为系统添加一个全局变量记录数据库的单词及其等级，使得数据库单词等级只需在登录时进行一次评级，大致能将点击下一篇的时间缩减为原来的10^-15次以下，感谢章翊、赵煜涵、唐伟、宋江涛同学的建议，没有他们我懒得改的

app/difficulty.py

@@ -6,12 +6,14 @@
 # Purpose: compute difficulty level of a English text
 
 import pickle
-import math
 import time
 
-from wordfreqCMD import remove_punctuation, freq, sort_in_descending_order, sort_in_ascending_order
 import snowballstemmer
 
+from wordfreqCMD import remove_punctuation, freq, sort_in_descending_order, sort_in_ascending_order
+
+# 定义一个全局的res_d， 记录数据库单词评级之后的单词及其等级
+res_d = {}
 
 def load_record(pickle_fname):
     f = open(pickle_fname, 'rb')
@@ -43,7 +45,8 @@ def convert_test_type_to_difficulty_level(d):
             result[k] = 8
     time_end = time.time()
     print('convert_test_type_to_difficulty_level totally cost', time_end - time_start)
-
+    global res_d
+    res_d = result
     return result  # {'apple': 4, ...}
 
 
@@ -55,7 +58,10 @@ def get_difficulty_level_for_user(d1, d2):
     """
     time_start = time.time()
     # TODO: convert_test_type_to_difficulty_level() should not be called every time.  Each word's difficulty level should be pre-computed.
-    d2 = convert_test_type_to_difficulty_level(d2)  # 根据d2的标记评级{'apple': 4, 'abandon': 4, ...}
+    if res_d == {}:
+        d2 = convert_test_type_to_difficulty_level(d2)  # 根据d2的标记评级{'apple': 4, 'abandon': 4, ...}
+    else:
+        d2 = res_d
     stemmer = snowballstemmer.stemmer('english')
 
     for k in d1:  # 用户的词