code: def hash_memoize_helper(v: Any) -> str:
      if isinstance(v, dict):
          rolling = "{"
          for k2, v2 in v.items():
              rolling += f"{k2}:{hash_memoize_helper(v2)},"
          rolling += "}"
      elif isinstance(v, ModelDict):
          rolling = "{"
          for k2, v2 in v.items():
              rolling += f"{k2}:{hash_memoize_helper(v2)},"
          rolling += "}"
      elif isinstance(v, list):
          rolling = "["
          for i in v:
              rolling += f"{hash_memoize_helper(i)},"
          rolling += "]"
      elif isinstance(v, tuple):
          rolling = "("
          for i in v:
              rolling += f"{hash_memoize_helper(i)},"
          rolling += ")"
      elif isinstance(v, bool):
          rolling = "T" if v else "F"
      elif isinstance(v, int):
          rolling = str(v)
      elif isinstance(v, float):
          rolling = str(v)
      elif isinstance(v, str):
          rolling = v
      elif v is None:
          rolling = "N"
      elif isinstance(v, pd.DataFrame):
          rolling = hash_pdf(v)
      else:
          raise TypeError(f"Unsupported memoization type: {type(v)}")
  
      return rolling
  
imports: import hashlib
  import json
  import logging
  import os
  import pandas
  import pandas.util
  import platform
  import random
  import string
  import uuid
  import warnings
  from functools import lru_cache
  from typing import Any
  from collections import UserDict
  from .constants import VERBOSE, CACHE_COERCION_SIZE, TRACE
label_desc: Use image node_id 6 for calling a global function with example usage: hash_memoize_helper(v) and returns: rolling