fix: 添加工龄计算字段，整理代码结构（移动函数与处理的位置）

- 新增多个工具函数以处理日期、整数转换和职级分割，增强数据处理的灵活性
- 更新工龄计算逻辑，确保准确反映员工的工龄和学龄
- 移除冗余代码，提升代码可读性和维护性

main.py

@@ -9,32 +9,75 @@ from datetime import datetime
 # 配置日志记录
 logging.basicConfig(filename='log.txt', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 
+# 常量
+
 P_LIMIT = 6 # 最大晋升次数
 
 P_START = 10 # 晋升记录开始行
 H_START = 15 + P_LIMIT # 历史记录开始行
 
+nowtime = datetime.now()
+
+# 工具函数
+
 # 自定义日期解析函数
 def custom_date_parser(x):
     try:
         return datetime.strptime(x, '%Y-%m-%d')
     except:
         return x
+    
+def format_time(dt,info):
+    try:
+        return dt.strftime("%Y.%m")
+    except:
+        logging.warning(f"[{info}]时间格式错误：{dt}")
+        return dt
+
+def to_int(x):
+    try:
+        return int(x)
+    except:
+        return 0
+
+def fallback(x):
+    for i in x:
+        if pd.notna(i) and i != '':
+            return i
+    return ''
+
+def split_level(level:str):
+    try:
+        parts = level.split('-')
+        return (int(parts[0]), int(parts[1]))
+    except:
+        raise Exception(f"职级[{level}]格式错误")
+
+# 读取员工数据
 
 BaseData = pd.read_excel("原数据.xlsx", sheet_name="入职信息")
-Promote = pd.read_excel("原数据.xlsx", sheet_name="职务变动") # 
 
 for col in ["出生年月","任职年月","原职时间","参加工作时间","入职时间", "晋档起始", "晋级起始", "日期2"]:
     BaseData[col] = BaseData[col].apply(custom_date_parser)
-
 for col in ["晋档起始", "晋级起始"]:
     BaseData[col] = BaseData[col].apply(lambda x: datetime(x.year, 1, 1) if isinstance(x, datetime) else x)
 
+BaseData["工龄调增"] = BaseData["工龄调增"].apply(to_int)
+BaseData["工龄调减"] = BaseData["工龄调减"].apply(to_int)
+BaseData["学龄"] = BaseData["学龄"].apply(to_int)
+BaseData["工龄"] = BaseData.apply(lambda row: nowtime.year-row["参加工作时间"].year+row["工龄调增"]-row["工龄调减"]+1, axis=1)
+
+# 读取晋升记录
+
+Promote = pd.read_excel("原数据.xlsx", sheet_name="职务变动") # 
+
 for col in ["任职时间","工资执行时间"]:
     Promote[col] = Promote[col].apply(custom_date_parser)
 
 logging.info("人员信息加载完成")
 
+# 读取规则
+
 Rule_Role = []
 col = 4
 while True: # 职位规则
@@ -94,16 +137,6 @@ Rule_Role = sorted(Rule_Role, key=lambda x: x['start'])
 Rule_Level = sorted(Rule_Level, key=lambda x: x['start'])
 Rule_RoleName = sorted(Rule_RoleName, key=lambda x: x['start'])
 
-nowtime = datetime.now()
-
-def split_level(level:str):
-    try:
-        parts = level.split('-')
-        return (int(parts[0]), int(parts[1]))
-    except:
-        raise Exception(f"职级[{level}]格式错误")
-        return (0, 0)
-
 def role_salary(role:str, time):
     for rule in Rule_Role:
         if rule["start"] <= time <= rule["end"]:
@@ -134,28 +167,6 @@ def role_limit(role:str):
         logging.warning(f"职位[{role}]不存在职级上限规则")
         return -1
 
-def format_time(dt,info):
-    try:
-        return dt.strftime("%Y.%m")
-    except:
-        logging.warning(f"[{info}]时间格式错误：{dt}")
-        return dt
-
-def to_int(x):
-    try:
-        return int(x)
-    except:
-        return 0
-BaseData["工龄调增"] = BaseData["工龄调增"].apply(to_int)
-BaseData["工龄调减"] = BaseData["工龄调减"].apply(to_int)
-BaseData["学龄"] = BaseData["学龄"].apply(to_int)
-
-def fallback(x):
-    for i in x:
-        if pd.notna(i) and i != '':
-            return i
-    return ''
-
 max_promote = 0
 max_history = 0
 
@@ -343,8 +354,8 @@ for index, row in BaseData.iterrows(): # 汇总
         ws.cell(row=6+index, column=4, value=format_time(row["出生年月"], "出生年月"))
         ws.cell(row=6+index, column=5, value=format_time(row["参加工作时间"], "参加工作时间"))
         ws.cell(row=6+index, column=6, value=fallback([row["现学历"],row["学历"]]))
-        ws.cell(row=6+index, column=7, value=nowtime.year-row["参加工作时间"].year+row["工龄调增"]-row["工龄调减"]+1+row["学龄"])
-        ws.cell(row=6+index, column=8, value=nowtime.year-row["参加工作时间"].year+row["工龄调增"]-row["工龄调减"]+1)
+        ws.cell(row=6+index, column=7, value=row['工龄']+row["学龄"])
+        ws.cell(row=6+index, column=8, value=row['工龄'])
         ws.cell(row=6+index, column=9, value=row["学龄"])
         ws.cell(row=6+index, column=10, value=row["工龄调减"])
         ws.cell(row=6+index, column=11, value=row["Latest_Role"])