From 7bc40604c39d50ca5afcbee81e2b1e2fceda3912 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E4=B8=AD=E5=A4=A7=E6=B7=98=E6=B2=99?=
 <yahyawen@tencent.com>
Date: Fri, 3 Apr 2026 16:11:31 +0800
Subject: [PATCH] modify tperf.py for parsing error

---
 tperf.py | 34 +++++++++++++++++++++++++++++++---
 1 file changed, 31 insertions(+), 3 deletions(-)

diff --git a/tperf.py b/tperf.py
index 14c2567..fd9f38c 100755
--- a/tperf.py
+++ b/tperf.py
@@ -394,6 +394,13 @@ def summary_result(data: dict, base: dict) -> dict:
         "score": 0,
     }
     for tc in data:
+        if tc not in base:
+            warn(f"基准数据中缺少用例 {tc}，跳过该用例的评分汇总（请更新 base.json 或指定 -b）")
+            continue
+        base_results = base[tc].get("result")
+        if not isinstance(base_results, dict):
+            warn(f"基准数据中用例 {tc} 的 result 无效，跳过")
+            continue
         for item in data[tc]["result"]:
             L0 = data[tc]["result"][item].get("L0", "其他")
             if L0 not in result_dict["dim"]:
@@ -405,7 +412,12 @@ def summary_result(data: dict, base: dict) -> dict:
             if item in result_dict["dim"][L0]["data"]:
                 raise ValueError(f"重复的性能指标名{item}")
             value_item = item_data["value"]
-            value_base = base[tc]["result"][item]["value"]
+            if item not in base_results:
+                warn(
+                    f"基准数据中缺少用例 {tc} 的指标 {item}，跳过该指标的评分计算（请更新 base.json）"
+                )
+                continue
+            value_base = base_results[item]["value"]
             if item_data["type"] == "HIB":
                 if value_base == 0:
                     warn(f"测试用例{tc}性能指标{item}的基准值为0，跳过该指标的评分计算")
@@ -430,7 +442,16 @@ def summary_result(data: dict, base: dict) -> dict:
             }
     for L0 in result_dict["dim"]:
         dbg(f"try get score for {L0}")
-        result_dict["dim"][L0]["score"] = int(safe_weighted_geometric_mean(result_dict["dim"][L0]["data"]) * 10000)
+        dim_data = result_dict["dim"][L0]["data"]
+        if not dim_data:
+            warn(
+                f"维度 {L0} 下无有效指标参与评分（可能基准数据缺失或均被跳过），该维度得分记为 0"
+            )
+            result_dict["dim"][L0]["score"] = 0
+        else:
+            result_dict["dim"][L0]["score"] = int(
+                safe_weighted_geometric_mean(dim_data) * 10000
+            )
         msg(f"{L0} score: {result_dict['dim'][L0]['score']}")
     result_dict["score"] = sum(result_dict["dim"][L0]["score"] for L0 in result_dict["dim"])
     return result_dict
@@ -504,7 +525,14 @@ def report_excel(data: dict, base: dict, output: str):
                 item_data.get("type", ""),
                 item_data.get("unit", ""),
             ]
-            row_data.append(base[tc_name]["result"][item]["value"])
+            if tc_name in base and isinstance(base[tc_name].get("result"), dict):
+                br = base[tc_name]["result"]
+                if item in br:
+                    row_data.append(br[item]["value"])
+                else:
+                    row_data.append("")
+            else:
+                row_data.append("")
             data_list = []
             for loop in loop_list:
                 value = data[loop]["data"][tc_name]["result"][item].get("value", "")
-- 
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