python redis连接 有序集合去重

# -*- coding: utf-8 -*- import redisfrom constant import redis_ip,redis_db,redis_pw,logger,redis_zset_clean_date,redis_zset_name,   move_file_lmpool = redis.ConnectionPool(host=redis_ip,db=redis_db,password=redis_pw)# pool = redis.ConnectionPool(db=6,password=redis_pw)rr = redis.Redis(connection_pool=pool)  # # 客户端StrictRedis=Redis 合并了pipe = rr.pipeline(transaction=True)  # 批量操作,遇到异步容易出错,可以不使用,直接用 rr 连接对象,一次一个添加def distinct_md5(date,eml_md5,eml_path,redis_fail_path):　　#    # pipe.zadd(redis_zset_name,date)   # pipe.zadd(redis_zset_name,{date: eml_md5},nx=True)  # nx 只插入,存在的值不会修改其分数   # pipe.zadd(redis_zset_name,{date: eml_md5})   pipe.zadd(redis_zset_name,{eml_md5: date})   return pipe.execute()[0]  # 1 添加,0 没添加   # pipe.zcard(‘eml_md5_zset‘)  # 查看总个数def del_redis_md5(n,m):  # 按照分数值进行删除   try:      pipe.zremrangebyscore(redis_zset_name,n,m)   except Exception as e:      logger.warning("删除Redis缓存中md5值失败: {},".format(e))      return   pipe.execute()#  return# return pipe.execute()[0]def clean_redis_zset(md5_score):   if md5_score <= redis_zset_clean_date:      md5_score += 31   md5_clean_score = md5_score - redis_zset_clean_date   del_redis_md5(md5_clean_score - 0.5,md5_clean_score + 0.5)  # 清理Redis上的md5  闭区间# print(distinct_md5(redis_zset_name,"qwe",2,"sdfsd","sdfsdf"))#print(distinct_md5(27,"qweqwe","sdfsdf"))# print(del_redis_md5(redis_zset_name,1,10))