Method stop_monitoring

benchmarks/frameworks/common.py:167–194

Stop monitoring and return collected metrics.

(self)

        self.initial_memory_trace = tracemalloc.get_traced_memory()[0]

    def stop_monitoring(self) -> BenchmarkMetrics:
        """Stop monitoring and return collected metrics."""
        end_time = time.perf_counter()
        end_memory = self.process.memory_info().rss / 1024 / 1024  # MB
        end_cpu_times = self.process.cpu_times()

        current_memory, peak_memory = tracemalloc.get_traced_memory()
        tracemalloc.stop()

        # Calculate metrics
        execution_time_ms = (end_time - self.start_time) * 1000
        memory_usage_mb = end_memory - self.start_memory

        # Calculate CPU usage (approximate)
        cpu_time_used = (end_cpu_times.user - self.start_cpu_times.user) + (end_cpu_times.system - self.start_cpu_times.system)
        wall_time = end_time - self.start_time
        cpu_usage_percent = (cpu_time_used / wall_time) * 100 if wall_time > 0 else 0

        return BenchmarkMetrics(
            execution_time_ms=execution_time_ms,
            memory_usage_mb=memory_usage_mb,
            cpu_usage_percent=cpu_usage_percent,
            latency_ms=execution_time_ms,  # Same as execution time for single tasks
            metadata={
                "peak_memory_mb": peak_memory / 1024 / 1024,
                "memory_delta_mb": (current_memory - self.initial_memory_trace) / 1024 / 1024,
            },
        )


class BaseBenchmark(ABC):