elif isinstance(item, dict):
            assert len(item) == 1
            values = list(item.values())
            if not values:
                continue
            if isinstance(values[0], str):
                resolve_file(item=values[0], files=files, config=config)
            elif isinstance(values[0], list):
                resolve_files(items=values[0], files=files, config=config)
            else:

func FromBool(b bool) *Value {
	return &Value{value: b}
}

// FromTimestamp creates a Value from a timestamp
func FromTimestamp(t time.Time) *Value {
	return &Value{value: t}
}

// FromNull creates a Value with Null value
func FromNull() *Value {
	return &Value{value: nil}
}

// FromMissing creates a Value with Missing value
func FromMissing() *Value {
	return &Value{value: Missing{}}
}

}

func (association *Association) Append(values ...interface{}) error {
	values = expandValues(values)

	if association.Error == nil {
		switch association.Relationship.Type {
		case schema.HasOne, schema.BelongsTo:
			if len(values) > 0 {
				association.Error = association.Replace(values...)
			}
		default:
			association.saveAssociation( /*clear*/ false, values...)
		}
	}

	return association.Error
}

 * it easy to get sample values to use in such tests.
 *
 * This class is pretty fast and loose with default values: it attempts to provide values that are
 * well-formed, but doesn't guarantee values are internally consistent. Callers must take care to
 * configure the factory when sample values impact the correctness of the test.
 */
class TestValueFactory : Closeable {

   * called and that value is both inserted and returned.
   *
   * If multiple calls to this function are made concurrently with the same [type], multiple values
   * may be computed. But only one value will be inserted, and that inserted value will be returned
   * to all callers.
   *
   * If computing multiple values is problematic, use an appropriate concurrency mechanism in your

        assertWithMessage("mean by addAll(Stats) of %s", values).that(meanByAddAllStats).isNaN();
      } else if (values.hasAnyPositiveInfinity()) {
        assertWithMessage("mean of %s", values).that(mean).isPositiveInfinity();
        assertWithMessage("mean by addAll(Stats) of %s", values)
            .that(meanByAddAllStats)
            .isPositiveInfinity();
      } else if (values.hasAnyNegativeInfinity()) {

	values := make(url.Values)
	values.Set(peerRESTMetricsTypes, strconv.FormatUint(uint64(t), 10))
	for disk := range opts.disks {
		values.Add(peerRESTDisk, disk)
	}
	for host := range opts.hosts {
		values.Add(peerRESTHost, host)
	}
	values.Set(peerRESTJobID, opts.jobID)
	values.Set(peerRESTDepID, opts.depID)

    if is_sequence_field(field) and isinstance(values, (ImmutableMultiDict, Headers)):
        value = values.getlist(alias)
    else:
        value = values.get(alias, None)
    if (
        value is None
        or (
            isinstance(field.field_info, params.Form)
            and isinstance(value, str)  # For type checks
            and value == ""
        )

        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStatsAccumulator accumulator =
          createFilledPairedStatsAccumulator(values.asIterable(), OTHER_MANY_VALUES);
      PairedStatsAccumulator accumulatorByAddAllPartitionedPairedStats =

			return err
		}
	}
	return nil
}

// DropTable drop table for values
func (m Migrator) DropTable(values ...interface{}) error {
	values = m.ReorderModels(values, false)
	for i := len(values) - 1; i >= 0; i-- {
		tx := m.DB.Session(&gorm.Session{})
		if err := m.RunWithValue(values[i], func(stmt *gorm.Statement) error {
			return tx.Exec("DROP TABLE IF EXISTS ?", m.CurrentTable(stmt)).Error
		}); err != nil {