code: def index(data: Data, offset: int = 0) -> Data:
      if isIndexed(data, offset):
          return data
      else:
          data = dict(zip(itertools.count(offset), data.values()))
          return data
  
imports: from __future__ import annotations
  import collections
  import functools
  import itertools
  import multiprocessing
  import multiprocessing.dummy
  import os
  import queue
  import tempfile
  from typing import TYPE_CHECKING, overload
  import numpy
  from dedupe.backport import RLock
label_desc: Use image node_id 7 for calling a global function with example usage: index(data, offset) and returns: data, data