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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 _on_iteration(self, *args, **kwargs) -> None: """ Called at each iteration. This function does time measurements, updates timing in the monitoring context and calls all monitoring tasks. """


        # Update timing and the iteration number in the monitoring context.
        current_timestamp = get_hr_time()
        self._context.optimisation_time += current_timestamp - self._last_timestamp
        self._context.total_time = current_timestamp - self._start_timestamp
        self._context.optimiser_updated = False
        if not self._context.optimisation_finished:
            self._context.iteration_no += 1

        # Call all monitoring functions
        for func in self._monitor_tasks:
            func(self._context, *args, **kwargs)

        # Remember the time when the control is returned back to the optimiser, so that the next
        # optimisation step can be accurately timed.
        self._last_timestamp = get_hr_time()