code update

client.py

@@ -540,7 +540,7 @@ if __name__ == '__main__':
         ttm_factor_sets, balance_sets = get_basic_growth_data(date_index)
         growth_sets = pd.merge(ttm_factor_sets, balance_sets, on='symbol')
         cache_data.set_cache(session1, date_index, growth_sets.to_json(orient='records'))
-        factor_growth.factor_calculate(date_index=date_index, session=session1)
+        factor_growth.factor_calculate.delay(date_index=date_index, session=session1)
         time1 = time.time()
         print('growth_cal_time:{}'.format(time1 - start_time))
 
@@ -550,7 +550,7 @@ if __name__ == '__main__':
         valuation_sets = pd.merge(valuation_sets, ttm_factor_sets, on='symbol')
         valuation_sets = pd.merge(valuation_sets, cash_flow_sets, on='symbol')
         cache_data.set_cache(session2, date_index, valuation_sets.to_json(orient='records'))
-        historical_value.factor_calculate(date_index=date_index, session=session2)
+        historical_value.factor_calculate.delay(date_index=date_index, session=session2)
         time2 = time.time()
         print('history_cal_time:{}'.format(time2 - time1))
 
@@ -561,32 +561,32 @@ if __name__ == '__main__':
         valuation_sets = pd.merge(valuation_sets, cash_flow_sets, on='symbol')
         valuation_sets = pd.merge(valuation_sets, balance_sets, on='symbol')
         cache_data.set_cache(session3, date_index, valuation_sets.to_json(orient='records'))
-        factor_per_share_indicators.factor_calculate(date_index=date_index, session=session3)
+        factor_per_share_indicators.factor_calculate.delay(date_index=date_index, session=session3)
         time3 = time.time()
         print('per_share_cal_time:{}'.format(time3 - time2))
 
         # cash flow
         tp_cash_flow, ttm_cash_flow_sets = get_basic_cash_flow(date_index)
-        cache_data.set_cache(session4 + "1", date_index, tp_cash_flow.to_json(orient='records'))
-        cache_data.set_cache(session4 + "2", date_index, ttm_cash_flow_sets.to_json(orient='records'))
-        factor_cash_flow.factor_calculate(date_index=date_index, session=session4)
+        cache_data.set_cache(session4 + date_index + "1", date_index, tp_cash_flow.to_json(orient='records'))
+        cache_data.set_cache(session4 + date_index + "2", date_index, ttm_cash_flow_sets.to_json(orient='records'))
+        factor_cash_flow.factor_calculate.delay(date_index=date_index, session=session4)
         time4 = time.time()
         print('cash_flow_cal_time:{}'.format(time4 - time3))
 
         # constrain
         balance_sets, ttm_factors_sets = get_basic_constrain(date_index)
-        cache_data.set_cache(session5 + '1', date_index, balance_sets.to_json(orient='records'))
-        cache_data.set_cache(session5 + '2', date_index, ttm_factors_sets.to_json(orient='records'))
-        factor_constrain.factor_calculate(date_index=date_index, session=session5)
+        cache_data.set_cache(session5 + date_index + '1', date_index, balance_sets.to_json(orient='records'))
+        cache_data.set_cache(session5 + date_index + '2', date_index, ttm_factors_sets.to_json(orient='records'))
+        factor_constrain.factor_calculate.delay(date_index=date_index, session=session5)
         time5 = time.time()
         print('constrain_cal_time:{}'.format(time5 - time4))
 
         # earning
         # tp_earning, ttm_earning_5y, ttm_earning = get_basic_earning(date_index)
-        # cache_data.set_cache(session6 + "1", date_index, tp_earning.to_json(orient='records'))
-        # cache_data.set_cache(session6 + "2", date_index, ttm_earning_5y.to_json(orient='records'))
-        # cache_data.set_cache(session6 + "3", date_index, ttm_earning.to_json(orient='records'))
-        # factor_earning.factor_calculate(date_index=date_index, session=session6)
+        # cache_data.set_cache(session6 + date_index + "1", date_index, tp_earning.to_json(orient='records'))
+        # cache_data.set_cache(session6 + date_index + "2", date_index, ttm_earning_5y.to_json(orient='records'))
+        # cache_data.set_cache(session6 + date_index + "3", date_index, ttm_earning.to_json(orient='records'))
+        # factor_earning.factor_calculate.delay(date_index=date_index, session=session6)
         # time6 = time.time()
         # print('earning_cal_time:{}'.format(time6 - time5))
         print('---------------------->')

factor/__init__.py

@@ -13,4 +13,5 @@ app = create_app('factor', ['factor.factor_growth',
                             'factor.historical_value',
                             'factor.factor_cash_flow',
                             'factor.factor_constrain',
-                            'factor.factor_earning'])
+                            'factor.factor_earning',
+                            'factor.factor_per_share_indicators'])

factor/factor_cash_flow.py

@@ -8,8 +8,7 @@ import numpy as np
 from pandas.io.json import json_normalize
 from factor.ttm_fundamental import *
 from factor.factor_base import FactorBase
-from vision.fm.signletion_engine import *
-from vision.utillities.calc_tools import CalcTools
+from factor.utillities.calc_tools import CalcTools
 from ultron.cluster.invoke.cache_data import cache_data
 
 
@@ -272,8 +271,8 @@ def factor_calculate(**kwargs):
     session = kwargs['session']
     cash_flow = FactorCashFlow('factor_cash_flow')  # 注意, 这里的name要与client中新建table时的name一致, 不然回报错
 
-    content1 = cache_data.get_cache(session + "1", date_index)
-    content2 = cache_data.get_cache(session + "2", date_index)
+    content1 = cache_data.get_cache(session + date_index + "1", date_index)
+    content2 = cache_data.get_cache(session + date_index + "2", date_index)
     tp_cash_flow = json_normalize(json.loads(str(content1, encoding='utf8')))
     ttm_factor_sets = json_normalize(json.loads(str(content2, encoding='utf8')))
     tp_cash_flow.set_index('symbol', inplace=True)

factor/factor_constrain.py

@@ -9,8 +9,7 @@ from pandas.io.json import json_normalize
 from factor import app
 from factor.factor_base import FactorBase
 from factor.ttm_fundamental import *
-from vision.fm.signletion_engine import *
-from vision.utillities.calc_tools import CalcTools
+from factor.utillities.calc_tools import CalcTools
 from ultron.cluster.invoke.cache_data import cache_data
 
 
@@ -190,8 +189,8 @@ def factor_calculate(**kwargs):
     date_index = kwargs['date_index']
     session = kwargs['session']
     constrain = FactorConstrain('factor_constrain')  # 注意, 这里的name要与client中新建table时的name一致, 不然回报错
-    content1 = cache_data.get_cache(session + '1', date_index)
-    content2 = cache_data.get_cache(session + '2', date_index)
+    content1 = cache_data.get_cache(session + date_index + '1', date_index)
+    content2 = cache_data.get_cache(session + date_index + '2', date_index)
     balance_sets = json_normalize(json.loads(str(content1, encoding='utf8')))
     ttm_factors_sets = json_normalize(json.loads(str(content2, encoding='utf8')))
     balance_sets.set_index('symbol', inplace=True)

factor/factor_earning.py

@@ -14,8 +14,7 @@ from factor import app
 import numpy as np
 from factor.ttm_fundamental import *
 from factor.factor_base import FactorBase
-from vision.fm.signletion_engine import *
-from vision.utillities.calc_tools import CalcTools
+from factor.utillities.calc_tools import CalcTools
 from pandas.io.json import json_normalize
 from ultron.cluster.invoke.cache_data import cache_data
 
@@ -600,9 +599,9 @@ def factor_calculate(**kwargs):
     date_index = kwargs['date_index']
     session = kwargs['session']
     earning = FactorEarning('factor_earning')  # 注意, 这里的name要与client中新建table时的name一致, 不然回报错
-    content1 = cache_data.get_cache(session + "1", date_index)
-    content2 = cache_data.get_cache(session + "2", date_index)
-    content3 = cache_data.get_cache(session + "3", date_index)
+    content1 = cache_data.get_cache(session + date_index + "1", date_index)
+    content2 = cache_data.get_cache(session + date_index + "2", date_index)
+    content3 = cache_data.get_cache(session + date_index + "3", date_index)
     tp_earning = json_normalize(json.loads(str(content1, encoding='utf8')))
     ttm_earning_5y = json_normalize(json.loads(str(content2, encoding='utf8')))
     ttm_earning = json_normalize(json.loads(str(content3, encoding='utf8')))

factor/factor_growth.py

@@ -14,7 +14,6 @@ from pandas.io.json import json_normalize
 from factor import app
 from factor.factor_base import FactorBase
 from factor.ttm_fundamental import *
-from vision.fm.signletion_engine import *
 from ultron.cluster.invoke.cache_data import cache_data
 
 

factor/factor_per_share_indicators.py

@@ -13,10 +13,10 @@ import sys
 sys.path.append("..")
 
 import json
+from factor import app
 from pandas.io.json import json_normalize
 from factor.ttm_fundamental import *
 from factor.factor_base import FactorBase
-from vision.fm.signletion_engine import *
 from ultron.cluster.invoke.cache_data import cache_data
 
 
@@ -526,7 +526,7 @@ def calculate(trade_date, valuation_sets, per_share):
     per_share._storage_data(factor_share_indicators, trade_date)
 
 
-# @app.task()
+@app.task()
 def factor_calculate(**kwargs):
     print("per_share_kwargs: {}".format(kwargs))
     date_index = kwargs['date_index']

factor/historical_value.py

@@ -17,7 +17,6 @@ from pandas.io.json import json_normalize
 from factor import app
 from factor.factor_base import FactorBase
 from factor.ttm_fundamental import *
-from vision.fm.signletion_engine import *
 from factor.utillities.calc_tools import CalcTools
 from ultron.cluster.invoke.cache_data import cache_data
 

init.py

 from ultron.config import config_setting
 
-config_setting.set_queue(qtype='redis', host='10.15.5.34', port=6379, pwd='', db=1)
+config_setting.set_queue(qtype='redis', host='10.15.5.164', port=6379, pwd='', db=1)
 config_setting.update()