code: def _dict_from_terse_tabular(
          names: List[str],
          inp: str,
          transformers: Dict[str, Callable[[str], Any]] = {})\
          -> List[Dict[str, Any]]:
      
      res = []
      for n in names:
          if n not in transformers:
              transformers[n] = lambda s: s
      for line in inp.split('\n'):
          if len(line) < 3:
              continue
          fields = line.split(':')
          res.append(dict([
              (elem[0], transformers[elem[0]](elem[1]))
              for elem in zip(names, fields)]))
      return res
docs: Parse NMCLI terse tabular output into a list of Python dict.
  
      ``names`` is a list of strings of field names to apply to the input data,
      which is assumed to be colon separated.
  
      ``inp`` is the input as a string (i.e. already decode()d) from nmcli
  
      ``transformers`` is a dict mapping field names to callables of the form
      f: str -> any. If a fieldname is in transformers, that callable will be
      invoked on the field matching the name and the result stored.
  
      The return value is a list with one element per valid line of input, where
      each element is a dict with keys taken from names and values from the input