code: def is_all_strings(value: ArrayLike) -> bool:
      """
      Check if this is an array of strings that we should try parsing.
  
      Includes object-dtype ndarray containing all-strings, StringArray,
      and Categorical with all-string categories.
      Does not include numpy string dtypes.
      """
      dtype = value.dtype
  
      if isinstance(dtype, np.dtype):
          if len(value) == 0:
              return dtype == np.dtype("object")
          else:
              return dtype == np.dtype(
                  "object"
              ) and lib.is_string_array(np.asarray(value), skipna=False)
      elif isinstance(dtype, CategoricalDtype):
          return dtype.categories.inferred_type == "string"
      return dtype == "string"
  
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, Any, Callable
  import warnings
  import numpy
  from pandas._libs import Interval, Period, algos, lib
  from pandas._libs.tslibs import conversion
  from pandas.util._exceptions import find_stack_level
  from pandas.core.dtypes.base import _registry
  from pandas.core.dtypes.dtypes import CategoricalDtype, DatetimeTZDtype, ExtensionDtype, IntervalDtype, PeriodDtype, SparseDtype
  from pandas.core.dtypes.generic import ABCIndex
  from pandas.core.dtypes.inference import is_array_like, is_bool, is_complex, is_dataclass, is_decimal, is_dict_like, is_file_like, is_float, is_hashable, is_integer, is_interval, is_iterator, is_list_like, is_named_tuple, is_nested_list_like, is_number, is_re, is_re_compilable, is_scalar, is_sequence
label_desc: Use image node_id 41 for calling a global function with example usage: is_all_strings(value) and returns: unknown, unknown, unknown, unknown