code: def construct_1d_object_array_from_listlike(values):
      """
      Transform any list-like object in a 1-dimensional numpy array of object
      dtype.
  
      Parameters
      ----------
      values : any iterable which has a len()
  
      Raises
      ------
      TypeError
          * If `values` does not have a len()
  
      Returns
      -------
      1-dimensional numpy array of dtype object
      """
      # numpy will try to interpret nested lists as further dimensions, hence
      # making a 1D array that contains list-likes is a bit tricky:
      result = np.empty(len(values), dtype="object")
      result[:] = values
      return result
  
imports: from datetime import datetime, timedelta
  import numpy
  from pandas._libs import lib, tslib, tslibs
  from pandas._libs.tslibs import NaT, OutOfBoundsDatetime, Period, iNaT
  from pandas.compat import PY3, string_types, text_type, to_str
  from .common import _INT64_DTYPE, _NS_DTYPE, _POSSIBLY_CAST_DTYPES, _TD_DTYPE, ensure_int8, ensure_int16, ensure_int32, ensure_int64, ensure_object, is_bool, is_bool_dtype, is_categorical_dtype, is_complex, is_complex_dtype, is_datetime64_dtype, is_datetime64_ns_dtype, is_datetime64tz_dtype, is_datetime_or_timedelta_dtype, is_datetimelike, is_dtype_equal, is_extension_array_dtype, is_extension_type, is_float, is_float_dtype, is_integer, is_integer_dtype, is_object_dtype, is_scalar, is_string_dtype, is_timedelta64_dtype, is_timedelta64_ns_dtype, is_unsigned_integer_dtype, pandas_dtype
  from .dtypes import DatetimeTZDtype, ExtensionDtype, PandasExtensionDtype, PeriodDtype
  from .generic import ABCDatetimeArray, ABCDatetimeIndex, ABCPeriodArray, ABCPeriodIndex, ABCSeries
  from .inference import is_list_like
  from .missing import isna, notna
label_desc: Use image node_id 24 for calling a global function with example usage: construct_1d_object_array_from_listlike(values) and returns: result