Not allow repeated

recommender.py

@@ -29,7 +29,7 @@ def get_best_tid(current_list, ps_matrix_row, K=50, MAX_tid=10):
     topK_pid = [i for i, _ in sortedList[1:K + 1]]
 
     n = 0
-
+    new_list = []
     while (1):
 
         top_pid = topK_pid[n]
@@ -37,7 +37,8 @@ def get_best_tid(current_list, ps_matrix_row, K=50, MAX_tid=10):
         add_tid_list = df_ps_train.loc[top_pid].tid
 
         # Form new list
-        new_tid_list = current_list + add_tid_list
+        new_tid_list = new_list + add_tid_list
+        new_tid_list = [x for x in new_tid_list if x not in current_list]
         new_tid_list = list(dict.fromkeys(new_tid_list))
 
         # Check number of songs and Add to data for prediction
@@ -46,15 +47,15 @@ def get_best_tid(current_list, ps_matrix_row, K=50, MAX_tid=10):
         if (total_song > MAX_tid):
             new_tid_list = new_tid_list[:MAX_tid]
             # Add
-            current_list = new_tid_list
+            new_list = new_tid_list
             break
         else:
-            current_list = new_tid_list
+            new_list = new_tid_list
         n += 1
         if (n == K):
             break
 
-    return current_list
+    return new_list
 
 
 def inference_from_tid(list_tid, K=50, MAX_tid=10):
@@ -78,4 +79,4 @@ def inference_from_uri(list_uri, K=50, MAX_tid=10):
     with open('model/dict_tid2uri.pkl', 'rb') as f:
         dict_tid2uri = pickle.load(f)
     best_uri = [dict_tid2uri[x] for x in best_tid]
-    return best_uri
+    return best_uri