增加类目判断

src/main/Python/estools.py

@@ -11,6 +11,7 @@ class ESTools:
     _host = [{"host": '172.18.45.18', "port": 9200}, {"host": '172.18.45.17', "port": 9200},
              {"host": '172.18.45.16', "port": 9200}, {"host": '172.18.69.190', "port": 9200},
              {"host": '172.18.69.192', "port": 9200}]
+    # _host = 'localhost:9200'
 
     _TB_RATE = 0.7
     _JD_RATE = 0.55
@@ -18,9 +19,10 @@ class ESTools:
     def __init__(self):
         self.es = Elasticsearch(self._host)
 
-    def search_tools(self, price=0, title="", size=20):
+    def search_tools(self, price=0, title="", category="", size=20):
         """
         搜索es方法
+        :param category: 商品类目
         :param price: 券后价
         :param title: 商品名称
         :param size: 商品数量
@@ -58,21 +60,27 @@ class ESTools:
         else:
             return None
 
-    def data_format(self, price=0, title="", size=20):
+    def data_format(self, price=0, title="", category="", size=20):
+
         """
         格式化数据方法
+        :param category: 商品类目
         :param price: 券后价
         :param title: 商品标题
         :param size: 商品数量
         :return: 格式化后的数据
         """
-        res, sco = self.search_tools(price=price, title=title, size=size)
+        res, sco = self.search_tools(price=price, title=title, category=category, size=size)
         if res:
             temp = []
             # 匹配分数平均数
             score_avg = sum(sco) / len(sco)
             # 匹配分数中位数
             score_median = sco[int(len(sco) / 2)]
+            score_max = max(sco)
+            if score_max < 50:
+                return None
+            else:
                 for i in res:
                     # 对每条数据进行处理
                     # 分数大于中位数