refactor: 重构数据读取逻辑以提升代码结构和可读性

- 将员工数据、晋升记录、职位规则和职级规则的读取逻辑封装为独立函数，增强代码的模块化
- 更新全局变量的定义，确保数据处理的一致性和清晰性
- 移除冗余代码，提升整体代码的可维护性和可读性

main.py

@@ -16,11 +16,26 @@ 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()
+NOWTIME = datetime.now()
+
+# 全局变量
+
+## 通过函数读取
+BaseData = pd.DataFrame()
+Promote = pd.DataFrame()
+Rule_Role = []
+Rule_Level = []
+Rule_RoleName = []
+Level_Limit = pd.DataFrame()
+Promote_Level = pd.DataFrame()
+Promote_verify = pd.DataFrame()
+
+## 统计量
+max_promote = 0
+max_history = 0
 
 # 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')
@@ -53,34 +68,32 @@ def split_level(level:str):
     except:
         raise Exception(f"职级[{level}]格式错误")
 
-# 读取员工数据
+# 读取信息
 
-BaseData = pd.read_excel("原数据.xlsx", sheet_name="入职信息")
+def read_base_data(): # 读取员工数据
-
+    global BaseData
-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 = pd.read_excel("原数据.xlsx", sheet_name="入职信息")
+    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"]:
+    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["Latest_Role"] = None
+    BaseData["Latest_Prom"] = None
+    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)
 
-BaseData["工龄调增"] = BaseData["工龄调增"].apply(to_int)
+def read_promote(): # 读取晋升记录
-BaseData["工龄调减"] = BaseData["工龄调减"].apply(to_int)
+    global Promote
-BaseData["学龄"] = BaseData["学龄"].apply(to_int)
+    Promote = pd.read_excel("原数据.xlsx", sheet_name="职务变动")
-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)
+    for col in ["任职时间","工资执行时间"]:
-
-# 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")
+def read_rule_role(): # 读取职位规则
-
+    global Rule_Role
-# 读取规则
+    col = 4
-
+    while True: 
-Rule_Role = []
-col = 4
-while True: # 职位规则
         try:
             rule = pd.read_excel("原数据.xlsx", sheet_name="职位规则",usecols=f"{get_column_letter(col)}:{get_column_letter(col+1)}", header=None)
             Rule_Role.append({
@@ -91,9 +104,12 @@ while True: # 职位规则
             col += 2
         except:
             break
-Rule_Level = []
+    Rule_Role = sorted(Rule_Role, key=lambda x: x['start'])
-col = 1
+
-while True: # 职级规则
+def read_rule_level(): # 读取职级规则
+    global Rule_Level
+    col = 1
+    while True: # 职级规则
         try:
             rule = pd.read_excel("原数据.xlsx", sheet_name="职级规则",usecols=f"{get_column_letter(col)}:{get_column_letter(col+1)}", header=None)
             Rule_Level.append({
@@ -104,9 +120,12 @@ while True: # 职级规则
             col += 2
         except:
             break
-Rule_RoleName = []
+    Rule_Level = sorted(Rule_Level, key=lambda x: x['start'])
-col = 1
+
-while True: # 名称变化
+def read_rule_role_name(): # 读取名称变化规则
+    global Rule_RoleName
+    col = 1
+    while True: # 名称变化
         try:
             rule = pd.read_excel("原数据.xlsx", sheet_name="名称变化",usecols=f"{get_column_letter(col)}:{get_column_letter(col+1)}", header=None)
             Rule_RoleName.append({
@@ -117,25 +136,37 @@ while True: # 名称变化
             col += 2
         except:
             break
+    Rule_RoleName = sorted(Rule_RoleName, key=lambda x: x['start'])
 
-# 读取职位对应的级别限制
+def read_level_limit(): # 读取职位对应的级别限制
-Level_Limit_tmp = pd.read_excel("原数据.xlsx", sheet_name="职位规则", usecols="A:A", skiprows=2, names=["limit"])
+    global Level_Limit, Promote_Level
-Promote_Level_tmp = pd.read_excel("原数据.xlsx", sheet_name="职位规则", usecols="B:C", skiprows=2, names=["级别","档次"])
+    Level_Limit_tmp = pd.read_excel("原数据.xlsx", sheet_name="职位规则", usecols="A:A", skiprows=2, names=["limit"])
-Level_Limit = {}
+    Promote_Level_tmp = pd.read_excel("原数据.xlsx", sheet_name="职位规则", usecols="B:C", skiprows=2, names=["级别","档次"])
-Promote_Level = {}
+    Level_Limit = {}
-for rule in Rule_Role:
+    Promote_Level = {}
+    for rule in Rule_Role:
         for index, row in rule["rule"].iterrows():
             Level_Limit[row["role"]] = Level_Limit_tmp.iloc[index]["limit"]
             Promote_Level[row["role"]] = (Promote_Level_tmp.iloc[index]["级别"], Promote_Level_tmp.iloc[index]["档次"])
 
-# 晋升校验
+def read_promote_verify(): # 读取晋升校验
-Promote_verify = Level_Limit_tmp = pd.read_excel("原数据.xlsx", sheet_name="晋升校验", usecols="A:B")
+    global Promote_verify
+    Promote_verify = pd.read_excel("原数据.xlsx", sheet_name="晋升校验", usecols="A:B")
 
-logging.info("规则加载完成")
+def load_people():
+    read_base_data()
+    read_promote()
+    logging.info("人员信息加载完成")
 
-Rule_Role = sorted(Rule_Role, key=lambda x: x['start'])
+def load_rule():
-Rule_Level = sorted(Rule_Level, key=lambda x: x['start'])
+    read_rule_role()
-Rule_RoleName = sorted(Rule_RoleName, key=lambda x: x['start'])
+    read_rule_level()
+    read_rule_role_name()
+    read_level_limit()
+    read_promote_verify()
+    logging.info("规则加载完成")
+
+# 获取配置类函数
 
 def role_salary(role:str, time):
     for rule in Rule_Role:
@@ -167,8 +198,7 @@ def role_limit(role:str):
         logging.warning(f"职位[{role}]不存在职级上限规则")
         return -1
 
-max_promote = 0
+# 填充类辅助函数
-max_history = 0
 
 def fill_basic_info(ws, row):# 填充基本信息
     ws.cell(row=2, column=1, value=f"部门：{row['部门']}    职务：{row['职务']}")
@@ -218,13 +248,15 @@ def fill_history_info(ws, History_pd):# 填充历史记录
         ws.cell(row=H_START+index, column=7, value=hrow["变动原因"])
         # ws.cell(row=H_START+index, column=8, value=index) # Debug
 
-BaseData["Latest_Role"] = None
+def main():
-BaseData["Latest_Prom"] = None
 
-# 创建一个空的DataFrame来存储所有历史记录
+    load_people()
-all_history = pd.DataFrame(columns=["身份证号码", "姓名", "时间", "职务", "职务工资", "级别档次", "级别工资", "工资合计", "变动原因", "晋升备注"])
+    load_rule()
 
-for index, row in BaseData.iterrows():
+    # 创建一个空的DataFrame来存储所有历史记录
+    all_history = pd.DataFrame(columns=["身份证号码", "姓名", "时间", "职务", "职务工资", "级别档次", "级别工资", "工资合计", "变动原因", "晋升备注"])
+
+    for index, row in BaseData.iterrows():
         try:
             logging.info(f"台账：第[{index+1}]共[{BaseData.shape[0]}]现在是[{row['身份证号码']}]")
             BaseData.at[index, "Latest_Role"] = row["初始职务"]
@@ -260,13 +292,13 @@ for index, row in BaseData.iterrows():
                 calctime=row["晋档起始"] + relativedelta(minute=1)
                 while True: # 添加晋档记录
                     calctime += relativedelta(years=row["晋档间隔"]) 
-                if calctime > nowtime:
+                    if calctime > NOWTIME:
                         break
                     History_pd.loc[len(History_pd)] = [calctime, "", "", "", "", "", "两年晋档", ""]
                 calctime=row["晋级起始"]
                 while True: # 添加晋级记录
                     calctime += relativedelta(years=row["晋级间隔"])
-                if calctime > nowtime:
+                    if calctime > NOWTIME:
                         break
                     History_pd.loc[len(History_pd)] = [calctime, "", "", "", "", "", "五年晋级", ""]
             except:
@@ -336,14 +368,14 @@ for index, row in BaseData.iterrows():
         except Exception as e:
             logging.error(f"{row['身份证号码']}:{e}")
 
-# 保存所有历史记录到Excel文件
+    # 保存所有历史记录到Excel文件
-all_history["时间"] = all_history["时间"].apply(lambda x: format_time(x, "历史记录时间"))
+    all_history["时间"] = all_history["时间"].apply(lambda x: format_time(x, "历史记录时间"))
-all_history.to_excel("所有人员历史记录.xlsx", index=False)
+    all_history.to_excel("所有人员历史记录.xlsx", index=False)
-logging.info("所有人员历史记录已保存到'所有人员历史记录.xlsx'")
+    logging.info("所有人员历史记录已保存到'所有人员历史记录.xlsx'")
 
-wb = load_workbook("模板/汇总名册.xlsx")
+    wb = load_workbook("模板/汇总名册.xlsx")
-ws = wb.active
+    ws = wb.active
-for index, row in BaseData.iterrows(): # 汇总
+    for index, row in BaseData.iterrows(): # 汇总
         try:
             logging.info(f"汇总：第[{index+1}]共[{BaseData.shape[0]}]现在是[{row['身份证号码']}]")
             for col in range(1,16):
@@ -364,9 +396,12 @@ for index, row in BaseData.iterrows(): # 汇总
             ws.cell(row=6+index, column=14, value=format_time(row["日期2"], "日期2"))
         except Exception as e:
             logging.error(f"{row['身份证号码']}:{e}")
-wb.save("汇总名册.xlsx") # 保存汇总
+    wb.save("汇总名册.xlsx") # 保存汇总
 
-if max_promote > 0:
+    if max_promote > 0:
         logging.warning(f"最多有[{max_promote}]条晋升信息，需要调整模板。记得同时调整薪资历史的起始行和个人评价结果。")
-if max_history > 0:
+    if max_history > 0:
         logging.warning(f"最多有[{max_history}]条薪资历史，需要调整模板。")
+
+if __name__ == "__main__":
+    main()