优化代码写法，测试指标调整

bin/start.sh

@@ -7,6 +7,6 @@ set -x
 for port in `echo '6001,6002' | tr ',' ' '`
 do
     echo $port
-    nohup python ../src/service/service.py --port=$port > ../log/console_service_$port.log 2>&1 &
+    nohup python ../src/service/recommend_service.py --port=$port > ../log/console_service_$port.log 2>&1 &
     echo $! >> .start_service.pid
 done
\ No newline at end of file

bin/test.py

@@ -45,6 +45,8 @@ def load_test_data():
 
 
 def evaluation(result_detail):
+
+    top_n_list = [1, 3, 5, 10]
     metrics = {
         'all_test_cnt': 0,
         'all_recall_cnt': 0,
@@ -54,6 +56,8 @@ def evaluation(result_detail):
         'new_user_recall_cnt': 0,
         'same_user_recall_cnt': 0,
         'similar_user_recall_cnt': 0,
+        'default_recall_cnt': 0,
+        'top_n_recall_cnt': [0] * len(top_n_list),
     }
 
     for rd in result_detail:
@@ -62,12 +66,22 @@ def evaluation(result_detail):
             metrics['all_recall_cnt'] += 1
             
             is_same_user, is_similar_user = False, False
-            for counselor in rd['recall_counselors']:
-                from_id = counselor['from'].split(' ')[1]
+            for top_n, counselor in enumerate(rd['recall_counselors']):
+                if counselor['counselor'] == rd['supplier_id']:
+                    from_info = counselor['from'].split(' ')
+                    if from_info[0] == 'top_50':
+                        metrics['default_recall_cnt'] += 1
+                    else:
+                        from_id = from_info[1]
                         if from_id == rd['uid']:
                             is_same_user = True
                         if from_id != rd['uid']:
                             is_similar_user = True
+
+                        for i, n in enumerate(top_n_list):
+                            if n > top_n:
+                                metrics['top_n_recall_cnt'][i] += 1
+
             if is_same_user:
                 metrics['same_user_recall_cnt'] += 1
 
@@ -97,8 +111,14 @@ def evaluation(result_detail):
     
     logger.info('--' * 45)
     logger.info('')
-    logger.info('用户自己召回数 {} 占总召回比例 {:.2%}'.format(metrics['same_user_recall_cnt'], metrics['same_user_recall_cnt'] / metrics['all_recall_cnt']))
-    logger.info('相似用户召回数 {} 占总召回比例 {:.2%}'.format(metrics['similar_user_recall_cnt'], metrics['similar_user_recall_cnt'] / metrics['all_recall_cnt']))
+    logger.info('用户自己召回数 {:<4} 占总召回比例 {:.2%}'.format(metrics['same_user_recall_cnt'], metrics['same_user_recall_cnt'] / metrics['all_recall_cnt']))
+    logger.info('相似用户召回数 {:<4} 占总召回比例 {:.2%}'.format(metrics['similar_user_recall_cnt'], metrics['similar_user_recall_cnt'] / metrics['all_recall_cnt']))
+    logger.info('兜底用户召回数 {:<4} 占总召回比例 {:.2%}'.format(metrics['default_recall_cnt'], metrics['default_recall_cnt'] / metrics['all_recall_cnt']))
+
+    logger.info('--' * 45)
+    logger.info('')
+    for i, n in enumerate(top_n_list):
+        logger.info('top {:<2} 的召回数 {:<4} 召回率 {:.2%}'.format(n, metrics['top_n_recall_cnt'][i], metrics['top_n_recall_cnt'][i] / metrics['all_test_cnt']))
 
 
 def do_test(args):
@@ -113,6 +133,7 @@ def do_test(args):
     recommender = UserCFRecommender(top_n=args.top_n, k=args.k, is_use_db=False)
 
     result_detail = []
+    logger.info('开始测试')
     for index, order_info in test_orders.iterrows():
         if args.max_test > 0:
             if index >= args.max_test:
@@ -124,7 +145,8 @@ def do_test(args):
             continue
 
         is_merge = args.mode == 0
-        recommend_result = recommender.recommend_with_profile(profile, is_merge=is_merge)
+        size = 10 if args.mode == 0 else 0
+        recommend_result = recommender.recommend_with_profile(profile, size=size, is_merge=is_merge)
         recall_resons = []
         for rr in recommend_result:
             if rr['counselor'] == order_info['supplier_id']:
@@ -138,6 +160,7 @@ def do_test(args):
             'is_recall': len(recall_resons) > 0,
             'recall_reason': '|'.join(recall_resons),
         })
+    logger.info('测试结束')
 
     # 测试结果统计
     evaluation(result_detail)
@@ -158,6 +181,7 @@ def update_test_data(args):
         logger.error('args.start_date 参数格式错误，%s', args.start_date)
         raise
 
+    logger.info('开始更新测试数据，测试数据获取条件为 create_time >= %s ', start_date)
     conditions = ['create_time >= "{}"'.format(start_date)]
 
     client = MySQLClient.create_from_config_file(get_conf_path())
@@ -175,8 +199,9 @@ def update_test_data(args):
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
-    parser.add_argument('--k', default=5, type=int, help='召回相似用户的数量')
+    
     parser.add_argument('--mode', default=0, type=int, help='模式：0-推荐的咨询师列表去重（默认，与实际线上一样）；1-推荐的咨询师列表没有去重')
+    parser.add_argument('--k', default=10, type=int, help='召回相似用户的数量')
     parser.add_argument('--top_n', default=5, type=int, help='每个相似用户召回的咨询师数量')
     parser.add_argument('--max_test', default=0, type=int, help='最多测试数据量')
     

src/core/recommender.py

@@ -24,7 +24,7 @@ class Recommender():
 
 class UserCFRecommender(Recommender):
 
-    def __init__(self, top_n=5, k=5, is_use_db=True) -> None:
+    def __init__(self, top_n=5, k=10, is_use_db=True) -> None:
         super().__init__()
         # 召回 top_n 个相似用户
         self.top_n = top_n
@@ -91,8 +91,8 @@ class UserCFRecommender(Recommender):
         return self.manager.profile_to_embedding(user_profile)
 
 
-    def _recommend_top(self):
-        return self.default_counselor
+    def _recommend_top(self, size=50):
+        return self.default_counselor[:size]
     
 
     def _recommend(self, user_embedding):
@@ -115,12 +115,12 @@ class UserCFRecommender(Recommender):
         return counselors
 
 
-    def recommend_with_profile(self, user_profile, count=0, is_merge=True):
+    def recommend_with_profile(self, user_profile, size=0, is_merge=True):
         user_embedding = self.user_token(user_profile)
         counselors = self._recommend(user_embedding)
 
-        # count == 0 时，不追加默认推荐咨询师
-        if count > 0:
+        # size == 0 时，不追加默认推荐咨询师
+        if size > 0:
             counselors.extend(self._recommend_top())
 
         if is_merge:
@@ -132,21 +132,21 @@ class UserCFRecommender(Recommender):
                     merged_counselors.append(counselor)
             counselors = merged_counselors
 
-        if count > 0:
-            counselors = counselors[:count]
+        if size > 0:
+            counselors = counselors[:size]
         return counselors
 
 
-    def recommend(self, user_id, count=0, is_merge=True):
+    def recommend(self, user_id, size=0, is_merge=True):
         """
         根据用户画像，推荐咨询师
         若获取不到用户画像，推荐默认咨询师（订单最多的）
         """
         user_profile = self.get_user_profile(user_id)
         if not user_profile:
-            return self._recommend_top()
+            return self._recommend_top(size)
 
-        return self.recommend_with_profile(user_profile, count, is_merge)
+        return self.recommend_with_profile(user_profile, size, is_merge)
 
 
 if __name__ == '__main__':

src/service/service.py → src/service/recommend_service.py

@@ -26,14 +26,14 @@ class RecommendHandler(tornado.web.RequestHandler):
         if uid is None:
             logger.warn('请求参数不正确，无uid')
 
-        row = self.get_argument('row', 10)
+        size = self.get_argument('size', 10)
         try:
-            row = int(row)
+            size = int(size)
         except Exception as e:
-            logger.warn('row=%s 不是数字', row)
-            row = 10
+            logger.warn('size=%s 不是数字', size)
+            size = 10
 
-        ret = yield self.run(uid, row)
+        ret = yield self.run(uid, size)
         self.write(ret)
 
 
@@ -41,24 +41,24 @@ class RecommendHandler(tornado.web.RequestHandler):
     def post(self):
         param = json.loads(self.request.body.decode('utf-8'))
         uid = param.get('uid', None)
-        row = param.get('row', 10)
+        size = param.get('size', 10)
         if uid is None:
             logger.warn('请求参数不正确，无uid')
 
-        ret = yield self.run(uid, row)
+        ret = yield self.run(uid, size)
         self.write(ret)
 
 
     @run_on_executor
-    def run(self, uid, row=10):
-        logger.info('request@@uid=%s@@row=%s', uid, row)
+    def run(self, uid, size=10):
+        logger.info('request@@uid=%s@@size=%s', uid, size)
         try:
-            recommend_result = recommender.recommend(uid, count=row, is_merge=True)
+            recommend_result = recommender.recommend(uid, size=size, is_merge=True)
             ret = {
                 'status': 'success',
                 'code': 0,
                 'data': recommend_result,
-                'row': len(recommend_result),
+                'total_count': len(recommend_result),
             }
         except Exception as e:
             logger.error('执行推荐函数报错', exc_info=True)
@@ -66,7 +66,7 @@ class RecommendHandler(tornado.web.RequestHandler):
                 'status': 'error',
                 'code': 1,
                 'data': [],
-                'row': 0,
+                'total_count': 0,
             }
 
         ret_str = json.dumps(ret, ensure_ascii=False)