parameters: (arg, unit="ns", errors="raise", name=None)
return_statement: return value
docstring: Convert a list of objects to a timedelta index object.
docstring_summary: Convert a list of objects to a timedelta index object.
docstring_tokens: Convert a list of objects to a timedelta index object .
function: def _convert_listlike(arg, unit="ns", errors="raise", name=None):
      """Convert a list of objects to a timedelta index object."""
  
      if isinstance(arg, (list, tuple)) or not hasattr(arg, "dtype"):
          # This is needed only to ensure that in the case where we end up
          #  returning arg (errors == "ignore"), and where the input is a
          #  generator, we return a useful list-like instead of a
          #  used-up generator
          arg = np.array(list(arg), dtype=object)
  
      try:
          value = sequence_to_td64ns(arg, unit=unit, errors=errors, copy=False)[0]
      except ValueError:
          if errors == "ignore":
              return arg
          else:
              # This else-block accounts for the cases when errors='raise'
              # and errors='coerce'. If errors == 'raise', these errors
              # should be raised. If errors == 'coerce', we shouldn't
              # expect any errors to be raised, since all parsing errors
              # cause coercion to pd.NaT. However, if an error / bug is
              # introduced that causes an Exception to be raised, we would
              # like to surface it.
              raise
  
      from pandas import TimedeltaIndex
  
      value = TimedeltaIndex(value, unit="ns", name=name)
      return value
function_tokens: def _convert_listlike ( arg , unit = "ns" , errors = "raise" , name = None ) : if isinstance ( arg , ( list , tuple ) ) or not hasattr ( arg , "dtype" ) : # This is needed only to ensure that in the case where we end up #  returning arg (errors == "ignore"), and where the input is a #  generator, we return a useful list-like instead of a #  used-up generator arg = np . array ( list ( arg ) , dtype = object ) try : value = sequence_to_td64ns ( arg , unit = unit , errors = errors , copy = False ) [ 0 ] except ValueError : if errors == "ignore" : return arg else : # This else-block accounts for the cases when errors='raise' # and errors='coerce'. If errors == 'raise', these errors # should be raised. If errors == 'coerce', we shouldn't # expect any errors to be raised, since all parsing errors # cause coercion to pd.NaT. However, if an error / bug is # introduced that causes an Exception to be raised, we would # like to surface it. raise from pandas import TimedeltaIndex value = TimedeltaIndex ( value , unit = "ns" , name = name ) return value