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
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parent
bef29011c3
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465
main.py
465
main.py
@ -16,11 +16,26 @@ P_LIMIT = 6 # 最大晋升次数
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P_START = 10 # 晋升记录开始行
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H_START = 15 + P_LIMIT # 历史记录开始行
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nowtime = datetime.now()
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NOWTIME = datetime.now()
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# 全局变量
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## 通过函数读取
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BaseData = pd.DataFrame()
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Promote = pd.DataFrame()
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Rule_Role = []
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Rule_Level = []
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Rule_RoleName = []
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Level_Limit = pd.DataFrame()
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Promote_Level = pd.DataFrame()
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Promote_verify = pd.DataFrame()
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## 统计量
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max_promote = 0
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max_history = 0
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# 工具函数
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# 自定义日期解析函数
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def custom_date_parser(x):
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try:
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return datetime.strptime(x, '%Y-%m-%d')
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@ -53,89 +68,105 @@ def split_level(level:str):
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except:
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raise Exception(f"职级[{level}]格式错误")
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# 读取员工数据
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# 读取信息
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BaseData = pd.read_excel("原数据.xlsx", sheet_name="入职信息")
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def read_base_data(): # 读取员工数据
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global BaseData
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BaseData = pd.read_excel("原数据.xlsx", sheet_name="入职信息")
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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"]:
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BaseData[col] = BaseData[col].apply(custom_date_parser)
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for col in ["晋档起始", "晋级起始"]:
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BaseData[col] = BaseData[col].apply(lambda x: datetime(x.year, 1, 1) if isinstance(x, datetime) else x)
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BaseData["Latest_Role"] = None
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BaseData["Latest_Prom"] = None
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BaseData["工龄调增"] = BaseData["工龄调增"].apply(to_int)
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BaseData["工龄调减"] = BaseData["工龄调减"].apply(to_int)
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BaseData["学龄"] = BaseData["学龄"].apply(to_int)
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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)
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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"]:
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BaseData[col] = BaseData[col].apply(custom_date_parser)
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for col in ["晋档起始", "晋级起始"]:
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BaseData[col] = BaseData[col].apply(lambda x: datetime(x.year, 1, 1) if isinstance(x, datetime) else x)
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def read_promote(): # 读取晋升记录
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global Promote
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Promote = pd.read_excel("原数据.xlsx", sheet_name="职务变动")
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for col in ["任职时间","工资执行时间"]:
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Promote[col] = Promote[col].apply(custom_date_parser)
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BaseData["工龄调增"] = BaseData["工龄调增"].apply(to_int)
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BaseData["工龄调减"] = BaseData["工龄调减"].apply(to_int)
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BaseData["学龄"] = BaseData["学龄"].apply(to_int)
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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)
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def read_rule_role(): # 读取职位规则
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global Rule_Role
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col = 4
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while True:
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try:
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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)
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Rule_Role.append({
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"start":rule.iloc[0,1],
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"end":rule.iloc[1,1],
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"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)}",skiprows=2, names=["role","salary"])
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})
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col += 2
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except:
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break
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Rule_Role = sorted(Rule_Role, key=lambda x: x['start'])
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# 读取晋升记录
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def read_rule_level(): # 读取职级规则
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global Rule_Level
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col = 1
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while True: # 职级规则
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try:
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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)
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Rule_Level.append({
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"start":rule.iloc[0,1],
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"end":rule.iloc[1,1],
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"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)}",skiprows=2, names=["level","salary"])
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})
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col += 2
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except:
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break
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Rule_Level = sorted(Rule_Level, key=lambda x: x['start'])
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Promote = pd.read_excel("原数据.xlsx", sheet_name="职务变动") #
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def read_rule_role_name(): # 读取名称变化规则
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global Rule_RoleName
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col = 1
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while True: # 名称变化
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try:
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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)
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Rule_RoleName.append({
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"start":rule.iloc[0,1],
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"end":rule.iloc[1,1],
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"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)}",skiprows=2)
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})
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col += 2
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except:
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break
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Rule_RoleName = sorted(Rule_RoleName, key=lambda x: x['start'])
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for col in ["任职时间","工资执行时间"]:
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Promote[col] = Promote[col].apply(custom_date_parser)
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def read_level_limit(): # 读取职位对应的级别限制
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global Level_Limit, Promote_Level
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Level_Limit_tmp = pd.read_excel("原数据.xlsx", sheet_name="职位规则", usecols="A:A", skiprows=2, names=["limit"])
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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"])
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Level_Limit = {}
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Promote_Level = {}
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for rule in Rule_Role:
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for index, row in rule["rule"].iterrows():
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Level_Limit[row["role"]] = Level_Limit_tmp.iloc[index]["limit"]
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Promote_Level[row["role"]] = (Promote_Level_tmp.iloc[index]["级别"], Promote_Level_tmp.iloc[index]["档次"])
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logging.info("人员信息加载完成")
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def read_promote_verify(): # 读取晋升校验
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global Promote_verify
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Promote_verify = pd.read_excel("原数据.xlsx", sheet_name="晋升校验", usecols="A:B")
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# 读取规则
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def load_people():
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read_base_data()
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read_promote()
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logging.info("人员信息加载完成")
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Rule_Role = []
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col = 4
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while True: # 职位规则
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try:
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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)
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Rule_Role.append({
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"start":rule.iloc[0,1],
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"end":rule.iloc[1,1],
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"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)}",skiprows=2, names=["role","salary"])
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})
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col += 2
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except:
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break
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Rule_Level = []
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col = 1
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while True: # 职级规则
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try:
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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)
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Rule_Level.append({
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"start":rule.iloc[0,1],
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"end":rule.iloc[1,1],
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"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)}",skiprows=2, names=["level","salary"])
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})
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col += 2
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except:
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break
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Rule_RoleName = []
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col = 1
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while True: # 名称变化
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try:
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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)
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Rule_RoleName.append({
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"start":rule.iloc[0,1],
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"end":rule.iloc[1,1],
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"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)}",skiprows=2)
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})
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col += 2
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except:
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break
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def load_rule():
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read_rule_role()
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read_rule_level()
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read_rule_role_name()
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read_level_limit()
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read_promote_verify()
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logging.info("规则加载完成")
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# 读取职位对应的级别限制
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Level_Limit_tmp = pd.read_excel("原数据.xlsx", sheet_name="职位规则", usecols="A:A", skiprows=2, names=["limit"])
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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"])
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Level_Limit = {}
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Promote_Level = {}
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for rule in Rule_Role:
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for index, row in rule["rule"].iterrows():
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Level_Limit[row["role"]] = Level_Limit_tmp.iloc[index]["limit"]
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Promote_Level[row["role"]] = (Promote_Level_tmp.iloc[index]["级别"], Promote_Level_tmp.iloc[index]["档次"])
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# 晋升校验
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Promote_verify = Level_Limit_tmp = pd.read_excel("原数据.xlsx", sheet_name="晋升校验", usecols="A:B")
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logging.info("规则加载完成")
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Rule_Role = sorted(Rule_Role, key=lambda x: x['start'])
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Rule_Level = sorted(Rule_Level, key=lambda x: x['start'])
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Rule_RoleName = sorted(Rule_RoleName, key=lambda x: x['start'])
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# 获取配置类函数
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def role_salary(role:str, time):
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for rule in Rule_Role:
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@ -167,8 +198,7 @@ def role_limit(role:str):
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logging.warning(f"职位[{role}]不存在职级上限规则")
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return -1
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max_promote = 0
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max_history = 0
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# 填充类辅助函数
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def fill_basic_info(ws, row):# 填充基本信息
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ws.cell(row=2, column=1, value=f"部门：{row['部门']} 职务：{row['职务']}")
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@ -218,155 +248,160 @@ def fill_history_info(ws, History_pd):# 填充历史记录
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ws.cell(row=H_START+index, column=7, value=hrow["变动原因"])
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# ws.cell(row=H_START+index, column=8, value=index) # Debug
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BaseData["Latest_Role"] = None
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BaseData["Latest_Prom"] = None
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def main():
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# 创建一个空的DataFrame来存储所有历史记录
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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"])
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load_people()
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load_rule()
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for index, row in BaseData.iterrows():
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try:
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logging.info(f"台账：第[{index+1}]共[{BaseData.shape[0]}]现在是[{row['身份证号码']}]")
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BaseData.at[index, "Latest_Role"] = row["初始职务"]
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BaseData.at[index, "Latest_Prom"] = row["入职时间"]
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wb = load_workbook("模板/个人台账.xlsx")
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ws = wb.active
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fill_basic_info(ws, row)# 填充基本信息
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# 创建一个空的DataFrame来存储所有历史记录
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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"])
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# 查找晋升信息
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promote = Promote[Promote["身份证号"] == row["身份证号码"]]
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if not promote.empty:
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promote = promote.sort_values(by=["工资执行时间", "任职时间"], ascending=[False, False]).reset_index(drop=True)
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BaseData.at[index, "Latest_Role"] = promote.iloc[0]["新职务"]
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BaseData.at[index, "Latest_Prom"] = promote.iloc[0]["任职时间"]
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# 把原职务取出来
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if promote.shape[0] > 1:
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BaseData.at[index, "职务2"] = promote.iloc[1]["新职务"]
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BaseData.at[index, "日期2"] = promote.iloc[1]["任职时间"]
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else:
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BaseData.at[index, "职务2"] = row["初始职务"]
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BaseData.at[index, "日期2"] = row["入职时间"]
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promote = promote.sort_values(by=["工资执行时间", "任职时间"]).reset_index(drop=True)
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fill_prompt_info(ws, promote)# 填充晋升信息
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# 根据规则匹配职级薪资
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History_pd = pd.DataFrame(columns=["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"])
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# 添加入职记录
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History_pd.loc[len(History_pd)] = [row["入职时间"], row["初始职务"], "", row["入职时的初始级别"], "", "", "套改/定级", ""]
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for index, prow in promote.iterrows(): # 添加晋升记录
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History_pd.loc[len(History_pd)] = [prow["工资执行时间"]+relativedelta(hours=prow["任职时间"].month,minutes=prow["任职时间"].day), prow["新职务"], "", "", "", "", "晋升", f"任{prow['新职务']} {prow['变动批注'] if pd.notna(prow['变动批注']) else ''}"]
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for index, row in BaseData.iterrows():
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try:
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calctime=row["晋档起始"] + relativedelta(minute=1)
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while True: # 添加晋档记录
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calctime += relativedelta(years=row["晋档间隔"])
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if calctime > nowtime:
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break
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History_pd.loc[len(History_pd)] = [calctime, "", "", "", "", "", "两年晋档", ""]
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calctime=row["晋级起始"]
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while True: # 添加晋级记录
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calctime += relativedelta(years=row["晋级间隔"])
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if calctime > nowtime:
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break
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History_pd.loc[len(History_pd)] = [calctime, "", "", "", "", "", "五年晋级", ""]
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except:
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raise Exception(f"晋级、档起始或间隔时间格式错误：{row['晋级起始']}-{row['晋档起始']}-{row['晋级间隔']}-{row['晋档间隔']}")
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for rule in Rule_Level: # 工资调标
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if row["入职时间"] < rule["start"]:
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History_pd.loc[len(History_pd)] = [rule["start"], "", "", "", "", "", "工资调标", ""]
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History_pd = History_pd.sort_values(by="时间").reset_index(drop=True)
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logging.info(f"台账：第[{index+1}]共[{BaseData.shape[0]}]现在是[{row['身份证号码']}]")
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BaseData.at[index, "Latest_Role"] = row["初始职务"]
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BaseData.at[index, "Latest_Prom"] = row["入职时间"]
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wb = load_workbook("模板/个人台账.xlsx")
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ws = wb.active
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fill_basic_info(ws, row)# 填充基本信息
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if History_pd.at[0,"时间"] != row["入职时间"]:
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raise Exception(f"入职时间晚于其他时间:{row['入职时间']} < {History_pd.at[0,'时间']} ({History_pd.at[0,'变动原因']})")
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for index, hrow in History_pd.iterrows(): # 数据计算
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# 调整职务职级
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if index > 0 and hrow["职务"] == "":
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History_pd.at[index, "职务"] = History_pd.iloc[index-1]["职务"]
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for rule in Rule_RoleName: # 名称变化
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if rule["start"] <= hrow["时间"] <= rule["end"]:
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if History_pd.iloc[index]["职务"] in rule["rule"]["原名称"].values:
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History_pd.at[index, "职务"] = rule["rule"][rule["rule"]["原名称"] == History_pd.iloc[index]["职务"]]["现名称"].values[0]
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if index > 0 and hrow["级别档次"] == "":
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jb, dc = split_level(History_pd.iloc[index-1]["级别档次"])
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if hrow["变动原因"] == "两年晋档":
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History_pd.at[index, "级别档次"] = f"{jb}-{dc+1}"
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elif hrow["变动原因"] == "五年晋级":
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if jb-1 < 1 or jb-1 < role_limit(History_pd.iloc[index]["职务"]):
|
||||
# 查找晋升信息
|
||||
promote = Promote[Promote["身份证号"] == row["身份证号码"]]
|
||||
if not promote.empty:
|
||||
promote = promote.sort_values(by=["工资执行时间", "任职时间"], ascending=[False, False]).reset_index(drop=True)
|
||||
BaseData.at[index, "Latest_Role"] = promote.iloc[0]["新职务"]
|
||||
BaseData.at[index, "Latest_Prom"] = promote.iloc[0]["任职时间"]
|
||||
# 把原职务取出来
|
||||
if promote.shape[0] > 1:
|
||||
BaseData.at[index, "职务2"] = promote.iloc[1]["新职务"]
|
||||
BaseData.at[index, "日期2"] = promote.iloc[1]["任职时间"]
|
||||
else:
|
||||
BaseData.at[index, "职务2"] = row["初始职务"]
|
||||
BaseData.at[index, "日期2"] = row["入职时间"]
|
||||
|
||||
promote = promote.sort_values(by=["工资执行时间", "任职时间"]).reset_index(drop=True)
|
||||
fill_prompt_info(ws, promote)# 填充晋升信息
|
||||
|
||||
# 根据规则匹配职级薪资
|
||||
History_pd = pd.DataFrame(columns=["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"])
|
||||
# 添加入职记录
|
||||
History_pd.loc[len(History_pd)] = [row["入职时间"], row["初始职务"], "", row["入职时的初始级别"], "", "", "套改/定级", ""]
|
||||
for index, prow in promote.iterrows(): # 添加晋升记录
|
||||
History_pd.loc[len(History_pd)] = [prow["工资执行时间"]+relativedelta(hours=prow["任职时间"].month,minutes=prow["任职时间"].day), prow["新职务"], "", "", "", "", "晋升", f"任{prow['新职务']} {prow['变动批注'] if pd.notna(prow['变动批注']) else ''}"]
|
||||
try:
|
||||
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:
|
||||
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:
|
||||
break
|
||||
History_pd.loc[len(History_pd)] = [calctime, "", "", "", "", "", "五年晋级", ""]
|
||||
except:
|
||||
raise Exception(f"晋级、档起始或间隔时间格式错误：{row['晋级起始']}-{row['晋档起始']}-{row['晋级间隔']}-{row['晋档间隔']}")
|
||||
for rule in Rule_Level: # 工资调标
|
||||
if row["入职时间"] < rule["start"]:
|
||||
History_pd.loc[len(History_pd)] = [rule["start"], "", "", "", "", "", "工资调标", ""]
|
||||
History_pd = History_pd.sort_values(by="时间").reset_index(drop=True)
|
||||
|
||||
if History_pd.at[0,"时间"] != row["入职时间"]:
|
||||
raise Exception(f"入职时间晚于其他时间:{row['入职时间']} < {History_pd.at[0,'时间']} ({History_pd.at[0,'变动原因']})")
|
||||
for index, hrow in History_pd.iterrows(): # 数据计算
|
||||
# 调整职务职级
|
||||
if index > 0 and hrow["职务"] == "":
|
||||
History_pd.at[index, "职务"] = History_pd.iloc[index-1]["职务"]
|
||||
for rule in Rule_RoleName: # 名称变化
|
||||
if rule["start"] <= hrow["时间"] <= rule["end"]:
|
||||
if History_pd.iloc[index]["职务"] in rule["rule"]["原名称"].values:
|
||||
History_pd.at[index, "职务"] = rule["rule"][rule["rule"]["原名称"] == History_pd.iloc[index]["职务"]]["现名称"].values[0]
|
||||
if index > 0 and hrow["级别档次"] == "":
|
||||
jb, dc = split_level(History_pd.iloc[index-1]["级别档次"])
|
||||
if hrow["变动原因"] == "两年晋档":
|
||||
History_pd.at[index, "级别档次"] = f"{jb}-{dc+1}"
|
||||
else:
|
||||
History_pd.at[index, "级别档次"] = f"{jb-1}-{dc-1}"
|
||||
elif hrow["变动原因"] == "工资调标":
|
||||
History_pd.at[index, "级别档次"] = f"{jb}-{dc}"
|
||||
elif hrow["变动原因"] == "晋升":
|
||||
role = History_pd.iloc[index]["职务"]
|
||||
if role in Promote_Level.keys():
|
||||
new_jb = jb + Promote_Level[role][0]
|
||||
new_dc = dc + Promote_Level[role][1]
|
||||
if pd.isna(new_jb) or pd.isna(new_dc):
|
||||
print(Promote_Level[role][1])
|
||||
raise Exception(f"级别档次计算出现NaN值：[{new_jb}]-[{new_dc}]({role})")
|
||||
else:
|
||||
new_jb = int(new_jb)
|
||||
new_dc = int(new_dc)
|
||||
if (History_pd.iloc[index-1]["职务"] in Promote_verify.iloc[:,0].values and
|
||||
role in Promote_verify.iloc[:,1].values):
|
||||
logging.info(f"[{row['身份证号码']}]命中晋升校验规则[{History_pd.iloc[index-1]['职务']}]->[{role}]")
|
||||
History_pd.at[index, "级别档次"] = f"{jb}-{dc}"
|
||||
elif new_jb < role_limit(role):
|
||||
elif hrow["变动原因"] == "五年晋级":
|
||||
if jb-1 < 1 or jb-1 < role_limit(History_pd.iloc[index]["职务"]):
|
||||
History_pd.at[index, "级别档次"] = f"{jb}-{dc+1}"
|
||||
elif new_jb < 1 or new_dc < 1:
|
||||
raise Exception(f"级别档次小于0：[{new_jb}]-[{new_dc}]")
|
||||
else:
|
||||
History_pd.at[index, "级别档次"] = f"{new_jb}-{new_dc}"
|
||||
else:
|
||||
logging.warning(f"职位[{role}]不存在职级上限规则")
|
||||
# 计算工资
|
||||
History_pd.at[index, "职务工资"] = role_salary(History_pd.iloc[index]["职务"], hrow["时间"])
|
||||
History_pd.at[index, "级别工资"] = level_salary(History_pd.iloc[index]["级别档次"], hrow["时间"])
|
||||
History_pd.at[index, "工资合计"] = to_int(History_pd.iloc[index]["职务工资"]) + to_int(History_pd.iloc[index]["级别工资"])
|
||||
History_pd.at[index, "级别档次"] = f"{jb-1}-{dc-1}"
|
||||
elif hrow["变动原因"] == "工资调标":
|
||||
History_pd.at[index, "级别档次"] = f"{jb}-{dc}"
|
||||
elif hrow["变动原因"] == "晋升":
|
||||
role = History_pd.iloc[index]["职务"]
|
||||
if role in Promote_Level.keys():
|
||||
new_jb = jb + Promote_Level[role][0]
|
||||
new_dc = dc + Promote_Level[role][1]
|
||||
if pd.isna(new_jb) or pd.isna(new_dc):
|
||||
print(Promote_Level[role][1])
|
||||
raise Exception(f"级别档次计算出现NaN值：[{new_jb}]-[{new_dc}]({role})")
|
||||
else:
|
||||
new_jb = int(new_jb)
|
||||
new_dc = int(new_dc)
|
||||
if (History_pd.iloc[index-1]["职务"] in Promote_verify.iloc[:,0].values and
|
||||
role in Promote_verify.iloc[:,1].values):
|
||||
logging.info(f"[{row['身份证号码']}]命中晋升校验规则[{History_pd.iloc[index-1]['职务']}]->[{role}]")
|
||||
History_pd.at[index, "级别档次"] = f"{jb}-{dc}"
|
||||
elif new_jb < role_limit(role):
|
||||
History_pd.at[index, "级别档次"] = f"{jb}-{dc+1}"
|
||||
elif new_jb < 1 or new_dc < 1:
|
||||
raise Exception(f"级别档次小于0：[{new_jb}]-[{new_dc}]")
|
||||
else:
|
||||
History_pd.at[index, "级别档次"] = f"{new_jb}-{new_dc}"
|
||||
else:
|
||||
logging.warning(f"职位[{role}]不存在职级上限规则")
|
||||
# 计算工资
|
||||
History_pd.at[index, "职务工资"] = role_salary(History_pd.iloc[index]["职务"], hrow["时间"])
|
||||
History_pd.at[index, "级别工资"] = level_salary(History_pd.iloc[index]["级别档次"], hrow["时间"])
|
||||
History_pd.at[index, "工资合计"] = to_int(History_pd.iloc[index]["职务工资"]) + to_int(History_pd.iloc[index]["级别工资"])
|
||||
|
||||
fill_history_info(ws, History_pd)# 填充历史记录
|
||||
fill_history_info(ws, History_pd)# 填充历史记录
|
||||
|
||||
# 将当前人员的历史记录添加到总表中
|
||||
History_pd["身份证号码"] = row["身份证号码"]
|
||||
History_pd["姓名"] = row["姓名"]
|
||||
all_history = pd.concat([all_history, History_pd], ignore_index=True)
|
||||
# 将当前人员的历史记录添加到总表中
|
||||
History_pd["身份证号码"] = row["身份证号码"]
|
||||
History_pd["姓名"] = row["姓名"]
|
||||
all_history = pd.concat([all_history, History_pd], ignore_index=True)
|
||||
|
||||
wb.save(f"个人台账/{row['身份证号码']}_{row['姓名']}.xlsx")
|
||||
except Exception as e:
|
||||
logging.error(f"{row['身份证号码']}:{e}")
|
||||
wb.save(f"个人台账/{row['身份证号码']}_{row['姓名']}.xlsx")
|
||||
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
|
||||
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)
|
||||
logging.info("所有人员历史记录已保存到'所有人员历史记录.xlsx'")
|
||||
# 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.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'")
|
||||
|
||||
wb = load_workbook("模板/汇总名册.xlsx")
|
||||
ws = wb.active
|
||||
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):
|
||||
ws.cell(row=6+index, column=col)._style = ws.cell(row=6, column=col)._style
|
||||
ws.cell(row=6+index, column=1, value=index+1)
|
||||
ws.cell(row=6+index, column=2, value=row["姓名"])
|
||||
ws.cell(row=6+index, column=3, value=row["性别"])
|
||||
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=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"])
|
||||
ws.cell(row=6+index, column=12, value=format_time(row["Latest_Prom"], "Latest_Prom"))
|
||||
ws.cell(row=6+index, column=13, value=row["职务2"])
|
||||
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 = load_workbook("模板/汇总名册.xlsx")
|
||||
ws = wb.active
|
||||
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):
|
||||
ws.cell(row=6+index, column=col)._style = ws.cell(row=6, column=col)._style
|
||||
ws.cell(row=6+index, column=1, value=index+1)
|
||||
ws.cell(row=6+index, column=2, value=row["姓名"])
|
||||
ws.cell(row=6+index, column=3, value=row["性别"])
|
||||
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=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"])
|
||||
ws.cell(row=6+index, column=12, value=format_time(row["Latest_Prom"], "Latest_Prom"))
|
||||
ws.cell(row=6+index, column=13, value=row["职务2"])
|
||||
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
|
||||
|
||||
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:
|
||||
logging.warning(f"最多有[{max_history}]条薪资历史，需要调整模板。")
|
||||
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:
|
||||
logging.warning(f"最多有[{max_history}]条薪资历史，需要调整模板。")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Loading…
x
Reference in New Issue
Block a user