code: def union_indexes(indexes, sort: bool | None = True) -> Index:
      """
      Return the union of indexes.
  
      The behavior of sort and names is not consistent.
  
      Parameters
      ----------
      indexes : list of Index or list objects
      sort : bool, default True
          Whether the result index should come out sorted or not.
  
      Returns
      -------
      Index
      """
      if len(indexes) == 0:
          raise AssertionError("Must have at least 1 Index to union")
      if len(indexes) == 1:
          result = indexes[0]
          if isinstance(result, list):
              result = Index(sorted(result))
          return result
  
      indexes, kind = _sanitize_and_check(indexes)
  
      def _unique_indices(inds, dtype) -> Index:
          """
          Convert indexes to lists and concatenate them, removing duplicates.
  
          The final dtype is inferred.
  
          Parameters
          ----------
          inds : list of Index or list objects
          dtype : dtype to set for the resulting Index
  
          Returns
          -------
          Index
          """
  
          def conv(i):
              if isinstance(i, Index):
                  i = i.tolist()
              return i
  
          return Index(
              lib.fast_unique_multiple_list(
                  [conv(i) for i in inds], sort=sort
              ),
              dtype=dtype,
          )
  
      def _find_common_index_dtype(inds):
          """
          Finds a common type for the indexes to pass through to resulting index.
  
          Parameters
          ----------
          inds: list of Index or list objects
  
          Returns
          -------
          The common type or None if no indexes were given
          """
          dtypes = [
              idx.dtype for idx in indexes if isinstance(idx, Index)
          ]
          if dtypes:
              dtype = find_common_type(dtypes)
          else:
              dtype = None
  
          return dtype
  
      if kind == "special":
          result = indexes[0]
  
          dtis = [x for x in indexes if isinstance(x, DatetimeIndex)]
          dti_tzs = [x for x in dtis if x.tz is not None]
          if len(dti_tzs) not in [0, len(dtis)]:
              # TODO: this behavior is not tested (so may not be desired),
              #  but is kept in order to keep behavior the same when
              #  deprecating union_many
              # test_frame_from_dict_with_mixed_indexes
              raise TypeError(
                  "Cannot join tz-naive with tz-aware DatetimeIndex"
              )
  
          if len(dtis) == len(indexes):
              sort = True
              result = indexes[0]
  
          elif len(dtis) > 1:
              # If we have mixed timezones, our casting behavior may depend on
              #  the order of indexes, which we don't want.
              sort = False
  
              # TODO: what about Categorical[dt64]?
              # test_frame_from_dict_with_mixed_indexes
              indexes = [x.astype(object, copy=False) for x in indexes]
              result = indexes[0]
  
          for other in indexes[1:]:
              result = result.union(other, sort=None if sort else False)
          return result
  
      elif kind == "array":
          dtype = _find_common_index_dtype(indexes)
          index = indexes[0]
          if not all(index.equals(other) for other in indexes[1:]):
              index = _unique_indices(indexes, dtype)
  
          name = get_unanimous_names(*indexes)[0]
          if name != index.name:
              index = index.rename(name)
          return index
      else:  # kind='list'
          dtype = _find_common_index_dtype(indexes)
          return _unique_indices(indexes, dtype)
  
imports: from __future__ import annotations
  import textwrap
  from typing import cast
  import numpy
  from pandas._libs import NaT, lib
  from pandas._typing import Axis
  from pandas.errors import InvalidIndexError
  from pandas.core.dtypes.cast import find_common_type
  from pandas.core.algorithms import safe_sort
  from pandas.core.indexes.base import Index, _new_Index, ensure_index, ensure_index_from_sequences, get_unanimous_names
  from pandas.core.indexes.category import CategoricalIndex
  from pandas.core.indexes.datetimes import DatetimeIndex
  from pandas.core.indexes.interval import IntervalIndex
  from pandas.core.indexes.multi import MultiIndex
  from pandas.core.indexes.period import PeriodIndex
  from pandas.core.indexes.range import RangeIndex
  from pandas.core.indexes.timedeltas import TimedeltaIndex
label_desc: Use image node_id 5 for calling a global function with example usage: union_indexes(indexes, sort) and returns: result, Index, dtype, result, i, index, _unique_indices