def generate_export(export_type, extension, username, id_string,
                    export_id=None, filter_query=None, group_delimiter='/',
                    split_select_multiples=True,
                    binary_select_multiples=False):

    export_type_func_map = {
        Export.XLS_EXPORT: 'to_xls_export',
        Export.CSV_EXPORT: 'to_flat_csv_export',
        Export.CSV_ZIP_EXPORT: 'to_zipped_csv',
        Export.SAV_ZIP_EXPORT: 'to_zipped_sav',
        Export.ANALYSER_EXPORT: 'to_analyser_export'
    }

    xform = XForm.objects.get(
        user__username__iexact=username, id_string__exact=id_string)

    # query mongo for the cursor
    records = query_mongo(username, id_string, filter_query)

    export_builder = ExportBuilder()
    export_builder.GROUP_DELIMITER = group_delimiter
    export_builder.SPLIT_SELECT_MULTIPLES = split_select_multiples
    export_builder.BINARY_SELECT_MULTIPLES = binary_select_multiples
    export_builder.set_survey(xform.data_dictionary().survey)

    temp_file = NamedTemporaryFile(prefix=export_type+'_EXPORT_TMP_', suffix=("." + extension))

    # get the export function by export type
    func = getattr(export_builder, export_type_func_map[export_type])

    func.__call__(
        temp_file.name, records, username, id_string, filter_query)

    # generate filename
    basename = "%s_%s" % (
        id_string, datetime.now().strftime("%Y_%m_%d_%H_%M_%S"))
    if export_type == Export.ANALYSER_EXPORT:
        # Analyser exports should be distinguished by more than just their file extension.
        basename= '{}_ANALYSER_{}'.format(id_string, datetime.now().strftime("%Y_%m_%d_%H_%M_%S"))
    filename = basename + "." + extension

    # check filename is unique
    while not Export.is_filename_unique(xform, filename):
        filename = increment_index_in_filename(filename)

    file_path = os.path.join(
        username,
        'exports',
        id_string,
        export_type,
        filename)

    # TODO: if s3 storage, make private - how will we protect local storage??
    storage = get_storage_class()()
    # seek to the beginning as required by storage classes
    temp_file.seek(0)
    export_filename = storage.save(
        file_path,
        File(temp_file, file_path))
    temp_file.close()

    dir_name, basename = os.path.split(export_filename)

    # get or create export object
    if export_id:
        export = Export.objects.get(id=export_id)
    else:
        export = Export(xform=xform, export_type=export_type)
    export.filedir = dir_name
    export.filename = basename
    export.internal_status = Export.SUCCESSFUL
    # dont persist exports that have a filter
    if filter_query is None:
        export.save()
    return export
Override this method so that it flushes the vtk pipeline if
dataset/ETHPy150Open kobotoolbox/kobocat/onadata/libs/utils/export_tools.py/generate_export--crossover with--dataset/ETHPy150Open enthought/mayavi/mayavi/components/glyph.py/Glyph.update_data