feat: 更新视频插入逻辑以包括is_repeat字段并改进代理池为空时的阻塞处理

DB.py

@@ -146,18 +146,25 @@ class DBVidcon:
         print(f"[回滚] 已退回 {len(payloads)} 条")
 
     def upsert_video(self, data: dict):
-        """
-        1) 插入到 sh_dm_video_op_v2  
-        2) DELETE sh_dm_video_v2 WHERE rn = … AND v_xid = …  
-        3) INSERT INTO sh_dm_video_v2 (…) VALUES (…)
-        """
-        # 保底字段
         data.setdefault("a_id", 0)
         data.setdefault("history_status", "")
         data.setdefault("is_repeat", 3)
         data["sort"] = data.get("index", 0)
 
         try:
+            select_repeat = """
+                SELECT is_repeat
+                  FROM sh_dm_video_v2
+                 WHERE rn    = %(rn)s
+                   AND v_xid = %(v_xid)s
+                 LIMIT 1
+            """
+            self.cursor.execute(select_repeat, data)
+            row = self.cursor.fetchone()
+            if row:
+                data['is_repeat'] = row[0]
+
+            # 2. 插入到 op 表
             sql_op = """
             INSERT INTO sh_dm_video_op_v2 (
                 v_id, v_xid, a_id, level, name_title,
@@ -170,12 +177,16 @@ class DBVidcon:
             )
             """
             self.cursor.execute(sql_op, data)
+
+            # 3. 删除旧表中的那行
             sql_del = """
             DELETE FROM sh_dm_video_v2
              WHERE rn    = %(rn)s
                AND v_xid = %(v_xid)s
             """
             self.cursor.execute(sql_del, data)
+
+            # 4. 带上 is_repeat 再插入新数据
             sql_ins = """
             INSERT INTO sh_dm_video_v2 (
                 v_id, v_xid, rn, v_name, title, link,
@@ -183,18 +194,19 @@ class DBVidcon:
                 watch_number, follow_number, video_number,
                 public_time, cover_pic, sort,
                 u_xid, u_id, u_pic, u_name,
-                    status, createtime, updatetime
+                status, createtime, updatetime,
+                is_repeat
             ) VALUES (
                 %(v_id)s, %(v_xid)s, %(rn)s, %(v_name)s, %(title)s, %(link)s,
-                    3, '', %(duration)s,
+                %(is_piracy)s, '', %(duration)s,
                 %(watch_number)s, %(fans)s, %(videos)s,
                 %(create_time)s, %(cover_pic)s, %(sort)s,
                 %(u_xid)s, %(u_id)s, %(u_pic)s, %(u_name)s,
-                    1, UNIX_TIMESTAMP(), UNIX_TIMESTAMP()
+                1, UNIX_TIMESTAMP(), UNIX_TIMESTAMP(),
+                %(is_repeat)s
             )
             """
             self.cursor.execute(sql_ins, data)
-
         except Exception as e:
             # 打印错误并回滚
             print("[数据库写入异常]", str(e))
@@ -212,7 +224,7 @@ class DBVidcon:
     def get_proxy(self, region_code: str) -> str:
         """
         从 Redis 队列 proxy_queue:<region_code> 弹出一个代理并返回。
-        如果队列为空，返回空字符串。
+        如果队列为空，阻塞
         """
         proxy = ""
         while True:

main.py

@@ -15,12 +15,12 @@ proxies_address = {
     "印度尼西亚": "ID",
     "马来":       "MY",
     "加拿大":     "CA",
-    "台湾":       "TW", #"CN_city_TW",
+    "台湾":       "CN_city_TW", # "TW", #
     "泰国":       "TH",
     "美国":       "US",
     "西班牙":     "ES",
     "韩国":       "KR",
-    "香港":       "HK", #"CN_city_HK",
+    "香港":       "CN_city_HK", # "HK", #
     "越南":       "VN",
 }
 MACHINE_ID = None
@@ -137,6 +137,7 @@ def post_with_retry(url, json_payload=None, data=None, headers=None, proxies=Non
     for attempt in range(1, retries + 1):
         try:
             proxy_str = db.get_proxy(Gproxies)
+
             proxies = {"http": proxy_str, "https": proxy_str}
 
             resp = requests.post(

multi_proxy_refill.py

@@ -28,12 +28,12 @@ PROXIES_ADDRESS = {
     "印度尼西亚": "ID",
     "马来":       "MY",
     "加拿大":     "CA",
-    "台湾":       "TW", #"CN_city_TW",
+    "台湾":       "CN_city_TW", #"TW", #
     "泰国":       "TH",
     "美国":       "US",
     "西班牙":     "ES",
     "韩国":       "KR",
-    "香港":       "HK", #"CN_city_HK",
+    "香港":       "CN_city_HK", #"HK", #
     "越南":       "VN",
 }
 

mysql_to_xlsx.py

@@ -39,10 +39,7 @@ def get_data_for_rn(rn: str) -> pd.DataFrame:
             v.watch_number       AS 观看数量,
             v.public_time        AS 上传时间,
             v.u_pic              AS 头像,
-          CASE
-            WHEN dup.cnt > 1 THEN 1
-            ELSE 2
-          END                  AS 是否重复,
+            v.is_repeat          AS 是否重复,   -- 直接用字段
             op.sort              AS 排序,
             op.batch             AS 批次,
             op.machine           AS 机器号,
@@ -50,15 +47,6 @@ def get_data_for_rn(rn: str) -> pd.DataFrame:
             v.u_xid              AS u_xid,
             v.u_name             AS 用户名称
         FROM sh_dm_video_op_v2 AS op
-        LEFT JOIN (
-          SELECT
-            t.v_xid,
-            COUNT(*) AS cnt
-          FROM sh_dm_video_op_v2 AS t
-          WHERE t.batch IN (1747324254, 1747323990)
-          GROUP BY t.v_xid
-        ) AS dup
-          ON op.v_xid = dup.v_xid
         LEFT JOIN sh_dm_video_v2 AS v
           ON op.v_xid = v.v_xid
         WHERE op.rn = %s