add

search/utils/auto_tips.py

@@ -95,10 +95,7 @@ def get_suggest_tips(query, lat, lng, offset=0, size=50):
             QUERY_KEY = "query:{}:search_tips"
             query_base64 = base64.b64encode(query.encode('utf8')).decode('utf8')
             key = QUERY_KEY.format(query_base64)
-            logging.info("get key:%s" % key)
             labels = list(map(lambda x: x.decode("utf8"), list(redis_client.smembers(key))))
-            logging.info("get labels:%s" % labels)
-
             for i in labels:
                 ori = i.split(":")[0]
                 ori_name = base64.b64decode(ori.encode('utf8')).decode('utf8')

trans2es/commons/words_utils.py

@@ -170,7 +170,6 @@ from gm_types.doris import MIND_TYPE
 
 QUERY_KEY = "query:{}:set"
 
-
 LABEL_VALUE = {
     MIND_TYPE.PROJECT: 8,
     MIND_TYPE.HOSPITAL: 7,
@@ -202,8 +201,5 @@ def get_tips_word_type(query=''):
     labels.append(MIND_TYPE.UNKNOWN)
     if query in QUERY_WORD_LABEL_NEED_MODIFIED:
         labels.append(MIND_TYPE.PROJECT)
-
-    logging.info("get labels:%s" % labels)
     labels.sort(key=label_key, reverse=True)
     return labels[0]
-

trans2es/type_info.py

@@ -147,18 +147,6 @@ class TypeInfo(object):
                         suggest_dict["suggest_type"] = suggest_item["suggest_type"]
                         suggest_dict["offline_score"] = suggest_item["word_weight"] + suggest_dict["order_weight"]
                         suggest_dict["id"] = str(suggest_dict["id"]) + "_" + str(suggest_item["cur_index"])
-                        # if suggest_item["suggest_type"] == 1 and item_dict["tips_name_type"] == 4:
-                        #     for resemble in resemble_list:
-                        #         suggest_item["input"].append(str(resemble))
-                        #
-                        #     suggest_dict["suggest"] = {
-                        #         "input": suggest_item["input"],
-                        #         "weight": int(suggest_dict["offline_score"]),
-                        #         "contexts": {
-                        #             "is_online": suggest_dict["is_online"]
-                        #         }
-                        #     }
-                        # else:
                         suggest_dict["suggest"] = {
                             "input": suggest_item["input"],
                             "weight": int(suggest_dict["offline_score"]),
@@ -167,7 +155,7 @@ class TypeInfo(object):
                             }
                         }
                         data_list.append(suggest_dict)
-                        # if item_dict["tips_name_type"] != 4:
+                        if item_dict["tips_name_type"] != 4:
                             for resemble_item in resemble_list:
                                 resemble_dict = copy.deepcopy(suggest_dict)
                                 resemble_dict["id"] = suggest_dict["id"] + "_" + getMd5Digest(resemble_item)
@@ -176,9 +164,8 @@ class TypeInfo(object):
                                 resemble_dict["offline_score"] = 0
                                 resemble_dict["suggest"]["weight"] = 0
                                 data_list.append(resemble_dict)
-
-                        # else:
-                        #     pass
+                        else:
+                            pass
                 except Exception:
                     traceback.print_exc()
                     logging.exception('bulk_get_data for name={}, doc_type={}, pk={}'.format(

trans2es/utils/wordresemble.py

@@ -151,11 +151,9 @@ class WordResemble(object):
 
             # result = wordresemble.WordRel.objects.all().values("keyword", "id")
             # for wordrm in result:
-            logging.info("get instance:%s" % instance.keyword)
             query_sql_item = wordresemble.WordRel.objects.filter(keyword=instance.keyword)
             for sql_obj in query_sql_item:
                 words = list(sql_obj.all_resembles.all().values_list('word', flat=True))
-                logging.info("get words:%s" % words)
                 for items in words:
                     # 先存储本体词
                     query_base64 = base64.b64encode(instance.keyword.encode('utf8')).decode('utf8')
@@ -170,7 +168,6 @@ class WordResemble(object):
                         total_count = int(redis_val_dict['t'])
 
                     # 存储到Redis
-                    logging.info("get items:%s" % items)
                     value = value_name + str(":" + str(total_count))
                     redis_client.sadd(key, value)