document.put("string_field", "value1");
        document.put("string_array_field", new String[] { "value2", "value3" });
        document.put("list_field", java.util.Arrays.asList("value4", "value5"));
        document.put("int_field", 123);

        String[] stringValues = defaultContentsParser.getFieldValues(document, "string_field");
        assertEquals(1, stringValues.length);

    }                                                                        \
    const auto len = std::min(max_values, attr->list().list_field##_size()); \
    for (int i = 0; i < len; ++i) {                                          \
      values[i] = static_cast<c_type>(attr->list().list_field(i));           \
    }                                                                        \
  }

def _get_flat_fields_from_params(fields: list[ModelField]) -> list[ModelField]:
    if not fields:
        return fields
    first_field = fields[0]
    if len(fields) == 1 and lenient_issubclass(
        first_field.field_info.annotation, BaseModel
    ):
        fields_to_extract = get_cached_model_fields(first_field.field_info.annotation)
        return fields_to_extract
    return fields

    ]
    default_convert_underscores = True
    if len(flat_dependant.header_params) == 1:
        first_field = flat_dependant.header_params[0]
        if lenient_issubclass(first_field.field_info.annotation, BaseModel):
            default_convert_underscores = getattr(
                first_field.field_info, "convert_underscores", True
            )
    for param_type, param_group in parameter_groups:

        `tf.contrib.data.make_csv_dataset()`. [tf.data] Remove
        `num_parallel_parser_calls` argument from
        `tf.contrib.data.make_csv_dataset()`.
    *   `tf.data.Dataset.list_files()` raises an exception at initialization
        time if the argument matches no files.
    *   Renamed BigTable class to BigtableTable for clarity
    *   Document use of the Cloud Bigtable API