def split_indexes(
    dims_or_levels,  # type: Union[Any, List[Any]]
    variables,  # type: OrderedDict[Any, Variable]
    coord_names,  # type: Set
    level_coords,  # type: Dict[Any, Any]
    drop=False,  # type: bool
):
    # type: (...) -> Tuple[OrderedDict[Any, Variable], Set]
    """Extract (multi-)indexes (levels) as variables.

    Not public API. Used in Dataset and DataArray reset_index
    methods.
    """
    if isinstance(dims_or_levels, str):
        dims_or_levels = [dims_or_levels]

    dim_levels = defaultdict(list)  # type: Dict[Any, list]
    dims = []
    for k in dims_or_levels:
        if k in level_coords:
            dim_levels[level_coords[k]].append(k)
        else:
            dims.append(k)

    vars_to_replace = {}
    vars_to_create = OrderedDict()  # type: OrderedDict[Any, Variable]
    vars_to_remove = []

    for d in dims:
        index = variables[d].to_index()
        if isinstance(index, pd.MultiIndex):
            dim_levels[d] = index.names
        else:
            vars_to_remove.append(d)
            if not drop:
                vars_to_create[d + '_'] = Variable(d, index)

    for d, levs in dim_levels.items():
        index = variables[d].to_index()
        if len(levs) == index.nlevels:
            vars_to_remove.append(d)
        else:
            vars_to_replace[d] = IndexVariable(d, index.droplevel(levs))

        if not drop:
            for lev in levs:
                idx = index.get_level_values(lev)
                vars_to_create[idx.name] = Variable(d, idx)

    new_variables = variables.copy()
    for v in set(vars_to_remove):
        del new_variables[v]
    new_variables.update(vars_to_replace)
    new_variables.update(vars_to_create)
    new_coord_names = (coord_names | set(vars_to_create)) - set(vars_to_remove)

    return new_variables, new_coord_names