parameters: (
      arg: DatetimeScalarOrArrayConvertible,
      cache_array: ABCSeries,
      name: Optional[str] = None,
  )
return_statement: return _box_as_indexlike(result, utc=None, name=name)
docstring: Convert array of dates with a cache and wrap the result in an Index.
  
      Parameters
      ----------
      arg : integer, float, string, datetime, list, tuple, 1-d array, Series
      cache_array : Series
          Cache of converted, unique dates
      name : string, default None
          Name for a DatetimeIndex
  
      Returns
      -------
      result : Index-like of converted dates
docstring_summary: Convert array of dates with a cache and wrap the result in an Index.
docstring_tokens: Convert array of dates with a cache and wrap the result in an Index .
function: def _convert_and_box_cache(
      arg: DatetimeScalarOrArrayConvertible,
      cache_array: ABCSeries,
      name: Optional[str] = None,
  ) -> ABCIndexClass:
      """
      Convert array of dates with a cache and wrap the result in an Index.
  
      Parameters
      ----------
      arg : integer, float, string, datetime, list, tuple, 1-d array, Series
      cache_array : Series
          Cache of converted, unique dates
      name : string, default None
          Name for a DatetimeIndex
  
      Returns
      -------
      result : Index-like of converted dates
      """
      from pandas import Series
  
      result = Series(arg).map(cache_array)
      return _box_as_indexlike(result, utc=None, name=name)
function_tokens: def _convert_and_box_cache ( arg : DatetimeScalarOrArrayConvertible , cache_array : ABCSeries , name : Optional [ str ] = None , ) -> ABCIndexClass : from pandas import Series result = Series ( arg ) . map ( cache_array ) return _box_as_indexlike ( result , utc = None , name = name )