code: def get_close_matches(word, possibilities, n=3, cutoff=0.6):
      """Use SequenceMatcher to return list of the best "good enough" matches.
  
      word is a sequence for which close matches are desired (typically a
      string).
  
      possibilities is a list of sequences against which to match word
      (typically a list of strings).
  
      Optional arg n (default 3) is the maximum number of close matches to
      return.  n must be > 0.
  
      Optional arg cutoff (default 0.6) is a float in [0, 1].  Possibilities
      that don't score at least that similar to word are ignored.
  
      The best (no more than n) matches among the possibilities are returned
      in a list, sorted by similarity score, most similar first.
  
      >>> get_close_matches("appel", ["ape", "apple", "peach", "puppy"])
      ['apple', 'ape']
      >>> import keyword as _keyword
      >>> get_close_matches("wheel", _keyword.kwlist)
      ['while']
      >>> get_close_matches("Apple", _keyword.kwlist)
      []
      >>> get_close_matches("accept", _keyword.kwlist)
      ['except']
      """
  
      if not n > 0:
          raise ValueError("n must be > 0: %r" % (n,))
      if not 0.0 <= cutoff <= 1.0:
          raise ValueError(
              "cutoff must be in [0.0, 1.0]: %r" % (cutoff,)
          )
      result = []
      s = SequenceMatcher()
      s.set_seq2(word)
      for x in possibilities:
          s.set_seq1(x)
          if (
              s.real_quick_ratio() >= cutoff
              and s.quick_ratio() >= cutoff
              and s.ratio() >= cutoff
          ):
              result.append((s.ratio(), x))
  
      # Move the best scorers to head of list
      result = _nlargest(n, result)
      # Strip scores for the best n matches
      return [x for score, x in result]
  
imports: from heapq import nlargest
  from collections import namedtuple
  from types import GenericAlias
  import re
label_desc: Use image node_id 2 for calling a global function with example usage: get_close_matches(word, possibilities, n, cutoff) and returns: unknown