code: def find_expectation_indexes(self,
                                   expectation_type=None,
                                   column=None,
                                   expectation_kwargs=None
                                   ):
          
          if expectation_kwargs == None:
              expectation_kwargs = {}
  
          if "column" in expectation_kwargs and column != None and column != expectation_kwargs["column"]:
              raise ValueError("Conflicting column names in remove_expectation: %s and %s" % (
                  column, expectation_kwargs["column"]))
  
          if column != None:
              expectation_kwargs["column"] = column
  
          match_indexes = []
          for i, exp in enumerate(self._expectations_config.expectations):
              if expectation_type == None or (expectation_type == exp['expectation_type']):
                  # if column == None or ('column' not in exp['kwargs']) or (exp['kwargs']['column'] == column) or (exp['kwargs']['column']==:
                  match = True
  
                  for k, v in expectation_kwargs.items():
                      if k in exp['kwargs'] and exp['kwargs'][k] == v:
                          continue
                      else:
                          match = False
  
                  if match:
                      match_indexes.append(i)
  
          return match_indexes
docs: Find matching expectations within _expectation_config.
          Args:
              expectation_type=None                : The name of the expectation type to be matched.
              column=None                          : The name of the column to be matched.
              expectation_kwargs=None              : A dictionary of kwargs to match against.
  
          Returns:
              A list of indexes for matching expectation objects.
              If there are no matches, the list will be empty.