code: def _attempt_YYYYMMDD(
      arg: npt.NDArray[np.object_], errors: str
  ) -> np.ndarray | None:
      """
      try to parse the YYYYMMDD/%Y%m%d format, try to deal with NaT-like,
      arg is a passed in as an object dtype, but could really be ints/strings
      with nan-like/or floats (e.g. with nan)
  
      Parameters
      ----------
      arg : np.ndarray[object]
      errors : {'raise','ignore','coerce'}
      """
  
      def calc(carg):
          # calculate the actual result
          carg = carg.astype(object, copy=False)
          parsed = parsing.try_parse_year_month_day(
              carg / 10000, carg / 100 % 100, carg % 100
          )
          return tslib.array_to_datetime(parsed, errors=errors)[0]
  
      def calc_with_mask(carg, mask):
          result = np.empty(carg.shape, dtype="M8[ns]")
          iresult = result.view("i8")
          iresult[~mask] = iNaT
  
          masked_result = calc(
              carg[mask].astype(np.float64).astype(np.int64)
          )
          result[mask] = masked_result.astype("M8[ns]")
          return result
  
      # try intlike / strings that are ints
      try:
          return calc(arg.astype(np.int64))
      except (ValueError, OverflowError, TypeError):
          pass
  
      # a float with actual np.nan
      try:
          carg = arg.astype(np.float64)
          return calc_with_mask(carg, notna(carg))
      except (ValueError, OverflowError, TypeError):
          pass
  
      # string with NaN-like
      try:
          # error: Argument 2 to "isin" has incompatible type "List[Any]"; expected
          # "Union[Union[ExtensionArray, ndarray], Index, Series]"
          mask = ~algorithms.isin(arg, list(nat_strings))  # type: ignore[arg-type]
          return calc_with_mask(arg, mask)
      except (ValueError, OverflowError, TypeError):
          pass
  
      return None
  
imports: from __future__ import annotations
  from collections import abc
  from datetime import datetime
  from functools import partial
  from itertools import islice
  from typing import TYPE_CHECKING, Callable, Hashable, List, Tuple, TypedDict, Union, cast, overload
  import warnings
  import numpy
  from pandas._libs import lib, tslib
  from pandas._libs.tslibs import OutOfBoundsDatetime, Timedelta, Timestamp, astype_overflowsafe, get_unit_from_dtype, iNaT, is_supported_unit, nat_strings, parsing, timezones
  from pandas._libs.tslibs.conversion import precision_from_unit
  from pandas._libs.tslibs.parsing import DateParseError, guess_datetime_format
  from pandas._libs.tslibs.strptime import array_strptime
  from pandas._typing import AnyArrayLike, ArrayLike, DateTimeErrorChoices, npt
  from pandas.util._exceptions import find_stack_level
  from pandas.core.dtypes.common import ensure_object, is_datetime64_dtype, is_datetime64tz_dtype, is_float, is_integer, is_integer_dtype, is_list_like, is_numeric_dtype, is_scalar
  from pandas.core.dtypes.generic import ABCDataFrame, ABCSeries
  from pandas.core.dtypes.missing import notna
  from pandas.arrays import DatetimeArray, IntegerArray, PandasArray
  from pandas.core import algorithms
  from pandas.core.algorithms import unique
  from pandas.core.arrays.base import ExtensionArray
  from pandas.core.arrays.datetimes import maybe_convert_dtype, objects_to_datetime64ns, tz_to_dtype
  from pandas.core.construction import extract_array
  from pandas.core.indexes.base import Index
  from pandas.core.indexes.datetimes import DatetimeIndex
label_desc: Use image node_id 16 for calling a global function with example usage: _attempt_YYYYMMDD(arg, errors) and returns: None, tslib, result, calc, calc_with_mask, calc_with_mask