调整列名并添加输入验证

app/prediction.py

@@ -57,7 +57,17 @@ FEATURES = [
 ]
 
 ID_COLUMN = "管道编号"
-PIPE_AGE_COLUMN = "管龄"
+PIPE_AGE_COLUMN = "管龄（年）"
+LEGACY_PIPE_AGE_COLUMN = "管龄"
+STATUS_COLUMN = "状态"
+EVENT_AGE_COLUMN = "事件/观察管龄（年）"
+INPUT_COLUMNS = [
+    ID_COLUMN,
+    PIPE_AGE_COLUMN,
+    STATUS_COLUMN,
+    EVENT_AGE_COLUMN,
+    *FEATURES,
+]
 MATERIAL_COLUMN = "管材"
 MATERIAL_CODE_OPTIONS = [
     (1, "镀锌"),
@@ -183,11 +193,19 @@ def secure_upload_name(original_filename: str, run_id: str) -> tuple[str, str]:
 def read_input_file(path: Path, suffix: str) -> pd.DataFrame:
     try:
         if suffix == ".csv":
-            return pd.read_csv(path, dtype={ID_COLUMN: "string"})
-        return pd.read_excel(path, dtype={ID_COLUMN: "string"})
+            df = pd.read_csv(path, dtype={ID_COLUMN: "string"})
+        else:
+            df = pd.read_excel(path, dtype={ID_COLUMN: "string"})
     except Exception as exc:
         logging.exception("文件解析失败: %s", exc)
         raise PredictionError("文件解析失败，请检查编码或表格格式。")
+    return normalize_input_columns(df)
+
+
+def normalize_input_columns(df: pd.DataFrame) -> pd.DataFrame:
+    if PIPE_AGE_COLUMN not in df.columns and LEGACY_PIPE_AGE_COLUMN in df.columns:
+        return df.rename(columns={LEGACY_PIPE_AGE_COLUMN: PIPE_AGE_COLUMN})
+    return df
 
 
 def normalize_id_value(value: Any, fallback: str) -> str:
@@ -201,8 +219,7 @@ def normalize_id_value(value: Any, fallback: str) -> str:
 def validate_input_frame(df: pd.DataFrame) -> None:
     if df.empty:
         raise PredictionError("上传文件没有可预测的数据。")
-    required_columns = [ID_COLUMN, *FEATURES]
-    missing = [col for col in required_columns if col not in df.columns]
+    missing = [col for col in INPUT_COLUMNS if col not in df.columns]
     if missing:
         raise PredictionError(f"缺少必要字段: {', '.join(missing)}")
 
@@ -447,8 +464,8 @@ def render_survival_chart(df: pd.DataFrame, curves, image_path: Path) -> tuple[l
         )
         summary_sheet_rows.append(
             {
-                "管道编号": pipe_id,
-                "管龄": pipe_age,
+                ID_COLUMN: pipe_id,
+                PIPE_AGE_COLUMN: pipe_age,
                 "健康等级": grade_label,
             }
         )