def _getSmartIndenter(indenterName, qpart, indenter):
    """Get indenter by name.
    Available indenters are none, normal, cstyle, haskell, lilypond, lisp, python, ruby, xml
    Indenter name is not case sensitive
    Raise KeyError if not found
    indentText is indentation, which shall be used. i.e. '\t' for tabs, '    ' for 4 space symbols
    """
    indenterName = indenterName.lower()

    if indenterName in ('haskell', 'lilypond'):  # not supported yet
        logger.warning('Smart indentation for %s not supported yet. But you could be a hero who implemented it' % indenterName)
        from qutepart.indenter.base import IndentAlgNormal as indenterClass
    elif 'none' == indenterName:
        from qutepart.indenter.base import IndentAlgBase as indenterClass
    elif 'normal' == indenterName:
        from qutepart.indenter.base import IndentAlgNormal as indenterClass
    elif 'cstyle' == indenterName:
        from qutepart.indenter.cstyle import IndentAlgCStyle as indenterClass
    elif 'python' == indenterName:
        from qutepart.indenter.python import IndentAlgPython as indenterClass
    elif 'ruby' == indenterName:
        from qutepart.indenter.ruby import IndentAlgRuby as indenterClass
    elif 'xml' == indenterName:
        from qutepart.indenter.xmlindent import IndentAlgXml as indenterClass
    elif 'haskell' == indenterName:
        from qutepart.indenter.haskell import IndenterHaskell as indenterClass
    elif 'lilypond' == indenterName:
        from qutepart.indenter.lilypond import IndenterLilypond as indenterClass
    elif 'lisp' == indenterName:
        from qutepart.indenter.lisp import IndentAlgLisp as indenterClass
    elif 'scheme' == indenterName:
        from qutepart.indenter.scheme import IndentAlgScheme as indenterClass
    else:
        raise KeyError("Indenter %s not found" % indenterName)

    return indenterClass(qpart, indenter)
def _read_metadata_from_example_file(netcdf_file_name, include_soundings):
    """Reads metadata from file with input examples.

    :param netcdf_file_name: Path to input file.
    :param include_soundings: Boolean flag.  If True and file contains
        soundings, this method will return keys "sounding_field_names" and
        "sounding_heights_m_agl".  Otherwise, will not return said keys.

    :return: example_dict: Dictionary with the following keys (explained in doc
        to `write_example_file`).
    example_dict['full_id_strings']
    example_dict['storm_times_unix_sec']
    example_dict['radar_field_names']
    example_dict['radar_heights_m_agl']
    example_dict['rotated_grids']
    example_dict['rotated_grid_spacing_metres']
    example_dict['target_names']
    example_dict['sounding_field_names']
    example_dict['sounding_heights_m_agl']

    :return: netcdf_dataset: Instance of `netCDF4.Dataset`, which can be used to
        keep reading file.
    """

    netcdf_dataset = netCDF4.Dataset(netcdf_file_name)
    include_soundings = (
        include_soundings and
        SOUNDING_FIELDS_KEY in netcdf_dataset.variables
    )

    example_dict = {
        ROTATED_GRIDS_KEY: bool(getattr(netcdf_dataset, ROTATED_GRIDS_KEY)),
        TARGET_NAMES_KEY: [
            str(s) for s in
            netCDF4.chartostring(netcdf_dataset.variables[TARGET_NAMES_KEY][:])
        ],
        FULL_IDS_KEY: [
            str(s) for s in
            netCDF4.chartostring(netcdf_dataset.variables[FULL_IDS_KEY][:])
        ],
        STORM_TIMES_KEY: numpy.array(
            netcdf_dataset.variables[STORM_TIMES_KEY][:], dtype=int
        ),
        RADAR_FIELDS_KEY: [
            str(s) for s in
            netCDF4.chartostring(netcdf_dataset.variables[RADAR_FIELDS_KEY][:])
        ],
        RADAR_HEIGHTS_KEY: numpy.array(
            netcdf_dataset.variables[RADAR_HEIGHTS_KEY][:], dtype=int
        )
    }

    # TODO(thunderhoser): This is a HACK to deal with bad files.
    example_dict[TARGET_NAMES_KEY] = [
        n for n in example_dict[TARGET_NAMES_KEY] if n != ''
    ]

    if example_dict[ROTATED_GRIDS_KEY]:
        example_dict[ROTATED_GRID_SPACING_KEY] = getattr(
            netcdf_dataset, ROTATED_GRID_SPACING_KEY)
    else:
        example_dict[ROTATED_GRID_SPACING_KEY] = None

    if not include_soundings:
        return example_dict, netcdf_dataset

    example_dict.update({
        SOUNDING_FIELDS_KEY: [
            str(s) for s in netCDF4.chartostring(
                netcdf_dataset.variables[SOUNDING_FIELDS_KEY][:])
        ],
        SOUNDING_HEIGHTS_KEY:
            numpy.array(netcdf_dataset.variables[SOUNDING_HEIGHTS_KEY][:],
                        dtype=int)
    })

    return example_dict, netcdf_dataset