Spaces:
Running
on
Zero
Running
on
Zero
Create scoring_diagnostics.py
Browse files- scoring_diagnostics.py +137 -0
scoring_diagnostics.py
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class ScoringDiagnostics:
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"""評分系統診斷工具類"""
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def __init__(self, log_dir="scoring_diagnostics"):
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"""
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初始化診斷工具
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參數:
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log_dir (str): 日誌文件存放目錄
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"""
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self.log_dir = log_dir
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self._ensure_log_directory()
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self.current_session = datetime.now().strftime("%Y%m%d_%H%M%S")
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def _ensure_log_directory(self):
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"""確保日誌目錄存在"""
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if not os.path.exists(self.log_dir):
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os.makedirs(self.log_dir)
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def _create_log_filename(self, prefix):
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"""生成日誌文件名"""
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return os.path.join(
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self.log_dir,
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f"{prefix}_{self.current_session}.json"
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)
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def diagnostic_wrapper(self, original_func):
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"""
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包裝原始評分函數的診斷裝飾器
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使用方式:
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@scoring_diagnostics.diagnostic_wrapper
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def calculate_compatibility_score(breed_info, user_prefs):
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...
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"""
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@wraps(original_func)
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def wrapper(breed_info, user_prefs, *args, **kwargs):
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# 準備診斷信息
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diagnostic_info = {
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"timestamp": datetime.now().isoformat(),
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"breed": breed_info.get('Breed', 'Unknown'),
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"input_data": {
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"breed_info": breed_info,
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"user_preferences": vars(user_prefs)
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}
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}
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try:
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# 執行原始函數
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result = original_func(breed_info, user_prefs, *args, **kwargs)
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# 記錄成功結果
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diagnostic_info.update({
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"status": "success",
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"result": result
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})
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# 檢查是否所有分數都相同或接近預設值
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scores = [v for k, v in result.items() if k != 'overall']
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if all(abs(score - 0.5) < 0.1 for score in scores):
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diagnostic_info["warnings"] = {
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"type": "uniform_scores",
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"message": "所有分數都接近預設值 0.5",
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"scores": scores
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}
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except Exception as e:
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# 記錄錯誤信息
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diagnostic_info.update({
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"status": "error",
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"error": {
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"type": str(type(e).__name__),
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"message": str(e),
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"traceback": traceback.format_exc()
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}
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})
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raise # 重新拋出異常
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finally:
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# 保存診斷信息
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self._save_diagnostic_info(diagnostic_info)
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return result
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return wrapper
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def _save_diagnostic_info(self, diagnostic_info):
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"""保存診斷信息到文件"""
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filename = self._create_log_filename("scoring_diagnostic")
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try:
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# 如果文件存在,讀取現有記錄
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if os.path.exists(filename):
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with open(filename, 'r', encoding='utf-8') as f:
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records = json.load(f)
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else:
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records = []
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# 添加新記錄
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records.append(diagnostic_info)
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# 保存所有記錄
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with open(filename, 'w', encoding='utf-8') as f:
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json.dump(records, f, ensure_ascii=False, indent=2)
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except Exception as e:
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print(f"保存診斷信息時發生錯誤: {str(e)}")
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def analyze_diagnostics(self):
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"""分析診斷結果並生成報告"""
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try:
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filename = self._create_log_filename("scoring_diagnostic")
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if not os.path.exists(filename):
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return "沒有找到診斷記錄"
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with open(filename, 'r', encoding='utf-8') as f:
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records = json.load(f)
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# 分析結果
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analysis = {
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"total_records": len(records),
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"success_count": sum(1 for r in records if r["status"] == "success"),
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"error_count": sum(1 for r in records if r["status"] == "error"),
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"uniform_scores_count": sum(1 for r in records if "warnings" in r and
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r["warnings"]["type"] == "uniform_scores"),
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"error_types": {}
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}
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# 統計錯誤類型
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for record in records:
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if record["status"] == "error":
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error_type = record["error"]["type"]
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analysis["error_types"][error_type] = analysis["error_types"].get(error_type, 0) + 1
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return analysis
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except Exception as e:
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return f"分析診斷記錄時發生錯誤: {str(e)}"
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