import time
import psutil
import os
from typing import Dict, Any, Callable
from functools import wraps

class PerformanceMonitor:
    """性能监控器"""
    
    def __init__(self):
        self.metrics = {}
        self.start_time = time.time()
    
    def start_monitoring(self):
        """开始监控"""
        self.start_time = time.time()
        self.initial_memory = psutil.Process(os.getpid()).memory_info().rss
    
    def stop_monitoring(self) -> Dict[str, Any]:
        """停止监控并返回性能指标"""
        end_time = time.time()
        final_memory = psutil.Process(os.getpid()).memory_info().rss
        
        metrics = {
            "execution_time": end_time - self.start_time,
            "memory_used": final_memory - self.initial_memory,
            "peak_memory": final_memory
        }
        
        return metrics
    
    def monitor_function(self, func: Callable) -> Callable:
        """装饰器：监控函数性能"""
        @wraps(func)
        def wrapper(*args, **kwargs):
            # 记录开始时间
            start_time = time.time()
            start_memory = psutil.Process(os.getpid()).memory_info().rss
            
            try:
                # 执行函数
                result = func(*args, **kwargs)
                return result
            finally:
                # 记录结束时间
                end_time = time.time()
                end_memory = psutil.Process(os.getpid()).memory_info().rss
                
                # 记录指标
                func_name = func.__name__
                if func_name not in self.metrics:
                    self.metrics[func_name] = {
                        "call_count": 0,
                        "total_time": 0,
                        "total_memory": 0
                    }
                
                self.metrics[func_name]["call_count"] += 1
                self.metrics[func_name]["total_time"] += (end_time - start_time)
                self.metrics[func_name]["total_memory"] += (end_memory - start_memory)
        
        return wrapper
    
    def get_metrics_report(self) -> str:
        """获取性能指标报告"""
        if not self.metrics:
            return "暂无性能数据"
        
        report = "性能指标报告:\n"
        report += "=" * 50 + "\n"
        
        for func_name, metrics in self.metrics.items():
            avg_time = metrics["total_time"] / metrics["call_count"]
            avg_memory = metrics["total_memory"] / metrics["call_count"]
            
            report += f"函数: {func_name}\n"
            report += f"  调用次数: {metrics['call_count']}\n"
            report += f"  总执行时间: {metrics['total_time']:.4f}s\n"
            report += f"  平均执行时间: {avg_time:.4f}s\n"
            report += f"  总内存使用: {metrics['total_memory'] / 1024 / 1024:.2f}MB\n"
            report += f"  平均内存使用: {avg_memory / 1024 / 1024:.2f}MB\n"
            report += "-" * 30 + "\n"
        
        return report

# 创建全局性能监控器实例
perf_monitor = PerformanceMonitor()