class_docstr: Represents a basic subset object.
  
  Explanation
  ===========
  
  We generate subsets using essentially two techniques,
  binary enumeration and lexicographic enumeration.
  The Subset class takes two arguments, the first one
  describes the initial subset to consider and the second
  describes the superset.
  
  Examples
  ========
  
  >>> from sympy.combinatorics import Subset
  >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd'])
  >>> a.next_binary().subset
  ['b']
  >>> a.prev_binary().subset
  ['c']
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docstr: Gets the bitlist corresponding to a subset.
  
  Examples
  ========
  
  >>> from sympy.combinatorics import Subset
  >>> Subset.bitlist_from_subset(['c', 'd'], ['a', 'b', 'c', 'd'])
  '0011'
  
  See Also
  ========
  
  subset_from_bitlist
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code: def bitlist_from_subset(self, subset, superset):
      """
      Gets the bitlist corresponding to a subset.
  
      Examples
      ========
  
      >>> from sympy.combinatorics import Subset
      >>> Subset.bitlist_from_subset(['c', 'd'], ['a', 'b', 'c', 'd'])
      '0011'
  
      See Also
      ========
  
      subset_from_bitlist
      """
      bitlist = ["0"] * len(superset)
      if isinstance(subset, Subset):
          subset = subset.subset
      for i in Subset.subset_indices(subset, superset):
          bitlist[i] = "1"
      return "".join(bitlist)
  
imports: from itertools import combinations
  from sympy.combinatorics.graycode import GrayCode
label_desc: Use image node_id 20 for calling the Subset obj's underlying member method code with example usage: obj.bitlist_from_subset(subset, superset) and returns: str