非标业绩提报、合伙人结算登记字段时间分区修改
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@@ -30,3 +30,77 @@ Traceback (most recent call last):
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\indexes\base.py", line 3819, in get_loc
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raise KeyError(key) from err
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KeyError: '业务人员'
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2025-12-25 14:47:59,066 - log_config.py - error_task_logger - ERROR - 合伙人结算登记同步到BI发生错误："None of [Index(['订单支付时间'], dtype='object')] are in the [columns]"
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Traceback (most recent call last):
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File "D:\Idea Project\SaaS_V1.7\back_ground_module\partner_settlement_to_BI.py", line 297, in main
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df = self.data_process()
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File "D:\Idea Project\SaaS_V1.7\back_ground_module\partner_settlement_to_BI.py", line 165, in data_process
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df[time_columns] = df[time_columns].apply(
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~~^^^^^^^^^^^^^^
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\frame.py", line 4113, in __getitem__
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indexer = self.columns._get_indexer_strict(key, "columns")[1]
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\indexes\base.py", line 6212, in _get_indexer_strict
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self._raise_if_missing(keyarr, indexer, axis_name)
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~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\indexes\base.py", line 6261, in _raise_if_missing
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raise KeyError(f"None of [{key}] are in the [{axis_name}]")
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KeyError: "None of [Index(['订单支付时间'], dtype='object')] are in the [columns]"
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2025-12-25 14:48:41,241 - log_config.py - error_task_logger - ERROR - 合伙人结算登记同步到BI发生错误："None of [Index(['订单登记表.订单支付时间'], dtype='object')] are in the [columns]"
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Traceback (most recent call last):
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File "D:\Idea Project\SaaS_V1.7\back_ground_module\partner_settlement_to_BI.py", line 297, in main
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df = self.data_process()
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File "D:\Idea Project\SaaS_V1.7\back_ground_module\partner_settlement_to_BI.py", line 165, in data_process
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df[time_columns] = df[time_columns].apply(
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~~^^^^^^^^^^^^^^
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\frame.py", line 4113, in __getitem__
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indexer = self.columns._get_indexer_strict(key, "columns")[1]
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\indexes\base.py", line 6212, in _get_indexer_strict
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self._raise_if_missing(keyarr, indexer, axis_name)
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~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\indexes\base.py", line 6261, in _raise_if_missing
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raise KeyError(f"None of [{key}] are in the [{axis_name}]")
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KeyError: "None of [Index(['订单登记表.订单支付时间'], dtype='object')] are in the [columns]"
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2025-12-25 15:31:38,149 - log_config.py - error_task_logger - ERROR - 非标业绩提报转BI发生错误Already tz-aware, use tz_convert to convert.
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Traceback (most recent call last):
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File "D:\Idea Project\SaaS_V1.7\back_ground_module\non_standar_performance_to_BI.py", line 287, in main
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df = self.data_process()
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File "D:\Idea Project\SaaS_V1.7\back_ground_module\non_standar_performance_to_BI.py", line 148, in data_process
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df[time_columns] = df[time_columns].apply(
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~~~~~~~~~~~~~~~~~~~~~~^
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lambda col: pd.to_datetime(col, errors='coerce')
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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.dt.tz_localize('Asia/Shanghai')
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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.dt.strftime('%Y-%m-%d %H:%M:%S')
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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)
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^
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\frame.py", line 10381, in apply
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return op.apply().__finalize__(self, method="apply")
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~~~~~~~~^^
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\apply.py", line 916, in apply
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return self.apply_standard()
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~~~~~~~~~~~~~~~~~~~^^
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\apply.py", line 1063, in apply_standard
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results, res_index = self.apply_series_generator()
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~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\apply.py", line 1081, in apply_series_generator
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results[i] = self.func(v, *self.args, **self.kwargs)
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~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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File "D:\Idea Project\SaaS_V1.7\back_ground_module\non_standar_performance_to_BI.py", line 150, in <lambda>
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.dt.tz_localize('Asia/Shanghai')
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~~~~~~~~~~~^^^^^^^^^^^^^^^^^
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\accessor.py", line 112, in f
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return self._delegate_method(name, *args, **kwargs)
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~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\indexes\accessors.py", line 132, in _delegate_method
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result = method(*args, **kwargs)
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\indexes\datetimes.py", line 293, in tz_localize
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arr = self._data.tz_localize(tz, ambiguous, nonexistent)
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\arrays\_mixins.py", line 81, in method
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return meth(self, *args, **kwargs)
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File "D:\ProgramTools\anaconda3\envs\saas\Lib\site-packages\pandas\core\arrays\datetimes.py", line 1085, in tz_localize
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raise TypeError("Already tz-aware, use tz_convert to convert.")
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TypeError: Already tz-aware, use tz_convert to convert.
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@@ -143,13 +143,17 @@ class NonStandardPerformanceToBI:
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df[col] = df[col].map(lambda x: x.get("name", "") if isinstance(x, dict) else "")
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# 3.日期字段转为北京时间
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time_columns = ["支付日期", "开户/处理日期","提交时间","更新时间","业绩归属月","业绩归属日期"]
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time_columns = ["支付日期", "开户/处理日期", "提交时间", "更新时间", "业绩归属月", "业绩归属日期"]
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df[time_columns] = df[time_columns].apply(
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lambda col: pd.to_datetime(col, errors='coerce')
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.dt.tz_localize(None)
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.dt.strftime('%Y-%m-%d %H:%M:%S')
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)
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for col in time_columns:
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# 1. 解析为 datetime，并明确指定为 UTC（即使原始字符串无时区）
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dt_utc = pd.to_datetime(df[col], errors='coerce', utc=True)
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# 2. 转换为北京时间
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dt_beijing = dt_utc.dt.tz_convert('Asia/Shanghai')
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# 3. 去掉时区信息（变成 naive datetime），然后格式化为字符串
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df[col] = dt_beijing.dt.tz_localize(None).dt.strftime('%Y-%m-%d %H:%M:%S')
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# 4.处理所有配置的列表字段
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if "新签阶段及提成比例" in df.columns:
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@@ -139,13 +139,15 @@ class PartnerSettlementToBI:
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df[col] = df[col].map(lambda x: x.get("name", "") if isinstance(x, dict) else "")
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# 3.日期字段转为北京时间
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time_columns = ["提交时间", "更新时间","订单支付时间-核实","结算月份"]
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# 3. 日期字段转为北京时间（主表）
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time_columns = ["提交时间", "更新时间", "订单支付时间-核实", "结算月份"]
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df[time_columns] = df[time_columns].apply(
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lambda col: pd.to_datetime(col, errors='coerce')
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.dt.tz_localize(None)
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.dt.strftime('%Y-%m-%d %H:%M:%S')
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)
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for col in time_columns:
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if col in df.columns:
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# 假设原始时间是 UTC（即使字符串无时区）
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dt_utc = pd.to_datetime(df[col], errors='coerce', utc=True)
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dt_beijing = dt_utc.dt.tz_convert('Asia/Shanghai')
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df[col] = dt_beijing.dt.tz_localize(None).dt.strftime('%Y-%m-%d %H:%M:%S')
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# 4.处理订单登记表列表字段，将其拆分成多行
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if "订单登记表" in df.columns:
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@@ -168,12 +170,11 @@ class PartnerSettlementToBI:
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time_columns_nested = ["订单支付时间"] # 来自订单登记表等嵌套结构
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# 时间字段标准化：处理订单支付时间
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for col in time_columns_nested:
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if col in df_exploded.columns:
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df_exploded[col] = pd.to_datetime(df_exploded[col], errors='coerce') \
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.dt.tz_localize(None) \
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.dt.strftime('%Y-%m-%d %H:%M:%S')
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dt_utc = pd.to_datetime(df_exploded[col], errors='coerce', utc=True)
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dt_beijing = dt_utc.dt.tz_convert('Asia/Shanghai')
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df_exploded[col] = dt_beijing.dt.tz_localize(None).dt.strftime('%Y-%m-%d %H:%M:%S')
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# 删除原始的订单登记表列
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df_exploded = df_exploded.drop(columns=["订单登记表"])
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