code: def uniform(start, end=None, periods=None, freq=None, sc=None):
      
      dtmodule = sc._jvm.com.cloudera.sparkts.__getattr__('DateTimeIndex$').__getattr__('MODULE$')
      if freq is None:
          raise ValueError("Missing frequency")
      elif end is None and periods == None:
          raise ValueError("Need an end date or number of periods")
      elif end is not None:
          return DateTimeIndex(dtmodule.uniformFromInterval( \
              datetime_to_nanos(start), datetime_to_nanos(end), freq._jfreq))
      else:
          return DateTimeIndex(dtmodule.uniform( \
              datetime_to_nanos(start), periods, freq._jfreq))
docs: Instantiates a uniform DateTimeIndex.
  
      Either end or periods must be specified.
      
      Parameters
      ----------
          start : string, long (nanos from epoch), or Pandas Timestamp
          end : string, long (nanos from epoch), or Pandas Timestamp
          periods : int
          freq : a frequency object
          sc : SparkContext