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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def uniform(start, end=None, periods=None, freq=None, sc=None):
 """ 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 """

    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))