code: def indexer_from_factorized(
      labels, shape: Shape, compress: bool = True
  ) -> npt.NDArray[np.intp]:
      ids = get_group_index(labels, shape, sort=True, xnull=False)
  
      if not compress:
          ngroups = (ids.size and ids.max()) + 1
      else:
          ids, obs = compress_group_index(ids, sort=True)
          ngroups = len(obs)
  
      return get_group_index_sorter(ids, ngroups)
  
imports: from __future__ import annotations
  from collections import defaultdict
  from typing import TYPE_CHECKING, Callable, DefaultDict, Hashable, Iterable, Sequence, cast
  import numpy
  from pandas._libs import algos, hashtable, lib
  from pandas._libs.hashtable import unique_label_indices
  from pandas._typing import AxisInt, IndexKeyFunc, Level, NaPosition, Shape, SortKind, npt
  from pandas.core.dtypes.common import ensure_int64, ensure_platform_int, is_extension_array_dtype
  from pandas.core.dtypes.generic import ABCMultiIndex, ABCRangeIndex
  from pandas.core.dtypes.missing import isna
  from pandas.core.construction import extract_array
label_desc: Use image node_id 7 for calling a global function with example usage: indexer_from_factorized(labels, shape, compress) and returns: get_group_index_sorter