Method print_stats

Lib/profiling/sampling/pstats_collector.py:88–255

Print formatted statistics to stdout.

(self, sort=-1, limit=None, show_summary=True, mode=None)

            )

    def print_stats(self, sort=-1, limit=None, show_summary=True, mode=None):
        """Print formatted statistics to stdout."""
        # Create stats object
        stats = pstats.SampledStats(self).strip_dirs()
        if not stats.stats:
            print("No samples were collected.")
            if mode == PROFILING_MODE_CPU:
                print("This can happen in CPU mode when all threads are idle.")
            return

        # Get the stats data
        stats_list = []
        for func, (
            direct_calls,
            cumulative_calls,
            total_time,
            cumulative_time,
            callers,
        ) in stats.stats.items():
            stats_list.append(
                (
                    func,
                    direct_calls,
                    cumulative_calls,
                    total_time,
                    cumulative_time,
                    callers,
                )
            )

        # Calculate total samples for percentage calculations (using direct_calls)
        total_samples = sum(
            direct_calls for _, direct_calls, _, _, _, _ in stats_list
        )

        # Sort based on the requested field
        sort_field = sort
        if sort_field == -1:  # stdname
            stats_list.sort(key=lambda x: str(x[0]))
        elif sort_field == 0:  # nsamples (direct samples)
            stats_list.sort(key=lambda x: x[1], reverse=True)  # direct_calls
        elif sort_field == 1:  # tottime
            stats_list.sort(key=lambda x: x[3], reverse=True)  # total_time
        elif sort_field == 2:  # cumtime
            stats_list.sort(key=lambda x: x[4], reverse=True)  # cumulative_time
        elif sort_field == 3:  # sample%
            stats_list.sort(
                key=lambda x: (x[1] / total_samples * 100)
                if total_samples > 0
                else 0,
                reverse=True,  # direct_calls percentage
            )
        elif sort_field == 4:  # cumul%
            stats_list.sort(
                key=lambda x: (x[2] / total_samples * 100)
                if total_samples > 0
                else 0,
                reverse=True,  # cumulative_calls percentage