fix(data): 修复 Excel 数据读取中的空值问题

- 在读取 Excel 文件时，添加了 keep_default_na=False 和 na_values=[] 参数
- 这样可以确保在处理数据时不会出现 unintended null values
- 此修改应用于多个文件：advertise_erp.py, payment.py, payment_erp.py, return_goods.py, spa_search.py

src/advertise_erp.py

@@ -31,7 +31,7 @@ def main():
     if not os.path.isfile(file_name):
         raise FileNotFoundError(f"{file_name},文件不存在")
 
-    result = pd.read_excel(file_name)
+    result = pd.read_excel(file_name, keep_default_na=False, na_values=[])
 
     log.info(f"共计：{len(result)} 订单")
 

src/payment.py

@@ -416,7 +416,7 @@ def push_data_queue(file_name):
     rabbit = rabbitmq.RabbitMQClient()
     rabbit.connect(queue='refund_robot', routing_key='refund_robot', exchange='reports')
 
-    data = pd.read_excel(file_name)
+    data = pd.read_excel(file_name, keep_default_na=False, na_values=[])
 
     for _, item_row in data.iterrows():
         push_data = {

src/payment_erp.py

@@ -65,7 +65,7 @@ def export_list_read_data():
         log.error("页面加载失败,刷新重新加载")
         page.refresh()
 
-    all_df = pd.read_excel(file_name, header=None)
+    all_df = pd.read_excel(file_name, header=None, keep_default_na=False, na_values=[])
 
     # 找到所有空行的索引，这里假设完全空的行为表头之间的分界线
     empty_rows = all_df[all_df.isnull().all(axis=1)].index.tolist()

src/return_goods.py

@@ -120,7 +120,7 @@ def push_data_queue(file_name):
     rabbit = rabbitmq.RabbitMQClient()
     rabbit.connect(queue='return_robot', routing_key='return_robot', exchange='reports')
 
-    data = pd.read_excel(file_name)
+    data = pd.read_excel(file_name, keep_default_na=False, na_values=[])
 
     for _, item_row in data.iterrows():
         push_data = {

src/spa_search.py

@@ -313,7 +313,7 @@ def push_data_queue(file_name):
     rabbit = rabbitmq.RabbitMQClient()
     rabbit.connect(queue='spa_robot', routing_key='spa_robot', exchange='reports')
     log.info("开始读取数据....")
-    data_dict = pd.read_excel(file_name, sheet_name=None)
+    data_dict = pd.read_excel(file_name, sheet_name=None, keep_default_na=False, na_values=[])
     log.info("开始推送消息....")
     for sheet_name, values in data_dict.items():
         for _, item_row in values.iterrows():