mapping回归测试,更改部分代码

J_feature/催收模型调试.ipynb

@@ -1142,7 +1142,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.4"
+   "version": "3.6.6"
   }
  },
  "nbformat": 4,

J_feature/紧急联系人运营商特征_test.ipynb

@@ -768,7 +768,6 @@
     {
      "ename": "ValueError",
      "evalue": "All objects passed were None",
-     "output_type": "error",
      "traceback": [
       "---------------------------------------------------------------------------",
       "ValueError                                Traceback (most recent call last)",
@@ -777,7 +776,8 @@
       "/Users/zhangpengcheng/.pyenv/versions/3.6.0/lib/python3.6/site-packages/pandas/core/reshape/concat.py in concat(objs, axis, join, join_axes, ignore_index, keys, levels, names, verify_integrity, copy)\n    210                        keys=keys, levels=levels, names=names,\n    211                        verify_integrity=verify_integrity,\n--> 212                        copy=copy)\n    213     return op.get_result()\n    214 \n",
       "/Users/zhangpengcheng/.pyenv/versions/3.6.0/lib/python3.6/site-packages/pandas/core/reshape/concat.py in __init__(self, objs, axis, join, join_axes, keys, levels, names, ignore_index, verify_integrity, copy)\n    261 \n    262         if len(objs) == 0:\n--> 263             raise ValueError('All objects passed were None')\n    264 \n    265         # consolidate data & figure out what our result ndim is going to be\n",
       "ValueError: All objects passed were None"
-     ]
+     ],
+     "output_type": "error"
     }
    ],
    "source": [

config/concat_sql.py

@@ -61,11 +61,11 @@ con_urgent_people = create_engine('mysql+pymysql://drisk_controlpro:uijk78ytlk95
                                ,echo=False)
 
 #身份证归属地（省）黑名单标志
-con_realtime_hmd = create_engine('mysql+pymysql://vcc_black_list_w:Kz8p0Wf0iw7nIV85@guangdadb.xyqb.com:3306/vcc_black_list?charset=utf8',echo=False)
+con_realtime_hmd = create_engine('mysql+pymysql://qa:qatest@172.17.5.8:31110/vcc_black_list?charset=utf8',echo=False)
 #近一个月通话记录成功爬取标志
 con_day30_sql = create_engine('mysql+pymysql://qa:qatest@172.30.220.9:3306/lkb_spider?charset=utf8',echo=False)
 
 """vcc 三期"""
-con_vccthree_acsdb = create_engine('mysql+pymysql://qa:qatest@172.17.5.10:31110/acsdb?charset=utf8',echo=False)
+con_vccthree_acsdb = create_engine('mysql+pymysql://qa:qatest@172.17.5.8:31110/acsdb?charset=utf8',echo=False)
 
-con_vccthree_vcc_talos = create_engine('mysql+pymysql://qa:qatest@172.17.5.10:31110/vcc_talos?charset=utf8',echo=False)
\ No newline at end of file
+con_vccthree_vcc_talos = create_engine('mysql+pymysql://qa:qatest@172.17.5.8:31110/vcc_talos?charset=utf8',echo=False)
\ No newline at end of file

features/calc_features/DoubleLoan.py

@@ -11,7 +11,6 @@ class __INIT__(BF):
         time_now = datetime.datetime.strptime(datetime.datetime.strftime(datetime.datetime.now(),'%Y-%m-%d %H:%M:%S'),'%Y-%m-%d %H:%M:%S')
         BF.df_loan_all = Sql_contactsOperator.getSql_loanAll(str(tuple([self.user_id])).replace(',)',')'))
         BF._apply_at = time_now
-
         BF.df_apply_order = pd.DataFrame()
         BF.df_loan_rollBack = pd.DataFrame()
 
@@ -168,11 +167,16 @@ class delq_days_max():
     """delq_days_max_days_v2	delq_days_max   历史最大逾期天数(可正可负)"""
     def feature(self):
         _delq_days_max = -9999999
+
         if self.df_loan_rollBack.empty == False:
-            df_loan = self.df_loan_rollBack#.loc[self.df_loan_rollBack['progress'] == 16]
-            df_loan['observationTime'] = df_loan['observationTime'].apply(lambda x : datetime.datetime.strptime(datetime.datetime.strftime(x,'%Y-%m-%d 00:00:00'),'%Y-%m-%d 00:00:00'))
-            df_loan['loan_paid_at'] = df_loan['loan_paid_at'].apply(lambda x : datetime.datetime.strptime(datetime.datetime.strftime(x,'%Y-%m-%d 00:00:00'),'%Y-%m-%d 00:00:00'))
-            df_loan = df_loan[df_loan['observationTime']>df_loan['loan_paid_at']]
+            df_loan = self.df_loan_rollBack  # .loc[self.df_loan_rollBack['progress'] == 16]
+            df_loan['observationTime'] = df_loan['observationTime'].apply(
+                lambda x: datetime.datetime.strptime(datetime.datetime.strftime(x, '%Y-%m-%d 00:00:00'),
+                                                     '%Y-%m-%d 00:00:00'))
+            df_loan['loan_paid_at'] = df_loan['loan_paid_at'].apply(
+                lambda x: datetime.datetime.strptime(datetime.datetime.strftime(x, '%Y-%m-%d 00:00:00'),
+                                                     '%Y-%m-%d 00:00:00'))
+            df_loan = df_loan[df_loan['observationTime'] > df_loan['loan_paid_at']]
             if df_loan.empty == False:
                 _delq_days_max = df_loan['passdue_day'].max()
         self._result['delq_days_max']['value'] = _delq_days_max

features/calc_features/RevealTheBottomChannel.py

@@ -25,6 +25,7 @@ class __INIT__(BF):
             BF.df_loan_rollBack = Sql_complexOrder.get_Loan_rollBack(BF.df_loan_all,BF._apply_at)
 
 class 进件订单所在渠道的未结清订单总数():
+    """current_channel_unfinished_loan_cnt 进件订单所在渠道的未结清订单总数"""
     def feature(self):
         _进件订单所在渠道的未结清订单总数 = -9999999
         if self._df_loan_apply.empty == False:
@@ -39,6 +40,7 @@ class 进件订单所在渠道的未结清订单总数():
         return self._result
 
 class 进件订单在兜底渠道未结清订单总数():
+    """bottom_channel_unfinished_loan_cnt  进件订单在兜底渠道未结清订单总数"""
     def feature(self):
         _进件订单在兜底渠道未结清订单总数 = -9999999
         if self.df_loan_rollBack.empty == False:

features/calc_features/VccContact.py

@@ -28,7 +28,6 @@ class __INIT__(BF):
             BF._created_at = datetime.datetime.strptime(df_auth['modifyDate'].max(), '%Y-%m-%d %H:%M:%S')
 
         BF._apply_at = time_now
-        BF.register_hmd = user_register(self.uuid)
         BF.get_id_hmd = get_idcard_detail(self.uuid)
 
         if self.orderId:
@@ -44,7 +43,6 @@ class __INIT__(BF):
             BF._df_telephone = getSql_unicomCallInfoDataService_one(user_phone = BF._user_phone ,time_start = BF._created_at_from,time_end = BF._created_at)
         elif userSource == 'DIANXIN':
             BF._df_telephone = getSql_telecomCallInfoDataService_one(user_phone = BF._user_phone,time_start = BF._created_at_from,time_end = BF._created_at)
-        BF.day30paqu = day30_Call_record_spider(self.uuid)
 
 
 ################################## VCC
@@ -254,8 +252,9 @@ class 注册手机号码黑名单标志():
     """user_phone_is_black  注册手机号码黑名单标志"""
     def feature(self):
         _注册手机号码黑名单标志 = -9999999
-        if self.register_hmd.empty == False:
-            zhuce_hmd_df = self.register_hmd
+        register_hmd = user_register(self.uuid)
+        if register_hmd.empty == False:
+            zhuce_hmd_df = register_hmd
             _df_qgblack_1 = getSql_relation_in_qgblack(str(tuple(zhuce_hmd_df["phone_no"])).replace(',)', ')'),self._apply_at)
             _df_qgblack = _df_qgblack_1.drop_duplicates(['phone'])
             _注册手机号码黑名单标志 = _df_qgblack['phone'].count()
@@ -331,8 +330,9 @@ class 手机号归属地黑名单标志():
 
     def feature(self):
         _手机号归属地黑名单标志 = -9999999
-        if self.register_hmd.empty == False:
-            get_zc_hmd = self.register_hmd["phone_no"].values[0]
+        register_hmd = user_register(self.uuid)
+        if register_hmd.empty == False:
+            get_zc_hmd = register_hmd["phone_no"].values[0]
             get_zc_hmd_1 = str(get_zc_hmd)[0:7]
             _df = phone_Location_Attribution_black(int(get_zc_hmd_1), self._apply_at)["count"][0]
             if _df > 0:
@@ -348,9 +348,8 @@ class 近一个月通话记录成功爬取标志():
     """user_call_spider_in_m1   近一个月通话记录成功爬取标志"""
     def feature(self):
         _近一个月通话记录成功爬取标志 = -9999999
-        if self.day30paqu.empty == False:
-            day30paqu = self.day30paqu
-
+        day30paqu = day30_Call_record_spider(self.uuid)
+        if day30paqu.empty == False:
             day30paqu["days30_spider"] = self._apply_at
             day30paqu['days30_spider'] = pd.to_datetime(day30paqu['days30_spider'])
             day30paqu['update_at'] = pd.to_datetime(day30paqu['update_at'])
@@ -424,12 +423,9 @@ class 近150天内有效通话次数():
         _近150天内有效通话次数 = -9999999
         if self._df_telephone.empty == False:
             df = self._df_telephone
-            # df["receiverPhone"] = df["receiverPhone"].map(lambda x: x if re.match(r'^(1[3546789]\d{9})$', str(x)) else np.nan)
-            # df = df.dropna(subset=["receiverPhone"])
             df = df_filter(df)
-            # df["receiverPhone"] = df["receiverPhone"].astype(np.int64)
+            df = df.dropna(subset=['tradeTime'])
             df["tradeTime"] = df["tradeTime"].astype(np.int)
-            # df = df[df["tradeTime"] < 120]
             df = df.loc[df['tradeTime'] > 120]
             _近150天内有效通话次数 = len(df)
         self._result['近150天内有效通话次数']['value'] = _近150天内有效通话次数

features/calc_features/VccContact_V2.py

@@ -116,7 +116,7 @@ class 测试白名单():
         _测试白名单 = -9999999
         if self.register_white.empty == False:
             get_user_white = self.register_white["id_no"].values[0]
-            _df = id_is_whitelist(int(get_user_white), self._apply_at)["count"][0]
+            _df = id_is_whitelist(str(get_user_white), self._apply_at)["count"][0]
             if _df > 0:
                 _df_qgblack_1_1 = 1
             else:

features/calc_features/VccContact_V3.py

@@ -58,6 +58,8 @@ class 当日申请进件客户数():
         if day_incoming_from.empty == False:
             day_incoming_from = day_incoming_from["count"].sum()
             _当日申请进件客户数 = day_incoming_from
+        elif day_incoming_from.empty == True:
+            _当日申请进件客户数 = 0
         self._result['当日申请进件客户数']['value'] = _当日申请进件客户数
         return self._result
 
@@ -71,6 +73,8 @@ class 当日申请通过客户数():
             day_cross_from = day_cross_from[day_cross_from["applyStatus"]==2]
             day_cross_from = day_cross_from["count"].sum()
             _当日申请通过客户数 = day_cross_from
+        elif day_cross_from.empty == True:
+            _当日申请通过客户数 = 0
         self._result['当日申请通过客户数']['value'] = _当日申请通过客户数
         return self._result
 

features/calc_features/VccContact_V4.py

@@ -15,7 +15,6 @@ class __INIT__(BF):
         time_now = datetime.datetime.strptime(datetime.datetime.strftime(datetime.datetime.now(),'%Y-%m-%d %H:%M:%S'),'%Y-%m-%d %H:%M:%S')
         BF._created_at = time_now  #获取用户的手机号
         user_detail = getSql_userPhone_one(str(tuple([self.user_id])).replace(',)',')'))
-        BF._user_id_one = str(tuple(user_detail['user_id'].tolist())).replace(',)',')')
         BF._user_phone = user_detail['phone_no'].values[0]
         BF.get_phone_white_from = sale_phone_white(BF._user_phone)
 

features/calc_features/complexOrder.py

@@ -10,7 +10,7 @@ class __INIT__(BF):
         BF.df_loan = get_sql_user_in_loan(self.user_id)
         BF.df_loan.sort_values('loan_id',inplace = True)
         pass
-
+###多订单一期
 class current_loan_order_nums():
     """当前在贷订单数"""
     def feature(self):
@@ -32,7 +32,7 @@ class current_loan_term_nums():
         return self._result
 
 class current_loan_max_term():
-    """当前在贷最大期数"""
+    """uncompleted_loan_max_term_nums  当前在贷最大期数"""
     def feature(self):
         df_loan = self.df_loan
         _current_loan_max_term = -9999999
@@ -74,7 +74,7 @@ class current_loan_avg_repay():
         if df_loan.empty == False:
             x,y = str(float(df_loan.loc[df_loan['repayment_status']!=3]['required_repayment'].sum()/df_loan.loc[df_loan['repayment_status']!=3]['term_no'].count())).split('.')
             _current_loan_avg_repay = float(x+'.'+y[:6])
-        self._result[""]['value'] = _current_loan_avg_repay
+        self._result["current_loan_avg_repay"]['value'] = _current_loan_avg_repay
         return self._result
 
 class current_loan_max_repay():
@@ -191,8 +191,8 @@ class days_from_lastdue():
             if df_loan.loc[df_loan['passdue_day'] > 0].empty:
                 _days_from_lastdue = 0
             else:
-                passdue_day_max = datetime.strptime(str(df_loan.loc[df_loan['passdue_day'] > 0]['deadline'].max()).split(' ')[0],"%Y-%m-%d")
-                _days_from_lastdue = (datetime.now() - passdue_day_max).days
+                passdue_day_max = datetime.datetime.strptime(str(df_loan.loc[df_loan['passdue_day'] > 0]['deadline'].max()).split(' ')[0],"%Y-%m-%d")
+                _days_from_lastdue = (datetime.datetime.now() - passdue_day_max).days
         self._result["days_from_lastdue"]['value'] =_days_from_lastdue
         return self._result
 
@@ -202,8 +202,10 @@ class days_from_lastrepaid():
         _days_from_lastrepaid= -9999999
         df_loan = self.df_loan
         if df_loan.empty == False:
-            record_last_day = datetime.strptime(str(df_loan.loc[(df_loan['repayment_status'] ==3 )]['repaid_at'].max()).split(' ')[0],"%Y-%m-%d")
-            _days_from_lastrepaid =  int((datetime.now() - record_last_day).days)
+            df_loan_status = df_loan.loc[(df_loan['repayment_status'] == 3)]
+            if df_loan_status.empty ==False:
+                record_last_day = datetime.datetime.strptime(str(df_loan_status['repaid_at'].max()).split(' ')[0],"%Y-%m-%d")
+                _days_from_lastrepaid = int((datetime.datetime.strptime(datetime.datetime.strftime(datetime.datetime.now(),'%Y-%m-%d '),'%Y-%m-%d ') -record_last_day).days)
         self._result["days_from_lastrepaid"]['value'] = _days_from_lastrepaid
         return self._result
 
@@ -213,8 +215,8 @@ class current_loan_0duedays_rate():
         _current_loan_0duedays_rate = -9999999
         df_loan = self.df_loan
         if df_loan.empty == False:
-            if (df_loan.loc[datetime.strftime(datetime.now(),'%Y-%m-%d') > pd.to_datetime(df_loan['deadline'],format='%Y-%m-%d')]['plan_id'].count() > 0)  &( df_loan.loc[df_loan['passdue_day'] > 0 ]['passdue_day'].count() > 0):
-                x,y = str(float(df_loan.loc[df_loan['passdue_day'] > 0 ]['passdue_day'].count() / df_loan.loc[datetime.strftime(datetime.now(),'%Y-%m-%d') > pd.to_datetime(df_loan['deadline'],format='%Y-%m-%d')]['plan_id'].count())).split('.')
+            if (df_loan.loc[datetime.datetime.strftime(datetime.datetime.now(),'%Y-%m-%d') > pd.to_datetime(df_loan['deadline'],format='%Y-%m-%d')]['plan_id'].count() > 0)  &( df_loan.loc[df_loan['passdue_day'] > 0 ]['passdue_day'].count() > 0):
+                x,y = str(float(df_loan.loc[df_loan['passdue_day'] > 0 ]['passdue_day'].count() / df_loan.loc[datetime.datetime.strftime(datetime.datetime.now(),'%Y-%m-%d') > pd.to_datetime(df_loan['deadline'],format='%Y-%m-%d')]['plan_id'].count())).split('.')
                 _current_loan_0duedays_rate = float(x+'.'+y[:6])
             else : _current_loan_0duedays_rate = float(0)
         self._result["current_loan_0duedays_rate"]['value'] = _current_loan_0duedays_rate
@@ -224,9 +226,10 @@ class current_loan_0duedays_rate():
 class current_loan_5duedays_rate():
     """在贷逾期5天以上的占比 : 已放款未到期的订单中，分子是到期期数的，逾期>=5天的期数个数 分母是 到期期数的个数"""
     def feature(self):
+        _current_loan_5duedays_rate = -9999999
         df_loan = self.df_loan
         if df_loan.empty == False:
-            deadlineDay_cnt = int(df_loan.loc[datetime.strftime(datetime.now(),'%Y-%m-%d') > pd.to_datetime(df_loan['deadline'],format='%Y-%m-%d')]['plan_id'].count())
+            deadlineDay_cnt = int(df_loan.loc[datetime.datetime.strftime(datetime.datetime.now(),'%Y-%m-%d') > pd.to_datetime(df_loan['deadline'],format='%Y-%m-%d')]['plan_id'].count())
             passdueDay_cnt = int(df_loan.loc[df_loan['passdue_day'] > 5 ]['passdue_day'].count())
             if deadlineDay_cnt>0 and passdueDay_cnt > 0 :
                 x,y = str(float(passdueDay_cnt/deadlineDay_cnt)).split('.')
@@ -275,7 +278,7 @@ class current_loan_apply_cnt():
             loan_created_at = df_temp['loan_created_at'].astype(str).values[0]
             df_apply_quota_record = get_sql_apply_quota_record(user_id,loan_created_at)
             _current_loan_apply_cnt = len(df_apply_quota_record)
-        self._result["current_loan_refuse_rate"]['value'] = int(_current_loan_apply_cnt)
+        self._result["current_loan_apply_cnt"]['value'] = int(_current_loan_apply_cnt)
         return self._result
 
 class current_loan_refuse_cnt():
@@ -291,7 +294,9 @@ class current_loan_refuse_cnt():
             df_apply_quota_record = get_sql_apply_quota_record(user_id,loan_created_at)
             current_loan_apply_cnt = len(df_apply_quota_record)
             if current_loan_apply_cnt > 0 :
-                _current_loan_refuse_cnt = df_apply_quota_record.loc[df_apply_quota_record['apply_status'] == 2 ].sum()
+                df_apply_quota_record_status = df_apply_quota_record.loc[df_apply_quota_record['apply_status'] == 2]
+                if len(df_apply_quota_record_status)> 0:
+                    _current_loan_refuse_cnt = df_apply_quota_record_status['uuid'].count()
             else:
                 _current_loan_refuse_cnt = 0
 
@@ -311,10 +316,13 @@ class current_loan_refuse_rate():
             df_apply_quota_record = get_sql_apply_quota_record(user_id,loan_created_at)
             current_loan_apply_cnt = len(df_apply_quota_record)
             if current_loan_apply_cnt > 0 :
-                current_loan_refuse_cnt = df_apply_quota_record.loc[df_apply_quota_record['apply_status'] == 2 ].sum()
+                if df_apply_quota_record.loc[df_apply_quota_record['apply_status'] == 2 ].empty ==True:
+                    current_loan_refuse_cnt = 0
+                else:
+                    current_loan_refuse_cnt = df_apply_quota_record.loc[df_apply_quota_record['apply_status'] == 2 ]['uuid'].count()
             else:
                 current_loan_refuse_cnt = 0
-            if current_loan_apply_cnt > 0 & current_loan_refuse_cnt > 0 :
+            if current_loan_apply_cnt > 0 & current_loan_refuse_cnt > 0:
                 _current_loan_refuse_rate = current_loan_apply_cnt/current_loan_refuse_cnt
             else:
                 _current_loan_refuse_rate = 0

features/calc_features/complexOrder_V2.py

@@ -10,13 +10,13 @@ from dateutil.relativedelta import relativedelta
 class __INIT__(BF):
     def __init__(self):
         time_now = datetime.datetime.strptime(datetime.datetime.strftime(datetime.datetime.now(),'%Y-%m-%d %H:%M:%S'),'%Y-%m-%d %H:%M:%S')
-        BF.df_loan_all = Sql_contactsOperator.getSql_loanAll(str(tuple([self.user_id])).replace(',)',')'))
         BF._apply_at = time_now
         if self.orderId:
             _df = Sql_contactsOperator.getSql_Apply_quota_record(self.user_id,self.orderId)
             if _df.empty == False:
                 BF._apply_at = datetime.datetime.strptime(_df['apply_time'].astype(str).values[0],'%Y-%m-%d %H:%M:%S')
-
+        # BF.df_loan_all_v2 = Sql_contactsOperator.getSql_loanAll_diangdanv2(str(tuple([self.user_id])).replace(',)', ')'),str(BF._apply_at))
+        BF.df_loan_all = Sql_contactsOperator.getSql_loanAll(str(tuple([self.user_id])).replace(',)', ')'))
         BF.df_loan_rollBack = pd.DataFrame()
         if BF.df_loan_all.empty == False:
             BF.df_loan_rollBack = get_Loan_rollBack(BF.df_loan_all,BF._apply_at)
@@ -26,11 +26,16 @@ class has_loan_nums_2018():
     """user_success_loan_cnt#from2018TillNow  has_loan_nums_2018  用户2018年放款订单数 """
     def feature(self):
         _has_loan_nums_2018 = -9999999
-        df_loan = self.df_loan_rollBack
+        df_loan_all_v2 = Sql_contactsOperator.getSql_loanAll(str(tuple([self.user_id])).replace(',)', ')'))
+        df_loan = df_loan_all_v2
+        df_loan['_apply_at'] = self._apply_at
+        df_loan = df_loan [df_loan['loan_paid_at'] < df_loan['_apply_at']]
         if df_loan.empty == False:
-            # df_loan.dorp_d
+            # df_loan.dorp_d     apply_time       old loan_paid_at
             df_loan['loan_paid_at_year'] = df_loan['loan_paid_at'].dt.year
             df_loan = df_loan.loc[df_loan['loan_paid_at_year'] >= 2018]
+            # df_loan = df_loan.drop_duplicates('loan_id',keep='first')
+            # _has_loan_nums_2018 = df_loan['loan_id'].count()
             df_loan = df_loan.drop_duplicates('loan_id',keep='first')
             _has_loan_nums_2018 = df_loan['loan_id'].count()
         self._result['has_loan_nums_2018']['value'] = _has_loan_nums_2018
@@ -40,7 +45,10 @@ class has_loan_nums_2019():
     """user_success_loan_cnt#from2019TillNow  has_loan_nums_2019  用户2019年放款订单数 """
     def feature(self):
         _has_loan_nums_2019 = -9999999
-        df_loan = self.df_loan_rollBack
+        df_loan_all_v2 = Sql_contactsOperator.getSql_loanAll(str(tuple([self.user_id])).replace(',)', ')'))
+        df_loan = df_loan_all_v2
+        df_loan['_apply_at'] = self._apply_at
+        df_loan = df_loan [df_loan['loan_paid_at'] < df_loan['_apply_at']]
         if df_loan.empty == False:
             df_loan['loan_paid_at_year'] = df_loan['loan_paid_at'].dt.year
             df_loan = df_loan.loc[df_loan['loan_paid_at_year'] >= 2019]

features/calc_features/contactsToOperator.py

@@ -14,18 +14,21 @@ class __INIT__(BF):
             if _df.empty == False:
                 BF.created_at = datetime.datetime.strptime(_df['apply_time'].astype(str).values[0],'%Y-%m-%d %H:%M:%S')
 
+
         BF.user_phone = getSql_userPhone(str(tuple([self.user_id])).replace(',)',')'))['phone_no'].tolist()
         BF._df = getSql_EmergencyContact(self.user_id,BF.created_at)
         BF._df.sort_values('created_at',ascending=False,inplace=True)
         BF._df = BF._df.loc[~(BF._df['phone_no'].isin(BF.user_phone))]
+        # BF._df = BF._df.drop_duplicates(['phone_no'],keep='first')
+        # BF._df = BF._df.sort_values('created_at')
         BF._df = BF._df.iloc[:2]
         BF.contacts_phone = BF._df['phone_no'].tolist() # 获取历史联系人手机号
         pass
 
-def get_CallPhone(df_auth,uuid,user_phone,contacts_phone,day):
+def get_CallPhone(df_auth,uuid,user_phone,contacts_phone,day,apply_time):
 
     userSource = df_auth['userSource'].values[0]
-    _time = get_CallPhoneTime(userSource,uuid,user_phone,contacts_phone,day)
+    _time = get_CallPhoneTime(userSource,uuid,user_phone,contacts_phone,day,apply_time)
     df_telephone = pd.DataFrame()
     if _time:
         if userSource == 'YIDONG':
@@ -43,24 +46,34 @@ def get_CallPhone(df_auth,uuid,user_phone,contacts_phone,day):
     return df_telephone
 
 
-def get_CallPhoneTime(userSource,uuid,user_phone,contacts_phone,day):
+def get_CallPhoneTime(userSource,uuid,user_phone,contacts_phone,day,apply_time):
     df_telephone = pd.DataFrame()
     if userSource == 'YIDONG':
         df_telephone = getSql_mobileCallInfoDataService(uuid = uuid,
                                                         user_phone = user_phone,
-                                                        orderby=['timestamp','desc'],limit=1)
+                                                        orderby=['timestamp','desc'])
     elif userSource == 'LIANTONG':
         df_telephone = getSql_unicomCallInfoDataService(uuid = uuid,
                                                         user_phone = user_phone,
-                                                        orderby=['timestamp','desc'],limit=1)
+                                                        orderby=['timestamp','desc'])
     elif userSource == 'DIANXIN':
         df_telephone = getSql_telecomCallInfoDataService(uuid = uuid,
                                                          user_phone = user_phone,
-                                                         orderby=['timestamp','desc'],limit=1)
+                                                         orderby=['timestamp','desc'])
+    ###新增
+    df_telephone['timestamp'] = pd.to_datetime(df_telephone['timestamp'])
+    df_telephone['apply_at'] = BF.created_at
+    df_telephone['apply_at'] = pd.to_datetime(df_telephone['apply_at'])
+    df_telephone['cTime'] = pd.to_datetime(df_telephone['cTime'])
+    df_telephone = df_telephone.sort_values(['timestamp'])
+    df_telephone = df_telephone[df_telephone['timestamp'] <= df_telephone['apply_at']]
+
+
     if df_telephone.empty == False:
-        df_telephone['timestamp'] = df_telephone['timestamp'].apply(lambda x : str(x))
-        starttime = str(datetime.datetime.strptime(df_telephone['timestamp'].values[0] ,'%Y-%m-%d %H:%M:%S') - day)
-        endtime = df_telephone['timestamp'].values[0]
+        endtime = str(df_telephone['timestamp'].max())
+        # df_telephone['timestamp'] = df_telephone['timestamp'].apply(lambda x : str(x))
+        starttime = str(datetime.datetime.strptime(endtime ,'%Y-%m-%d %H:%M:%S') - day)
+        # endtime = df_telephone['timestamp'].values[0]
         return (starttime,endtime)
     return None
 
@@ -91,9 +104,9 @@ class call_with_relation_cnt_150():
                 contacts_phone = str(tuple(self.contacts_phone)).replace(',)',')')
                 df_telephone = get_CallPhone(df_auth,
                                              self.uuid,
-                                             str(tuple(self.user_phone)).replace(',)',')') ,
+                                             str(tuple(self.user_phone)).replace(',)',')'),
                                              contacts_phone,
-                                             datetime.timedelta(days=150))
+                                             datetime.timedelta(days=150),self.created_at)
                 if df_telephone.empty == False:
                     _call_with_relation_cnt = df_telephone['receiverPhone'].count()
 
@@ -112,7 +125,7 @@ class call_with_relation_cnt_90():
                 df_telephone = get_CallPhone(df_auth,self.uuid,
                                              str(tuple(self.user_phone)).replace(',)',')') ,
                                              contacts_phone,
-                                             datetime.timedelta(days=90))
+                                             datetime.timedelta(days=90),self.created_at)
 
                 if df_telephone.empty == False:
                     _call_with_relation_cnt = df_telephone['receiverPhone'].count()
@@ -132,7 +145,7 @@ class call_with_relation_cnt_30():
                 df_telephone = get_CallPhone(df_auth,self.uuid,
                                              str(tuple(self.user_phone)).replace(',)',')') ,
                                              contacts_phone,
-                                             datetime.timedelta(days=30))
+                                             datetime.timedelta(days=30),self.created_at)
 
                 if df_telephone.empty == False:
                     _call_with_relation_cnt = df_telephone['receiverPhone'].count()
@@ -152,7 +165,7 @@ class call_with_relation_cnt_7():
                 df_telephone = get_CallPhone(df_auth,self.uuid,
                                              str(tuple(self.user_phone)).replace(',)',')') ,
                                              contacts_phone,
-                                             datetime.timedelta(days=7))
+                                             datetime.timedelta(days=7),self.created_at)
 
                 if df_telephone.empty == False:
                     _call_with_relation_cnt = df_telephone['receiverPhone'].count()
@@ -491,7 +504,7 @@ class diffdays_fst_call_with_relation():
                 # df_telephone = pd.concat([df_mobile,df_telecom,df_unicom])
 
                 contacts_phone = str(tuple(self.contacts_phone)).replace(',)',')')
-                df_telephone = get_CallPhone(df_auth,self.uuid,str(tuple(self.user_phone)).replace(',)',')'),contacts_phone,datetime.timedelta(days=150))
+                df_telephone = get_CallPhone(df_auth,self.uuid,str(tuple(self.user_phone)).replace(',)',')'),contacts_phone,datetime.timedelta(days=150),self.created_at)
                 if df_telephone.empty == False:
                     _diffdays_fst_call_with_relation = (datetime.datetime.strptime(str(self.created_at).split(' ')[0],'%Y-%m-%d') - datetime.datetime.strptime(str(pd.to_datetime(df_telephone['cTime']).min()).split(' ')[0],'%Y-%m-%d')  ).days
         self._result['diffdays_fst_call_with_relation']['value'] = _diffdays_fst_call_with_relation
@@ -507,7 +520,7 @@ class diffdays_last_call_with_relation():
             if df_auth.empty == False:
 
                 contacts_phone = str(tuple(self.contacts_phone)).replace(',)',')')
-                df_telephone = get_CallPhone(df_auth,self.uuid,str(tuple(self.user_phone)).replace(',)',')'),contacts_phone,datetime.timedelta(days=150))
+                df_telephone = get_CallPhone(df_auth,self.uuid,str(tuple(self.user_phone)).replace(',)',')'),contacts_phone,datetime.timedelta(days=150),self.created_at)
                 if df_telephone.empty == False:
                     # _diffdays_last_call_with_relation = (self.created_at - pd.to_datetime(df_telephone['cTime']).max()).days
                     _diffdays_last_call_with_relation = (datetime.datetime.strptime(str(self.created_at).split(' ')[0],'%Y-%m-%d') - datetime.datetime.strptime(str(pd.to_datetime(df_telephone['cTime']).max()).split(' ')[0],'%Y-%m-%d')  ).days
@@ -527,7 +540,7 @@ class diffdays_call_with_relation():
                 df_telephone = get_CallPhone(df_auth,self.uuid,
                                              str(tuple(self.user_phone)).replace(',)',')') ,
                                              contacts_phone,
-                                             datetime.timedelta(days=150))
+                                             datetime.timedelta(days=150),self.created_at)
 
                 if df_telephone.empty == False:
                     diffdays_call_with_relation_min = (datetime.datetime.strptime(str(self.created_at).split(' ')[0],'%Y-%m-%d') - datetime.datetime.strptime(str(pd.to_datetime(df_telephone['cTime']).min()).split(' ')[0],'%Y-%m-%d')  ).days

features/calc_features/primary.py

@@ -15,6 +15,7 @@ class __INIT__(BF):
 
 class user_apply_refuse_cnt():
     def feature(self):
+        """user_apply_refuse_cnt"""
         #历史最大逾期天数 : 用户申请拒绝次数(一单一审放款拒绝和循环额度申请拒绝)
         _df_loan_refuse_cnt_old = get_sql_loan_refuse_cnt_old(self.user_id)
         _df_loan_refuse_cnt_new = get_sql_loan_refuse_cnt_new(self.user_id)
@@ -24,6 +25,7 @@ class user_apply_refuse_cnt():
         return self._result
 
 class diff_apply_to_last_refused_days_rc():
+
     def feature(self):
         _df_refused = get_sql_loan_refused(self.user_id)
         self._result['diff_apply_to_last_refused_days_rc']['value'] = 1000

service/Sql_complexOrder.py

@@ -14,7 +14,11 @@ def getSql_loanAll(user_id):
             when loan.created_at < '2018-05-08' then loan.created_from
             else null
             end as applied_from
-        ,if (sub.created_at is not null, sub.created_at ,loan.created_at) apply_time
+        -- ,if (sub.created_at is not null, sub.created_at ,loan.created_at) apply_time
+        ,case when loan.created_at >='2018-05-08' then aqr.apply_time
+            when loan.created_at < '2018-05-08' then if (sub.created_at is not null, sub.created_at ,loan.created_at)
+            else null
+            end as apply_time
         ,plan.id as plan_id,plan.term_no, plan.repayment_status, plan.deadline as deadline,DATE_ADD(plan.deadline,INTERVAL 1 second) as deadline_new
         ,plan.repaid_at
         ,plan.current_repayment
@@ -39,20 +43,21 @@ def get_Loan_rollBack(df_loan,apply_time,passdueDay_Negative=False):
     df_loan['observationTime'] = apply_time
     # df_loan = df_loan.loc[(df_loan['apply_time'] < df_loan['observationTime']) & (df_loan['loan_paid_at'] < df_loan['observationTime'] )]
 
-    # df_loan = df_loan.loc[ (df_loan['loan_paid_at'] < df_loan['observationTime'] )]
+
 
     df_loan['repaid_at'] = df_loan['repaid_at'].apply(lambda x : datetime.datetime.strptime(datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'),'%Y-%m-%d %H:%M:%S'))
     df_loan['deadline'] = df_loan['deadline'].apply(lambda x : datetime.datetime.strptime(datetime.datetime.strftime(x,'%Y-%m-%d 00:00:00'),'%Y-%m-%d 00:00:00'))
     df_loan['deadline'] = df_loan['deadline'].apply(lambda x : datetime.datetime.strptime(datetime.datetime.strftime(x,'%Y-%m-%d 00:00:00'),'%Y-%m-%d 00:00:00'))
     df_loan['apply_time'] = df_loan['apply_time'].apply(lambda x : datetime.datetime.strptime(datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'),'%Y-%m-%d %H:%M:%S'))
     df_loan['passdue_day'] = 0
-    df_loan = df_loan.loc[(df_loan['apply_time'] <= df_loan['observationTime'])]
+    # df_loan = df_loan.loc[(df_loan['apply_time'] <= df_loan['observationTime'])]
+    df_loan = df_loan.loc[(df_loan['loan_paid_at'] < df_loan['observationTime'])]
     if df_loan.empty == False:
         df_loan.loc[(df_loan['repaid_at'] != '2000-01-01')&(df_loan['repaid_at']>df_loan['observationTime']),'repaid_at'] = datetime.datetime.strptime('2000-01-01 00:00:00','%Y-%m-%d 00:00:00')
         # 还款时间正常 ,还款状态!=3
-        df_loan.loc[(df_loan['repaid_at'] != '2000-01-01') & (df_loan['repayment_status'] !=3 ),'repaid_at'] = datetime.datetime.strptime('2000-01-01 00:00:00','%Y-%m-%d 00:00:00')
-        # df_loan.loc[(df_loan['repaid_at'] == '2000-01-01'),'repayment_status'] = 0
-        df_loan.loc[(df_loan['repaid_at'] == '2000-01-01')& (df_loan['repayment_status'] != 3),'repayment_status'] = 0
+        df_loan.loc[(df_loan['repaid_at'] != '2000-01-01') & (df_loan['repayment_status'] !=3),'repaid_at'] = datetime.datetime.strptime('2000-01-01 00:00:00','%Y-%m-%d 00:00:00')
+        df_loan.loc[(df_loan['repaid_at'] == '2000-01-01'),'repayment_status'] = 0
+        # df_loan.loc[(df_loan['repaid_at'] == '2000-01-01')& (df_loan['repayment_status'] != 3),'repayment_status'] = 0
 
         df_loan.loc[(df_loan['repayment_status'] == 3),'passdue_day'] = (df_loan['repaid_at'] - df_loan['deadline']).dt.days
         df_loan.loc[(df_loan['repayment_status'] != 3)&(df_loan['observationTime'] > df_loan['deadline']) ,'passdue_day'] = (df_loan['observationTime'] - df_loan['deadline']).dt.days
@@ -60,11 +65,10 @@ def get_Loan_rollBack(df_loan,apply_time,passdueDay_Negative=False):
         # df_loan.loc[(df_loan['repaid_at'] != '2000-01-01'),'passdue_day'] = (df_loan['repaid_at'] - df_loan['deadline']).dt.days
         # df_loan.loc[(df_loan['repaid_at'] == '2000-01-01')&(df_loan['observationTime'] > df_loan['deadline']) ,'passdue_day'] = (df_loan['observationTime'] - df_loan['deadline']).dt.days
         # df_loan.loc[(df_loan['repaid_at'] == '2000-01-01')&(df_loan['repayment_status']==0)&(df_loan['observationTime']<df_loan['deadline']),'passdue_day'] = (df_loan['observationTime'] - df_loan['deadline']).dt.days
-
         if passdueDay_Negative == False:
             df_loan.loc[(df_loan['passdue_day'] < 0),'passdue_day'] = 0
-
         _loan_id = []
+
         for k ,v in df_loan.groupby(['loan_id']):
             _df = pd.DataFrame(v)
             if _df.loc[(_df['repayment_status']==3)]['plan_id'].count() != _df['plan_id'].count():

service/Sql_contactsOperator.py

@@ -236,7 +236,11 @@ def getSql_loanAll(user_id):
             when loan.created_at < '2018-05-08' then loan.created_from
             else null
             end as applied_from
-        ,if (sub.created_at is not null, sub.created_at ,loan.created_at) apply_time
+        -- ,if (sub.created_at is not null, sub.created_at ,loan.created_at) apply_time
+        ,case when loan.created_at >='2018-05-08' then aqr.apply_time
+            when loan.created_at < '2018-05-08' then if (sub.created_at is not null, sub.created_at ,loan.created_at)
+            else null
+            end as apply_time
         ,plan.id as plan_id,plan.term_no, plan.repayment_status, plan.deadline as deadline,DATE_ADD(plan.deadline,INTERVAL 1 second) as deadline_new
         ,plan.repaid_at
         ,plan.current_repayment,plan.required_repayment
@@ -253,10 +257,25 @@ def getSql_loanAll(user_id):
         and fest.transaction_status in (2,5)
         and loan.business_type in (0,2)
         order by loan.id,plan.id
-    """.format(user_id)
+        """.format(user_id)
+
     _df = pd.read_sql(_sql,con_tuomin_xyqb)
     return _df
 
+
+
+
+
+def getSql_loanAll_diangdanv2(user_id,apply_at):
+    """获取用户所有放款订单明细"""
+
+    _sql = """SELECT m.* FROM loan_application_history l
+JOIN loan_application_manifest_history m ON
+l.id = m.loan_application_history_id WHERE
+l.user_id in {0} AND l.progress IN (15,16,65) 
+AND l.business_type IN ( 0, 2, 4, 6 ) and m.loan_paid_at < '{1}' order by m.loan_paid_at desc""".format(user_id,apply_at)
+    _df = pd.read_sql(_sql,con_tuomin_xyqb)
+    return _df
 def getSql_loan_applyAll(user_id):
     """获取用户所有放款订单明细"""
     _sql = """
@@ -571,11 +590,12 @@ def get_user_bill_info_rows(uuid,_created_at=None,time_from=0):
     df = pd.DataFrame()
     if _response:
         df = pd.DataFrame(_response['data']['features']['user_bill_info_rows']['value'])
-        time_now = datetime.datetime.strptime(datetime.datetime.strftime((_created_at.replace(day=1) - datetime.timedelta(1)).replace(day=1),'%Y-%m-%d 00:00:00'),'%Y-%m-%d %H:%M:%S')
-        time_from = time_now - relativedelta(months=+time_from)
-        df['billDay'] = df['billDay'].apply(lambda stamp: time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(stamp/1000)))
-        # df['billDay'] = pd.to_datetime(df['billDay'])
-        df = df.loc[(df['billDay']>=str(time_from)) & (df['billDay']<str(time_now))]
+        if df.empty ==False:
+            time_now = datetime.datetime.strptime(datetime.datetime.strftime((_created_at.replace(day=1) - datetime.timedelta(1)).replace(day=1),'%Y-%m-%d 00:00:00'),'%Y-%m-%d %H:%M:%S')
+            time_from = time_now - relativedelta(months=+time_from)
+            df['billDay'] = df['billDay'].apply(lambda stamp: time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(stamp/1000)))
+            # df['billDay'] = pd.to_datetime(df['billDay'])
+            df = df.loc[(df['billDay']>str(time_from)) & (df['billDay']<=str(time_now))]
         return df
     return df
 

service/Sql_server.py

@@ -110,8 +110,8 @@ def get_sql_apply(user_id):
         SELECT
             user_id,
             apply_time,
-            case when aqr.apply_status = 1 then 1
-            else 2 end as apply_status,
+            case when apply_status = 1 then 1
+            else 2 end as apply_status
         FROM
             apply_quota_record
         WHERE user_id = {0}
@@ -123,13 +123,17 @@ def get_sql_apply(user_id):
 
 def get_sql_loan_refuse_cnt_old(user_id):
 # 一单一审放款拒绝
-    _sql = """
-      SELECT COUNT(1) count FROM loan_application_history l LEFT JOIN loan_account_ext e ON e.loan_id = l.id
-      WHERE l.user_id = {0}
-      and l.business_type IN (0,2)
-      AND l.progress IN (6,8,19) AND e.loan_id IS NULL
-
-      """
+#     _sql = """
+#       SELECT COUNT(1) count FROM loan_application_history l LEFT JOIN loan_account_ext e ON e.loan_id = l.id
+#       WHERE l.user_id = {0}
+#       and l.business_type IN (0,2,4,6)
+#       AND l.progress IN (6,8,19) AND e.loan_id IS NULL
+#
+#       """
+    _sql = """SELECT COUNT(1) count FROM loan_application_history l JOIN
+    loan_account_ext e ON e.loan_id = l.id WHERE l.user_id = {0}
+    and l.business_type IN (0,2,4,6)
+    AND l.progress = 8 """
     _df = pd.read_sql(_sql.format(user_id),con_tuomin_xyqb)
     return _df
 

service/Sql_vcc.py

@@ -470,6 +470,8 @@ def city_sign(uuid=None,order_no=None):
 
     if _response['data']['features']['user_ocr_info#address']['value'] == -9999999:
         return list([])
+    elif _response['data']['features']['user_ocr_info#address']['value'] == '':
+        return list([])
     c_list = []
     first_city = ["北京市","上海市","广州市","深圳市"]
     second_city = ["成都市", "杭州市", "重庆市", "武汉市", "苏州市", "西安市", "天津市", "南京市", "郑州市", "长沙市", "沈阳市", "青岛市", "宁波市", "东莞市", "无锡市"]
@@ -533,8 +535,12 @@ def card_expires(uuid=None,order_no=None):
         if _response['data']['features']['user_ocr_info#validDateEnd']['value'] == "?":
             return list([])
         ll_idcard = _response['data']['features']['user_ocr_info#validDateEnd']['value']
+
         if ll_idcard:
-            return int(ll_idcard)
+            if ll_idcard =='长期':
+                return 20301230
+            elif isinstance(ll_idcard,int):
+                return int(ll_idcard)
 
 
 
@@ -585,7 +591,7 @@ def id_user_credited(validity_date,user_id):
 def day_incoming_parts(Same_day_first,Same_day_next):
     """当日客户数"""
     _Sql = """select count(distinct user_id) count, apply_status applyStatus from risk_record
-     where created_at >= "{0}" and created_at < "{0}" group by apply_status;""".format(Same_day_first,Same_day_next)
+     where created_at >= "{0}" and created_at < "{1}" group by apply_status;""".format(Same_day_first,Same_day_next)
     _df = pd.read_sql(_Sql,con_vccthree_vcc_talos)
     return _df
 

service/addresss_book_sql.py

@@ -13,7 +13,7 @@ def getSql_authorizationPhone_one(uuid,userPhone):
     _sql = """
       select parentId as uuid,createDate,modifyDate,userSource,loginName
       from t_user_auth_info
-      where parentId = '{0}' and loginName in ("{1}")
+      where parentId = '{0}' and loginName in {1}
       and userSource in ('YIDONG','LIANTONG','DIANXIN')
     """.format(uuid,userPhone)
     _df = pd.read_sql(_sql,con_lkbadmin)
@@ -34,9 +34,11 @@ def getSql_userPhone_one(user_id):
 ##移动数据库
 def getSql_mobileCallInfoDataService_one(uuid = None,user_phone = None,contacts_phone = None,time_start = None,time_end = None):
     """ 移动通话记录 """
-    _sql = """
-      select uuid,cTime,tradeAddr,tradeWay,tradeType,receiverPhone,tradeTime,phone from comservice_i_mobile_call_info
-    """
+    # _sql = """
+    #   select uuid,cTime,tradeAddr,tradeWay,tradeType,receiverPhone,tradeTime,phone from comservice_i_mobile_call_info
+    # """
+    _sql = """	select uuid,cTime,tradeAddr,tradeWay,tradeType,receiverPhone,tradeTime,phone
+            from comservice_i_mobile_call_info  force index(index_mobile_call_info_phone)"""
     iswhere = []
     if user_phone:
         iswhere.append(' phone in {0}'.format(user_phone))
@@ -56,7 +58,7 @@ def getSql_mobileCallInfoDataService_one(uuid = None,user_phone = None,contacts_
     if contacts_phone:
         _sql = """
             select uuid,cTime,tradeAddr,tradeWay,tradeType,receiverPhone,tradeTime,phone
-            from comservice_i_mobile_call_info
+            from comservice_i_mobile_call_info force index(index_mobile_call_info_phone)
             where phone in ("{0}")
             and receiverPhone in ("{1}")
             and cTime  BETWEEN '{2}' and '{3}'
@@ -64,7 +66,7 @@ def getSql_mobileCallInfoDataService_one(uuid = None,user_phone = None,contacts_
     else:
         _sql = """
             select uuid,cTime,tradeAddr,tradeWay,tradeType,receiverPhone,tradeTime,phone
-            from comservice_i_mobile_call_info
+            from comservice_i_mobile_call_info force index(index_mobile_call_info_phone)
             where phone in ("{0}")
             and cTime  BETWEEN '{1}' and '{2}'
         """.format(user_phone,time_start,time_end)
@@ -78,7 +80,7 @@ def getSql_unicomCallInfoDataService_one(uuid = None,user_phone = None,contacts_
     if contacts_phone:
         _sql = """
             select uuid,cTime,tradeAddr,callType as tradeWay,tradeType,receiverPhone,tradeTime,phone
-            from comservice_i_unicom_call_info
+            from comservice_i_unicom_call_info force index(index_unicom_call_info_phone)
             where phone  in ("{0}")
              and receiverPhone in ("{1}")
             and cTime  BETWEEN '{2}' and '{3}'
@@ -87,7 +89,7 @@ def getSql_unicomCallInfoDataService_one(uuid = None,user_phone = None,contacts_
     else:
         _sql = """
             select uuid,cTime,tradeAddr,callType as tradeWay,tradeType,receiverPhone,tradeTime,phone
-            from comservice_i_unicom_call_info
+            from comservice_i_unicom_call_info force index(index_unicom_call_info_phone)
             where phone  in ("{0}")
             and cTime  BETWEEN '{1}' and '{2}'
         """.format(user_phone,time_start,time_end)
@@ -100,7 +102,7 @@ def getSql_telecomCallInfoDataService_one(uuid = None,user_phone = None,contacts
     if contacts_phone:
         _sql = """
             select uuid,cTime,tradeAddr,callWay as tradeWay,tradeType,receiverPhone,tradeTime,phone
-            from comservice_i_telecom_call_info
+            from comservice_i_telecom_call_info force index(index_telecom_call_info_phone)
             where phone  in ("{0}")
             and receiverPhone in ("{1}")
             and cTime  BETWEEN '{2}' and '{3}'
@@ -108,7 +110,7 @@ def getSql_telecomCallInfoDataService_one(uuid = None,user_phone = None,contacts
     else:
         _sql = """
             select uuid,cTime,tradeAddr,callWay as tradeWay,tradeType,receiverPhone,tradeTime,phone
-            from comservice_i_telecom_call_info
+            from comservice_i_telecom_call_info force index(index_telecom_call_info_phone)
             where phone  in ("{0}")
             and cTime  BETWEEN '{1}' and '{2}'
         """.format(user_phone,time_start,time_end)
@@ -189,22 +191,14 @@ def get_lxr_list(uuid=None,order_no=None):
     except Exception as e:
         print(e.args)
     if _response:
-        # if _response['data']['features']['user_contact_book_info#d7_contact_nums']['value'] == -9999999:
-        #     return list([-9999999])
-        # if _response['data']['features']['user_contact_book_info#d7_contact_nums']['value'] == []:
-        #     return list([])
         ll_phone = pd.DataFrame(_response['data']['features']['user_contact_book_info#d7_contact_nums']['value'])
-
         if len(ll_phone) > 0:
             l_phone =ll_phone[0].tolist()
             l_phone = [str(i).replace(" ","").replace("-","") for i in l_phone]
             l_phone = [i for i in l_phone if re.match(r'^(1[3546789]\d{9})$', str(i))]
             return l_phone
-        # else:
-        #     return list([])
     return list([])
 
-# get_lxr_list(uuid='9d75f662-04d4-4536-be35-f14f517a36f6')
 
 
 

startup.py

@@ -47,18 +47,18 @@ if __name__ == "__main__":
     # [i.setFormatter(LogFormatter()) for i in logging.getLogger().handlers]
     # tornado.options.parse_command_line()
     #
-    # # #== 本地调试
-    # app.listen(23011)
+    # # #== 本地调试get_id_hmd
+    # app.listen(23017)
     # IOLoop.instance().start()
 
 
-    #
+
     from tornado.options import define, options
-    define("port", default=23010, help="run on the given port ", type=int)
+    define("port", default=23016, help="run on the given port ", type=int)
     define("log_path", default='/tmp', help="log path ", type=str)
     tornado.options.parse_command_line()
     app = apps()
     http_server = tornado.httpserver.HTTPServer(app)
     http_server.bind(options.port)
-    http_server.start(num_processes=0)
+    http_server.start()
     tornado.ioloop.IOLoop.instance().start()