BrandCultivation/models/recall/hot_recall.py

#!/usr/bin/env python
# -*- encoding: utf-8 -*-
'''
@filename     : hot_recall.py
@description     : 热度召回算法   
@time     : 2025/01/21/00
@author     : Sherlock1011 & Min1027
@Version     : 1.0
'''
import pandas as pd
from database import RedisDatabaseHelper
from tqdm import tqdm

class HotRecallModel:
    def __init__(self, order_data):
        self._redis_db = RedisDatabaseHelper()
        self._hotkeys = self.get_hotkeys()
        self._order_data = order_data


    def get_hotkeys(self):
        info = self._redis_db.redis.zrange("configs:hotkeys", 0, -1, withscores=True)
        hotkeys = []
        for item, _ in info:
            hotkeys.append(item)
        return hotkeys
        
    def _calculate_hot_score(self, hot_name):
        """
        根据热度指标计算热度得分
        :param hot_name: 热度指标A
        :type param: string
        :return: 所有热度指标的得分
        :rtype: list
        """
        results = self._order_data.groupby("BB_RETAIL_CUSTOMER_CODE")[hot_name].mean().reset_index()
        sorted_results = results.sort_values(by=hot_name, ascending=False).reset_index(drop=True)
        item_hot_score = []
        # mock热度召回最大分数
        max_score = 1.0
        total_score = sorted_results.loc[0, hot_name] / max_score
        for row in sorted_results.itertuples(index=True, name="Row"):
            item = {row[1]:(row[2]/total_score)*100}
            item_hot_score.append(item)
        return {"key":f"{hot_name}", "value":item_hot_score}

    def calculate_all_hot_score(self, city_uuid):
        """
        计算所有的热度指标得分
        """
        # hot_datas = []
        for hotkey_name in tqdm(self._hotkeys, desc="hot_recall:正在计算热度分数"):
            self.to_redis(self._calculate_hot_score(hotkey_name), city_uuid)

    def to_redis(self, rec_content_score, city_uuid):
        hotkey_name = rec_content_score["key"]
        rec_item_id = f"hot:{city_uuid}:{str(hotkey_name)}" # 修正 rec_item_id 拼接方式
        print("自动清除历史id前数量", self._redis_db.redis.zcard(rec_item_id))
        # 清空 sorted set 数据，确保不会影响后续的存储
        self._redis_db.redis.delete(rec_item_id)
        print("自动清除历史id后数量", self._redis_db.redis.zcard(rec_item_id))
         
        res = {}

        for item in rec_content_score["value"]:  
            for content, score in item.items():  # item 形如 {A001: 75.0}
                res[content] = float(score)  # 确保 score 是 float 类型

        if res:  # 只有当 res 不为空时才执行 zadd
            self._redis_db.redis.zadd(rec_item_id, res)


if __name__ == "__main__":
    # 序列化
    model = HotRecallModel()
    model.calculate_all_hot_score()
    # joblib.dump(model, "hot_recall.model")