使用会员账号下载卖家精灵bsr销量。可以获取到5w排名之后的数据。每个月1号开始跑。查询sql有调整。只获取当月的预估销量。不在使用上个月的。因为是在当月跑的b…

使用会员账号下载卖家精灵bsr销量。可以获取到5w排名之后的数据。每个月1号开始跑。查询sql有调整。只获取当月的预估销量。不在使用上个月的。因为是在当月跑的bsr。之前是账号不够。在上个月末就开始跑数据

py_spider/amazon_every_day_spider/calcuate_mean.py

@@ -13,7 +13,7 @@ import math
 
 class CalculateMean(BaseUtils):
 
-    def __init__(self, site_name='us', nums_start=0, nums_step=10000000, year=2025, week=1, flag_uniformity=False):
+    def __init__(self, site_name='us', nums_start=0, nums_step=10000000, year=2026, week=1, flag_uniformity=False):
         super().__init__()
         self.site_name = site_name
         self.engine = self.mysql_connect()
@@ -51,34 +51,42 @@ class CalculateMean(BaseUtils):
         print(_year_month)
         print(f"读取 {self.site_name}_one_category")
 
-        # ---- 6 月份 ----
-        sql_6 = f"""
-            SELECT * from {self.site_name}_one_category WHERE id in (  select max(id) from {self.site_name}_one_category where  `year_month`='2025_5' and orders=0 and rank>50000  GROUP BY `name`)
-                    UNION
-                    select * from {self.site_name}_one_category where `year_month`='2025_8'  and rank<=50000 
-            """
-        print('查询原始表6：', sql_6)
-        self.df_sum_6 = self.engine.read_sql(sql_6)
-
-        # ---- 7 月份 ----
-        sql_7 = f"""
-             SELECT * from {self.site_name}_one_category WHERE id in (  select max(id) from {self.site_name}_one_category where  `year_month`='2025_5' and orders=0 and rank>50000  GROUP BY `name`)
-                    UNION
-                    select * from {self.site_name}_one_category where `year_month`='2025_9'  and rank<=50000 
-            """
-        print('查询原始表7：', sql_7)
-        self.df_sum_7 = self.engine.read_sql(sql_7)
-
-        # 合并后直接靠 keep='last' 留 7 月
-        self.df_sum = pd.concat([self.df_sum_6, self.df_sum_7], ignore_index=True)
-        print("合并前总行数:", len(self.df_sum))
-        self.df_sum.drop_duplicates(subset=['rank', 'name'], keep='last', inplace=True)
-        print("合并去重后总行数:", len(self.df_sum))
+        # # ---- 6 月份 ----
+        # sql_6 = f"""
+        #     SELECT * from {self.site_name}_one_category WHERE id in (  select max(id) from {self.site_name}_one_category where  `year_month`='2026_5' and orders=0 and rank>50000  GROUP BY `name`)
+        #             UNION
+        #             select * from {self.site_name}_one_category where `year_month`='2026_8'  and rank<=50000
+        #     """
+        # print('查询原始表6：', sql_6)
+        # self.df_sum_6 = self.engine.read_sql(sql_6)
+        #
+        # # ---- 7 月份 ----
+        # sql_7 = f"""
+        #      SELECT * from {self.site_name}_one_category WHERE id in (  select max(id) from {self.site_name}_one_category where  `year_month`='2026_5' and orders=0 and rank>50000  GROUP BY `name`)
+        #             UNION
+        #             select * from {self.site_name}_one_category where `year_month`='2026_9'  and rank<=50000
+        #     """
+        # print('查询原始表7：', sql_7)
+        # self.df_sum_7 = self.engine.read_sql(sql_7)
+        #
+        # # 合并后直接靠 keep='last' 留 7 月
+        # self.df_sum = pd.concat([self.df_sum_6, self.df_sum_7], ignore_index=True)
+        # print("合并前总行数:", len(self.df_sum))
+        # self.df_sum.drop_duplicates(subset=['rank', 'name'], keep='last', inplace=True)
+        # print("合并去重后总行数:", len(self.df_sum))
 
+        print(f"读取 {self.site_name}_one_category")
+        sql = f"select * from {self.site_name}_one_category where `year_month`='{_year_month}';"
+        print('查询原始表：', sql)
+        self.df_sum = self.engine.read_sql(sql)
+        print("self.df_sum.shape1:", self.df_sum.shape)
+        time.sleep(2)
         # 排序、后续处理
         self.df_sum.sort_values(by=['name', 'rank'], inplace=True)
+        # # 删除重复行，保留最后一行
+        self.df_sum.drop_duplicates(['name', 'rank'], keep='last', inplace=True)
+        print("self.df_sum.shape2:", self.df_sum.shape)
         print(self.df_sum[['year_month', 'rank', 'orders']].head(10).to_string())
-
         self.cate_list = list(set(self.df_sum.name))
         sql_select = f"SELECT `year_month` from selection.week_20_to_30 WHERE `week`={int(self.week)} and `year`={self.year}"
         print(sql_select, 'sql_select:')
@@ -161,7 +169,7 @@ class CalculateMean(BaseUtils):
         with engine_us_mysql.begin() as conn:
 
             time_strftime = time.strftime("%Y-%m-%d %X", time.localtime())
-            update_workflow_progress = f"update workflow_progress set status_val=3,status='抓取结束' where page='ASIN销量' and date_info='2025-{week}' and site_name='{site_name}' and date_type='week'"
+            update_workflow_progress = f"update workflow_progress set status_val=3,status='抓取结束' where page='ASIN销量' and date_info='2026-{week}' and site_name='{site_name}' and date_type='week'"
             print(update_workflow_progress)
             conn.execute(update_workflow_progress)
 
@@ -182,21 +190,21 @@ if __name__ == '__main__':
     # week = '04'
     print("week  周：", week)
     time.sleep(2)
-    handle_obj_us = CalculateMean(site_name='us', year=2025, week=week)
+    handle_obj_us = CalculateMean(site_name='us', year=2026, week=week)
     handle_obj_us.run()
     handle_obj_us.sendMessage(week, site_name='us')
-    # handle_obj_uk = CalculateMean(site_name='uk', year=2025, week=week)
+    # handle_obj_uk = CalculateMean(site_name='uk', year=2026, week=week)
     # handle_obj_uk.run()
     # handle_obj_uk.sendMessage(week, site_name='uk')
-    # handle_obj_de = CalculateMean(site_name='de', year=2025, week=week)
+    # handle_obj_de = CalculateMean(site_name='de', year=2026, week=week)
     # handle_obj_de.run()
     # handle_obj_de.sendMessage(week, site_name='de')
-    # handle_obj_fr = CalculateMean(site_name='fr', year=2025, week=week)
+    # handle_obj_fr = CalculateMean(site_name='fr', year=2026, week=week)
     # handle_obj_fr.run()
     # handle_obj_fr.sendMessage(week, site_name='fr')
-    # handle_obj_es = CalculateMean(site_name='es', year=2025, week=week)
+    # handle_obj_es = CalculateMean(site_name='es', year=2026, week=week)
     # handle_obj_es.run()
     # handle_obj_es.sendMessage(week, site_name='es')
-    # handle_obj_it = CalculateMean(site_name='it', year=2025, week=week)
+    # handle_obj_it = CalculateMean(site_name='it', year=2026, week=week)
     # handle_obj_it.run()
     # handle_obj_it.sendMessage(week, site_name='it')