from datetime import datetime
import pickle
import json
from config import logger
from config import subject_xdeepfm_rank_dict
from config import subject_bst_rank_dict
from config import test_user_id
from matching.subject.cold_start_recall import cold_start_user_recall


logger.info('加载实训推荐离线排序字典')
xdeepfm_rank_dict = pickle.load(open(subject_xdeepfm_rank_dict, 'rb'))
bst_rank_dict = pickle.load(open(subject_bst_rank_dict, 'rb'))

def subject_recommend_offline(user_id, disciplines_id_list=None, topk=100, rank_method='1'):
    """
    根据用户ID获取推荐的实训ID列表
    直接从计算好的离线排序字典中取出数据返回
    """
    start_time = datetime.now()

    logger.info(f"本次需要进行推荐的用户ID: {user_id}")

    has_data = False
    rank_list = []
    rank_list.clear()
    recommend_results = {}
    recommend_results.clear()

    # 如果离线排序字典中有此用户则直接取出
    if rank_method == '1':
        if user_id in xdeepfm_rank_dict:
            has_data = True
            rank_list = xdeepfm_rank_dict[user_id]
    else:
        if user_id in bst_rank_dict:
            has_data = True
            rank_list = bst_rank_dict[user_id]

    # 没有召回数据则根据兴趣标签使用冷启动召回推荐
    if has_data == False:
        recommend_results = cold_start_user_recall(user_id,disciplines_id_list, topk=topk)
    else:
        if topk > len(rank_list):
            topk = len(rank_list)

        # 取topk个返回
        rank_list = rank_list[:topk]

        recommend_results = {subject_id: subject_name for subject_id, subject_name in rank_list}

    # 计算耗时毫秒
    end_time = datetime.utcnow()
    cost_time_millisecond = round(float((end_time - start_time).microseconds / 1000.0), 3)    

    logger.info(f"本次推荐总耗时: {cost_time_millisecond} 毫秒")
    return recommend_results
    

if __name__ == '__main__':
    recommend_results = subject_recommend_offline(user_id=test_user_id, 
                                                disciplines_id_list=[1,2], 
                                                topk=100, 
                                                rank_method=1)
    print(json.dumps(recommend_results, ensure_ascii=False, indent=4))