scoring_diagnostics.py

class ScoringDiagnostics:
    """評分系統診斷工具類"""
    
    def __init__(self, log_dir="scoring_diagnostics"):
        """
        初始化診斷工具
        
        參數:
        log_dir (str): 日誌文件存放目錄
        """
        self.log_dir = log_dir
        self._ensure_log_directory()
        self.current_session = datetime.now().strftime("%Y%m%d_%H%M%S")
        
    def _ensure_log_directory(self):
        """確保日誌目錄存在"""
        if not os.path.exists(self.log_dir):
            os.makedirs(self.log_dir)
            
    def _create_log_filename(self, prefix):
        """生成日誌文件名"""
        return os.path.join(
            self.log_dir, 
            f"{prefix}_{self.current_session}.json"
        )
    
    def diagnostic_wrapper(self, original_func):
        """
        包裝原始評分函數的診斷裝飾器
        
        使用方式:
        @scoring_diagnostics.diagnostic_wrapper
        def calculate_compatibility_score(breed_info, user_prefs):
            ...
        """
        @wraps(original_func)
        def wrapper(breed_info, user_prefs, *args, **kwargs):
            # 準備診斷信息
            diagnostic_info = {
                "timestamp": datetime.now().isoformat(),
                "breed": breed_info.get('Breed', 'Unknown'),
                "input_data": {
                    "breed_info": breed_info,
                    "user_preferences": vars(user_prefs)
                }
            }
            
            try:
                # 執行原始函數
                result = original_func(breed_info, user_prefs, *args, **kwargs)
                
                # 記錄成功結果
                diagnostic_info.update({
                    "status": "success",
                    "result": result
                })
                
                # 檢查是否所有分數都相同或接近預設值
                scores = [v for k, v in result.items() if k != 'overall']
                if all(abs(score - 0.5) < 0.1 for score in scores):
                    diagnostic_info["warnings"] = {
                        "type": "uniform_scores",
                        "message": "所有分數都接近預設值 0.5",
                        "scores": scores
                    }
                
            except Exception as e:
                # 記錄錯誤信息
                diagnostic_info.update({
                    "status": "error",
                    "error": {
                        "type": str(type(e).__name__),
                        "message": str(e),
                        "traceback": traceback.format_exc()
                    }
                })
                raise  # 重新拋出異常
            
            finally:
                # 保存診斷信息
                self._save_diagnostic_info(diagnostic_info)
            
            return result
        
        return wrapper
    
    def _save_diagnostic_info(self, diagnostic_info):
        """保存診斷信息到文件"""
        filename = self._create_log_filename("scoring_diagnostic")
        try:
            # 如果文件存在，讀取現有記錄
            if os.path.exists(filename):
                with open(filename, 'r', encoding='utf-8') as f:
                    records = json.load(f)
            else:
                records = []
            
            # 添加新記錄
            records.append(diagnostic_info)
            
            # 保存所有記錄
            with open(filename, 'w', encoding='utf-8') as f:
                json.dump(records, f, ensure_ascii=False, indent=2)
                
        except Exception as e:
            print(f"保存診斷信息時發生錯誤: {str(e)}")
    
    def analyze_diagnostics(self):
        """分析診斷結果並生成報告"""
        try:
            filename = self._create_log_filename("scoring_diagnostic")
            if not os.path.exists(filename):
                return "沒有找到診斷記錄"
            
            with open(filename, 'r', encoding='utf-8') as f:
                records = json.load(f)
            
            # 分析結果
            analysis = {
                "total_records": len(records),
                "success_count": sum(1 for r in records if r["status"] == "success"),
                "error_count": sum(1 for r in records if r["status"] == "error"),
                "uniform_scores_count": sum(1 for r in records if "warnings" in r and 
                                         r["warnings"]["type"] == "uniform_scores"),
                "error_types": {}
            }
            
            # 統計錯誤類型
            for record in records:
                if record["status"] == "error":
                    error_type = record["error"]["type"]
                    analysis["error_types"][error_type] = analysis["error_types"].get(error_type, 0) + 1
            
            return analysis
            
        except Exception as e:
            return f"分析診斷記錄時發生錯誤: {str(e)}"