code: def _convert_and_box_cache(arg, cache_array, box, errors, name=None):
      """
      Convert array of dates with a cache and box the result
  
      Parameters
      ----------
      arg : integer, float, string, datetime, list, tuple, 1-d array, Series
      cache_array : Series
          Cache of converted, unique dates
      box : boolean
          True boxes result as an Index-like, False returns an ndarray
      errors : string
          'ignore' plus box=True will convert result to Index
      name : string, default None
          Name for a DatetimeIndex
  
      Returns
      -------
      result : datetime of converted dates
          Returns:
  
          - Index-like if box=True
          - ndarray if box=False
      """
      from pandas import Series, DatetimeIndex, Index
  
      result = Series(arg).map(cache_array)
      if box:
          if errors == "ignore":
              return Index(result, name=name)
          else:
              return DatetimeIndex(result, name=name)
      return result.values
  
imports: from datetime import datetime, time
  from functools import partial
  import numpy
  from pandas._libs import tslib, tslibs
  from pandas._libs.tslibs import Timestamp, conversion, parsing
  from pandas._libs.tslibs.parsing import DateParseError, _format_is_iso, _guess_datetime_format, parse_time_string
  from pandas._libs.tslibs.strptime import array_strptime
  from pandas.compat import zip
  from pandas.core.dtypes.common import ensure_object, is_datetime64_dtype, is_datetime64_ns_dtype, is_datetime64tz_dtype, is_float, is_integer, is_integer_dtype, is_list_like, is_numeric_dtype, is_object_dtype, is_scalar
  from pandas.core.dtypes.generic import ABCDataFrame, ABCIndexClass, ABCSeries
  from pandas.core.dtypes.missing import notna
  from pandas import compat
  from pandas.core import algorithms
label_desc: Use image node_id 3 for calling a global function with example usage: _convert_and_box_cache(arg, cache_array, box, errors, name) and returns: result, Index, DatetimeIndex