code: def _index_dispatch(arg, df, axis):  # noqa: F811
      """
      Base function for selection on a Pandas Index object.
      Applies only to list type.
      It can take any of slice, str, callable, re.Pattern types, ...,
      or a combination of these types.
  
      Returns an array of integers.
      """
      index = getattr(df, axis)
      if is_bool_indexer(arg):
          if len(arg) != len(index):
              raise ValueError(
                  "The length of the list of booleans "
                  f"({len(arg)}) does not match "
                  f"the length of the DataFrame's {axis}({index.size})."
              )
  
          return arg
  
      # shortcut for single unique dtype of scalars
      checks = (is_scalar(entry) for entry in arg)
      if all(checks):
          dtypes = {type(entry) for entry in arg}
          if len(dtypes) == 1:
              indices = index.get_indexer_for(list(arg))
              if (indices != -1).all():
                  return indices
      # treat multiple DropLabel instances as a single unit
      checks = (isinstance(entry, DropLabel) for entry in arg)
      if sum(checks) > 1:
          drop_labels = (
              entry for entry in arg if isinstance(entry, DropLabel)
          )
          drop_labels = [entry.label for entry in drop_labels]
          drop_labels = DropLabel(drop_labels)
          arg = [
              entry for entry in arg if not isinstance(entry, DropLabel)
          ]
          arg.append(drop_labels)
      indices = [_select_index(entry, df, axis) for entry in arg]
  
      # single entry does not need to be combined
      # or materialized if possible;
      # this offers more performance
      if len(indices) == 1:
          if is_scalar(indices[0]):
              return indices
          indices = indices[0]
          if is_list_like(indices):
              indices = np.asanyarray(indices)
          return indices
      indices = [_index_converter(arr, index) for arr in indices]
      return np.concatenate(indices)
  
imports: from __future__ import annotations
  import fnmatch
  import inspect
  import re
  import warnings
  from collections.abc import Callable
  from dataclasses import dataclass
  from enum import Enum
  from functools import singledispatch
  from typing import Any, Callable, Hashable, Iterable, List, Literal, Optional, Pattern, Union
  import numpy
  import pandas
  from multipledispatch import dispatch
  from pandas.api.types import is_bool_dtype, is_datetime64_dtype, is_list_like, is_scalar, is_string_dtype, union_categoricals
  from pandas.core.common import is_bool_indexer
  from pandas.core.groupby.generic import DataFrameGroupBy, SeriesGroupBy
  from janitor.utils import _expand_grid, check, check_column, find_stack_level
label_desc: Use image node_id 17 for calling a global function with example usage: _index_dispatch(arg, df, axis) and returns: np, arg, indices, indices, indices