End function for recomendation_system.py

recomendation_system.py

@@ -7,7 +7,7 @@ from models.all_models import TagsUsers, TagsAdvertisement
 from collections import Counter
 
 
-def calc_data_for_recomendation_by_tags(user_id):
+def get_recomendation_by_tags(user_id):
     queryset = db.session.query(TagsUsers).filter(TagsUsers.user_id==user_id).all()
     all_tags = []
     for _ in queryset:
@@ -17,43 +17,26 @@ def calc_data_for_recomendation_by_tags(user_id):
 
     user_data = dict(Counter(all_tags))
 
-    queryset = db.session.query(TagsUsers).all()
-    print(queryset[0][0])
+    from api.api_advertisment import all_advertisments
 
-    return user_data
+    all_data = dict()
 
-print(calc_data_for_recomendation_by_tags(user_id=1))
+    for _ in all_advertisments():
+        tag_id = []
+        for val in _['adv_id_tagsadv']:
+            tag_id.append(val['connect_tags']['id'])
+        all_data[_['id']] = tag_id
 
+    result_id = calc_recomendation_by_tags(user_data, all_data)
+    return result_id
 
-"""
-
-    
-    Формат вывода: Counter({1: 3, 2: 2})
-    Функция возвращает коллекцию со словарем 
-    ключ-значение
-    ключ - tag_id
-    значение - количество повторений tag_id
-    
-    Если присвоить переменной, например val = Counter({1: 3, 2: 2}), то
-    
-    In 1: val[1]
-    Out 2: 3
-    
-    In 1: val[2]
-    Out 2: 2
-    
-
-"""
-
-input_user_data = {1: 2, 2: 21, 3: 13, 4: 9}
-input_all_data = {1: [1, 2], 2: [1, 4, 5], 3: [2], 4: [1], 5: [6], 6: [1, 2], 7: [1, 2, 3]} #  Ключ - id бращения, значения [id тэгов]
 
 input_distance_user = {1: [10, 200]}  # key - user_id, [x, y]
 input_distance_data = {1: [20, 120], 2: [25, -100], 3: [10, 133], 4: [400, 300], 5: [144, 1322], 6: [122, -10],
                        7: [-120, 1432]}  # key - id_adv
 
 
-def get_recomendation_by_tags(user_data, all_data):
+def calc_recomendation_by_tags(user_data, all_data):
     row_column_index = []
     for i in range(len(user_data)):
         row_column_index.append(randint(0, 10))
@@ -90,7 +73,7 @@ def get_recomendation_by_tags(user_data, all_data):
 
 
 def get_recomendation_by_location(user_data, all_data):
-    tags_recomendation = get_recomendation_by_tags(input_user_data, input_all_data)
+    tags_recomendation = get_recomendation_by_tags(data1)
 
     row_column_index = []
     for i in range(len(tags_recomendation)):