class_docstr: This implements a lazily calculated DFA where states
  are labelled by some string that reaches them, and are
  distinguished by a membership test and a set of experiments.
code: def __init__(self, lstar):
      super().__init__()
      self.__lstar = lstar
      self.__generation = lstar.generation
  
imports: from bisect import bisect_right, insort
  from collections import Counter
  import attr
  from hypothesis.errors import InvalidState
  from hypothesis.internal.conjecture.dfa import DFA, cached
  from hypothesis.internal.conjecture.junkdrawer import IntList, NotFound, SelfOrganisingList, find_integer
label_desc: Use image node_id 1 to create a new LearnedDFA object from inherited base classes: DFA with example: obj = LearnedDFA(lstar)