s" items="${jobLogItems}">
                                                <tr
                                                        data-href="${contextPath}/admin/joblog/details/4/${f:u(data.id)}">
                                                    <td>${f:h(data.jobName)}</td>

Static\n\n  static _jQueryInterface(config) {\n    let data = $(this).data(DATA_KEY)\n    const _options = $.extend({}, Default, $(this).data())\n\n    if (!data) {\n      data = new CardRefresh($(this), _options)\n      $(this).data(DATA_KEY, typeof config === 'string' ? data : config)\n    }\n\n    if (typeof config === 'string' && /load/.test(config)) {\n      data[config]()\n    } else {\n      data._init($(this))\n    }\n  }\n}\n\n/**\n * Data API\n * ====================================================\n...

It doesn't return a large `str` containing the data in JSON format (as a string). It returns a Python standard data structure (e.g. a `dict`) with values and sub-values that are all compatible with JSON.

/// note

`jsonable_encoder` is actually used by **FastAPI** internally to convert data. But it is useful in many other scenarios.