code: def _deserialize_column_index(
      block_table, all_columns, column_indexes
  ):
      column_strings = [
          frombytes(x) if isinstance(x, bytes) else x
          for x in block_table.column_names
      ]
      if all_columns:
          columns_name_dict = {
              c.get(
                  "field_name", _column_name_to_strings(c["name"])
              ): c["name"]
              for c in all_columns
          }
          columns_values = [
              columns_name_dict.get(name, name)
              for name in column_strings
          ]
      else:
          columns_values = column_strings
  
      # If we're passed multiple column indexes then evaluate with
      # ast.literal_eval, since the column index values show up as a list of
      # tuples
      to_pair = (
          ast.literal_eval
          if len(column_indexes) > 1
          else lambda x: (x,)
      )
  
      # Create the column index
  
      # Construct the base index
      if not columns_values:
          columns = _pandas_api.pd.Index(columns_values)
      else:
          columns = _pandas_api.pd.MultiIndex.from_tuples(
              list(map(to_pair, columns_values)),
              names=[col_index["name"] for col_index in column_indexes]
              or None,
          )
  
      # if we're reconstructing the index
      if len(column_indexes) > 0:
          columns = _reconstruct_columns_from_metadata(
              columns, column_indexes
          )
  
      # ARROW-1751: flatten a single level column MultiIndex for pandas 0.21.0
      columns = _flatten_single_level_multiindex(columns)
  
      return columns
  
imports: import ast
  from collections.abc import Sequence
  from concurrent import futures
  import concurrent.futures.thread
  from copy import deepcopy
  from itertools import zip_longest
  import json
  import operator
  import re
  import warnings
  import numpy
  import pyarrow
  from pyarrow.lib import _pandas_api, frombytes
label_desc: Use image node_id 25 for calling a global function with example usage: _deserialize_column_index(block_table, all_columns, column_indexes) and returns: columns