class_docstr: Compute the Jaccard similarity between the two sequences.
  They should contain hashable items.
  The return value is a float between 0 and 1, where 1 means equal,
  and 0 totally different.
  
  https://en.wikipedia.org/wiki/Jaccard_index
  https://github.com/Yomguithereal/talisman/blob/master/src/metrics/jaccard.js
class_docstr_tok: ["Compute","the","Jaccard","similarity","between","the","two","sequences",".","They","should","contain","hashable","items",".","The","return","value","is","a","float","between","0","and","1",",","where","1","means","equal",",","and","0","totally","different",".","https",":","\/\/en.wikipedia.org\/wiki\/Jaccard_index","https",":","\/\/github.com\/Yomguithereal\/talisman\/blob\/master\/src\/metrics\/jaccard.js"]
code: def maximum(self, *sequences: Sequence) -> int:
      return 1
  
imports: from __future__ import annotations
  from functools import reduce
  from itertools import islice, permutations, repeat
  from math import log
  from typing import Sequence
  from .base import Base, BaseSimilarity
  from .edit_based import DamerauLevenshtein
label_desc: Use image node_id 2 for calling the Jaccard obj's underlying member method code with example usage: obj.maximum() and returns: int