code: def _reconstruct_block(item, columns=None, extension_columns=None):
      """
      Construct a pandas Block from the `item` dictionary coming from pyarrow's
      serialization or returned by arrow::python::ConvertTableToPandas.
  
      This function takes care of converting dictionary types to pandas
      categorical, Timestamp-with-timezones to the proper pandas Block, and
      conversion to pandas ExtensionBlock
  
      Parameters
      ----------
      item : dict
          For basic types, this is a dictionary in the form of
          {'block': np.ndarray of values, 'placement': pandas block placement}.
          Additional keys are present for other types (dictionary, timezone,
          object).
      columns :
          Column names of the table being constructed, used for extension types
      extension_columns : dict
          Dictionary of {column_name: pandas_dtype} that includes all columns
          and corresponding dtypes that will be converted to a pandas
          ExtensionBlock.
  
      Returns
      -------
      pandas Block
  
      """
      import pandas.core.internals as _int
  
      block_arr = item.get("block", None)
      placement = item["placement"]
      if "dictionary" in item:
          cat = _pandas_api.categorical_type.from_codes(
              block_arr,
              categories=item["dictionary"],
              ordered=item["ordered"],
          )
          block = _int.make_block(cat, placement=placement)
      elif "timezone" in item:
          unit, _ = np.datetime_data(block_arr.dtype)
          dtype = make_datetimetz(unit, item["timezone"])
          if _pandas_api.is_ge_v21():
              pd_arr = _pandas_api.pd.array(
                  block_arr.view("int64"), dtype=dtype, copy=False
              )
              block = _int.make_block(pd_arr, placement=placement)
          else:
              block = _int.make_block(
                  block_arr,
                  placement=placement,
                  klass=_int.DatetimeTZBlock,
                  dtype=dtype,
              )
      elif "py_array" in item:
          # create ExtensionBlock
          arr = item["py_array"]
          assert len(placement) == 1
          name = columns[placement[0]]
          pandas_dtype = extension_columns[name]
          if not hasattr(pandas_dtype, "__from_arrow__"):
              raise ValueError(
                  "This column does not support to be converted "
                  "to a pandas ExtensionArray"
              )
          pd_ext_arr = pandas_dtype.__from_arrow__(arr)
          block = _int.make_block(pd_ext_arr, placement=placement)
      else:
          block = _int.make_block(block_arr, placement=placement)
  
      return block
  
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 20 for calling a global function with example usage: _reconstruct_block(item, columns, extension_columns) and returns: block