fix(price_gui): 修复价格列数据推送逻辑错误

- 在读取CSV数据后提前将Price列转换为数值类型，错误值转为NaN
- 过滤掉Price列中无效的NaN值，避免发送无效价格数据
- 调整消息推送循环为遍历过滤后的有效数据集合
- 修正推送数据中price字段直接使用转换后的数值，避免类型判断错误
- 优化了RabbitMQ客户端导入位置，确保逻辑统一和清晰

price_gui.py

@@ -11,7 +11,7 @@ from ttkbootstrap.constants import *
 from tkinter import filedialog, scrolledtext
 from threading import Thread
 
-from app.helper import rabbitmq
+
 from app.helper.domain import switch_domain
 
 class AmazonPriceScraper:
@@ -167,22 +167,24 @@ class AmazonPriceScraper:
 
         # 读取Excel文件
         data = pd.read_csv(output_file)
+        # 提前转换 Price 列，错误值转为 NaN
+        data['Price'] = pd.to_numeric(data['Price'], errors='coerce')
+        # 过滤掉无效价格（NaN）
+        valid_data = data.dropna(subset=['Price'])
 
         self.log("开始推送消息....")
 
+        from app.helper import rabbitmq
+
         client = rabbitmq.RabbitMQClient()
         client.connection()
         client.connect(queue='price_robot', routing_key='price_robot', exchange='product')
         country = self.country_var.get()
-        for _, item_row in data.iterrows():
-            price = item_row.get('Price', 0)
-            if not isinstance(price, (int, float)):
-                continue
-
+        for _, item_row in valid_data.iterrows():
             push_data = {
                 'currency': country,
                 'asin': item_row.get('ASIN', ''),
-                'price': item_row.get('Price', 0),
+                'price': item_row['Price'],
             }
             client.send_message(push_data)