modify code name

README.md

@@ -54,5 +54,5 @@ python ./client/all_factor_cal.py --end_date 20190101  --count 3 --update True
 初始化分布式计算redis，运行之前需要在文件中设定需要指定的redis信息。
 
 ### sumbit
-分布式计算任务提交入口，执行之后，客户端会将指定目录即目录下所有文件分发到所有计算节点中。
+分布式计算任务提交入口，执行之后，客户端会将指定目录即目录下所有文件分发到所有计算节点中。不同的客户端在提交任务时需要修改其中的相关配置。
 

client/earning.py

@@ -135,7 +135,7 @@ def get_basic_earning(trade_date):
 
 
 def prepare_calculate(trade_date):
-    # cash flow
+    # earning
     tp_earning, ttm_earning_5y, ttm_earning = get_basic_earning(trade_date)
     if len(tp_earning) <= 0 or len(ttm_earning_5y) <= 0 or len(ttm_earning) <= 0:
         print("%s has no data" % trade_date)

client/factor_volatility_value.py

@@ -121,7 +121,7 @@ class FactorVolatilityValue(FactorBase):
         temp_price_sets = index_daily_price_sets[index_daily_price_sets.trade_date <= trade_date]
         return sk_daily_price_sets, temp_price_sets[:count]
 
-    def prepaer_calculate(self, trade_date):
+    def prepare_calculate(self, trade_date):
         self.trade_date = trade_date
 
         tp_price_return, temp_price_sets = self.get_basic_data(trade_date)
@@ -159,7 +159,7 @@ class FactorVolatilityValue(FactorBase):
         trade_date_sets = self._trade_date.trade_date_sets_ago(start_date, end_date, count)
         for trade_date in trade_date_sets:
             print('因子计算日期： %s' % trade_date)
-            self.prepaer_calculate(trade_date)
+            self.prepare_calculate(trade_date)
         print('----->')
 
 

client/growth.py

@@ -188,7 +188,7 @@ def get_basic_growth_data(trade_date):
 
 
 def prepare_calculate(trade_date):
-    # cash flow
+    # growth
     ttm_factor_sets, balance_sets = get_basic_growth_data(trade_date)
     growth_sets = pd.merge(ttm_factor_sets, balance_sets, on='symbol')
     if len(growth_sets) <= 0:

client/historical_value.py

@@ -142,7 +142,7 @@ def get_basic_history_value_data(trade_date):
 
 
 def prepare_calculate(trade_date):
-    # history_value
+    # historical_value
     valuation_sets, ttm_factor_sets, cash_flow_sets, income_sets = get_basic_history_value_data(trade_date)
     valuation_sets = pd.merge(valuation_sets, income_sets, on='symbol')
     valuation_sets = pd.merge(valuation_sets, ttm_factor_sets, on='symbol')

client/per_share_indicator.py

@@ -121,7 +121,7 @@ def prepare_calculate(trade_date):
     valuation_sets = pd.merge(valuation_sets, ttm_factor_sets, on='symbol')
     valuation_sets = pd.merge(valuation_sets, cash_flow_sets, on='symbol')
     valuation_sets = pd.merge(valuation_sets, balance_sets, on='symbol')
-    if len(valuation_sets) <= 0 :
+    if len(valuation_sets) <= 0:
         print("%s has no data" % trade_date)
         return
     else: