更新app.py

app.py

@@ -10,22 +10,21 @@ def run_hot_recall(order_data):
     hot_model.calculate_all_hot_score()
     print("热度召回已完成！")
 
-def run_itemcf(args):
+def run_itemcf(order_data, args):
     # """运行协同过滤算法"""
-    # if os.path.exists(args.interst_score_path) and os.path.exists(args.similarity_matrix_path):
-    #     os.remove(args.interst_score_path)
-    #     os.remove(args.similarity_matrix_path)
-    # # n_jobs = 4
+    if os.path.exists(args.interst_score_path) and os.path.exists(args.similarity_matrix_path):
+        os.remove(args.interst_score_path)
+        os.remove(args.similarity_matrix_path)
     
-    # # 计算user-score-item数据
-    # cal_interest_scores_model = UserItemScore()
-    # scores = cal_interest_scores_model.score(order_data)
-    # scores.to_csv(args.interst_score_path, index=False, encoding="utf-8")
-    # print("Interest Scores cal done!")
+    # 计算user-score-item数据
+    cal_interest_scores_model = UserItemScore()
+    scores = cal_interest_scores_model.score(order_data)
+    scores.to_csv(args.interst_score_path, index=False, encoding="utf-8")
+    print("Interest Scores cal done!")
     
-    # # 计算商户共现矩阵及相似度矩阵
-    # calculate_similarity_and_save_results(order_data, args.similarity_matrix_path)
-    # print("Shops similarity matrix cal done!")
+    # 计算商户共现矩阵及相似度矩阵
+    calculate_similarity_and_save_results(order_data, args.similarity_matrix_path)
+    print("Shops similarity matrix cal done!")
     
     # 运行协同过滤召回
     itemcf_model = ItemCFModel()
@@ -77,8 +76,8 @@ def run():
         run_hot_recall(order_data)
         
     elif args.run_itemcf:
-        # order_data = load_order_data_from_mysql()
-        run_itemcf(args)
+        order_data = load_order_data_from_mysql()
+        run_itemcf(order_data, args)
         
     elif args.run_itemcf_inference:
         recomments = run_itemcf_inference(args.product_code)