How to use the pprofile.ProfileBase function in pprofile

def __init__(self, **kw):
        super(ThreadProfile, self).__init__(**kw)
        self._local_trace_backup = self._local_trace

    def _enable(self):
        self._local_trace = self._local_trace_backup
        threading.settrace(self._global_trace)
        super(ThreadProfile, self)._enable()

    def _disable(self):
        super(ThreadProfile, self)._disable()
        threading.settrace(None)
        self._local_trace = None

class StatisticProfile(ProfileBase, ProfileRunnerBase):
    """
    Statistic profiling class.

    This class does not gather its own samples by itself.
    Instead, it must be provided with call stacks (as returned by
    sys._getframe() or sys._current_frames()).
    """
    def __init__(self):
        super(StatisticProfile, self).__init__()
        self.total_time = 1

    def sample(self, frame):
        getFileTiming = self._getFileTiming
        called_timing = getFileTiming(frame)
        called_code = frame.f_code
        called_timing.hit(called_code, frame.f_lineno, 0)

sys.path[:] = original_sys_path

    def runmodule(self, module, argv):
        original_sys_argv = list(sys.argv)
        original_sys_path0 = sys.path[0]
        try:
            sys.path[0] = os.getcwd()
            sys.argv[:] = argv
            with self():
                runpy.run_module(module, run_name='__main__', alter_sys=True)
        finally:
            sys.argv[:] = original_sys_argv
            sys.path[0] = original_sys_path0
        return self

class Profile(ProfileBase, ProfileRunnerBase):
    """
    Deterministic, recursive, line-granularity, profiling class.

    Does not require any source code change to work.
    If the performance hit is too large, it can benefit from some
    integration (calling enable/disable around selected code chunks).

    The sum of time spent in all profiled lines is less than the total
    profiled time reported. This is (part of) profiling overhead.
    This also mans that sum of time-spent-on-line percentage is less than 100%.

    All times are "internal time", ie they do not count time spent inside
    called (profilable, so python) functions.
    """
    __slots__ = (
        '_global_trace',