[Del] remove trailing white space

[Del] remove spaces in blank lines

.flake8

@@ -3,5 +3,3 @@ exclude = venv,build,__pycache__,__init__.py,ib,talib,uic
 ignore =
     E501 line too long, fixed by black
     W503 line break before binary operator
-    W293 blank line contains whitespace
-    W291 trailing whitespace

examples/simple_rpc/test_client.py

@@ -7,7 +7,7 @@
 
 class TestClient(RpcClient):
     """
-    Test RpcClient   
+    Test RpcClient
     """
 
     def __init__(self):

vnpy/api/rest/rest_client.py

@@ -147,7 +147,7 @@ def add_request(
         """
         Add a new request.
         :param method: GET, POST, PUT, DELETE, QUERY
-        :param path: 
+        :param path:
         :param callback: callback function if 2xx status, type: (dict, Request)
         :param params: dict for query string
         :param data: Http body. If it is a dict, it will be converted to form-data. Otherwise, it will be converted to bytes.
@@ -296,7 +296,7 @@ def request(
         """
         Add a new request.
         :param method: GET, POST, PUT, DELETE, QUERY
-        :param path: 
+        :param path:
         :param params: dict for query string
         :param data: dict for body
         :param headers: dict for headers

vnpy/app/algo_trading/algos/dma_algo.py

@@ -14,7 +14,7 @@ class DmaAlgo(AlgoTemplate):
         "vt_symbol": "",
         "direction": [Direction.LONG.value, Direction.SHORT.value],
         "order_type": [
-            OrderType.MARKET.value, 
+            OrderType.MARKET.value,
             OrderType.LIMIT.value,
             OrderType.STOP.value,
             OrderType.FAK.value,
@@ -74,7 +74,7 @@ def on_tick(self, tick: TickData):
                     self.order_type,
                     self.offset
                 )
-                
+
             else:
                 self.vt_orderid = self.sell(
                     self.vt_symbol,
@@ -96,4 +96,4 @@ def on_order(self, order: OrderData):
 
     def on_trade(self, trade: TradeData):
         """"""
-        pass   
+        pass

vnpy/app/cta_backtester/ui/widget.py

@@ -1013,13 +1013,13 @@ def update_history(self, history: list):
     def update_trades(self, trades: list):
         """"""
         trade_data = []
-        
+
         for trade in trades:
             ix = self.dt_ix_map[trade.datetime]
 
             scatter = {
-                "pos": (ix, trade.price), 
-                "data": 1, 
+                "pos": (ix, trade.price),
+                "data": 1,
                 "size": 14,
                 "pen": pg.mkPen((255, 255, 255))
             }
@@ -1030,19 +1030,19 @@ def update_trades(self, trades: list):
             else:
                 scatter["symbol"] = "t"
                 scatter["brush"] = pg.mkBrush((0, 0, 255))
-            
+
             trade_data.append(scatter)
 
         self.trade_scatter.setData(trade_data)
-        
+
     def clear_data(self):
         """"""
         self.updated = False
         self.chart.clear_all()
 
         self.dt_ix_map.clear()
         self.trade_scatter.clear()
-    
+
     def is_updated(self):
         """"""
         return self.updated

vnpy/app/cta_strategy/backtesting.py

@@ -13,7 +13,7 @@
 from pandas import DataFrame
 from deap import creator, base, tools, algorithms
 
-from vnpy.trader.constant import (Direction, Offset, Exchange, 
+from vnpy.trader.constant import (Direction, Offset, Exchange,
                                   Interval, Status)
 from vnpy.trader.database import database_manager
 from vnpy.trader.object import OrderData, TradeData, BarData, TickData
@@ -84,12 +84,12 @@ def generate_setting(self):
             settings.append(setting)
 
         return settings
-    
+
     def generate_setting_ga(self):
-        """""" 
+        """"""
         settings_ga = []
-        settings = self.generate_setting()     
-        for d in settings:            
+        settings = self.generate_setting()
+        for d in settings:
             param = [tuple(i) for i in d.items()]
             settings_ga.append(param)
         return settings_ga
@@ -215,8 +215,8 @@ def load_data(self):
             self.end = datetime.now()
 
         if self.start >= self.end:
-            self.output("起始日期必须小于结束日期")    
-            return        
+            self.output("起始日期必须小于结束日期")
+            return
 
         self.history_data.clear()       # Clear previously loaded history data
 
@@ -230,7 +230,7 @@ def load_data(self):
 
         while start < self.end:
             end = min(end, self.end)  # Make sure end time stays within set range
-            
+
             if self.mode == BacktestingMode.BAR:
                 data = load_bar_data(
                     self.symbol,
@@ -248,15 +248,15 @@ def load_data(self):
                 )
 
             self.history_data.extend(data)
-            
+
             progress += progress_delta / total_delta
             progress = min(progress, 1)
             progress_bar = "#" * int(progress * 10)
             self.output(f"加载进度：{progress_bar} [{progress:.0%}]")
-            
+
             start = end
             end += progress_delta
-        
+
         self.output(f"历史数据加载完成，数据量：{len(self.history_data)}")
 
     def run_backtesting(self):
@@ -271,7 +271,7 @@ def run_backtesting(self):
         # Use the first [days] of history data for initializing strategy
         day_count = 0
         ix = 0
-        
+
         for ix, data in enumerate(self.history_data):
             if self.datetime and data.datetime.day != self.datetime.day:
                 day_count += 1
@@ -339,8 +339,8 @@ def calculate_statistics(self, df: DataFrame = None, output=True):
         # Check DataFrame input exterior
         if df is None:
             df = self.daily_df
-        
-        # Check for init DataFrame 
+
+        # Check for init DataFrame
         if df is None:
             # Set all statistics to 0 if no trade.
             start_date = ""
@@ -484,11 +484,11 @@ def calculate_statistics(self, df: DataFrame = None, output=True):
 
     def show_chart(self, df: DataFrame = None):
         """"""
-        # Check DataFrame input exterior        
+        # Check DataFrame input exterior
         if df is None:
             df = self.daily_df
 
-        # Check for init DataFrame        
+        # Check for init DataFrame
         if df is None:
             return
 
@@ -580,7 +580,7 @@ def run_ga_optimization(self, optimization_setting: OptimizationSetting, populat
         def generate_parameter():
             """"""
             return random.choice(settings)
-        
+
         def mutate_individual(individual, indpb):
             """"""
             size = len(individual)
@@ -620,24 +620,24 @@ def mutate_individual(individual, indpb):
         ga_mode = self.mode
 
         # Set up genetic algorithem
-        toolbox = base.Toolbox() 
-        toolbox.register("individual", tools.initIterate, creator.Individual, generate_parameter)                          
-        toolbox.register("population", tools.initRepeat, list, toolbox.individual)                                            
-        toolbox.register("mate", tools.cxTwoPoint)                                               
-        toolbox.register("mutate", mutate_individual, indpb=1)               
-        toolbox.register("evaluate", ga_optimize)                                                
-        toolbox.register("select", tools.selNSGA2)       
+        toolbox = base.Toolbox()
+        toolbox.register("individual", tools.initIterate, creator.Individual, generate_parameter)
+        toolbox.register("population", tools.initRepeat, list, toolbox.individual)
+        toolbox.register("mate", tools.cxTwoPoint)
+        toolbox.register("mutate", mutate_individual, indpb=1)
+        toolbox.register("evaluate", ga_optimize)
+        toolbox.register("select", tools.selNSGA2)
 
         total_size = len(settings)
         pop_size = population_size                      # number of individuals in each generation
         lambda_ = pop_size                              # number of children to produce at each generation
         mu = int(pop_size * 0.8)                        # number of individuals to select for the next generation
 
-        cxpb = 0.95         # probability that an offspring is produced by crossover    
+        cxpb = 0.95         # probability that an offspring is produced by crossover
         mutpb = 1 - cxpb    # probability that an offspring is produced by mutation
         ngen = ngen_size    # number of generation
-                
-        pop = toolbox.population(pop_size)      
+
+        pop = toolbox.population(pop_size)
         hof = tools.ParetoFront()               # end result of pareto front
 
         stats = tools.Statistics(lambda ind: ind.fitness.values)
@@ -662,30 +662,30 @@ def mutate_individual(individual, indpb):
         start = time()
 
         algorithms.eaMuPlusLambda(
-            pop, 
-            toolbox, 
-            mu, 
-            lambda_, 
-            cxpb, 
-            mutpb, 
-            ngen, 
+            pop,
+            toolbox,
+            mu,
+            lambda_,
+            cxpb,
+            mutpb,
+            ngen,
             stats,
             halloffame=hof
-        )    
-        
+        )
+
         end = time()
         cost = int((end - start))
 
         self.output(f"遗传算法优化完成，耗时{cost}秒")
-        
+
         # Return result list
         results = []
 
         for parameter_values in hof:
             setting = dict(parameter_values)
             target_value = ga_optimize(parameter_values)[0]
             results.append((setting, target_value, {}))
-        
+
         return results
 
     def update_daily_close(self, price: float):
@@ -743,14 +743,14 @@ def cross_limit_order(self):
 
             # Check whether limit orders can be filled.
             long_cross = (
-                order.direction == Direction.LONG 
-                and order.price >= long_cross_price 
+                order.direction == Direction.LONG
+                and order.price >= long_cross_price
                 and long_cross_price > 0
             )
 
             short_cross = (
-                order.direction == Direction.SHORT 
-                and order.price <= short_cross_price 
+                order.direction == Direction.SHORT
+                and order.price <= short_cross_price
                 and short_cross_price > 0
             )
 
@@ -811,12 +811,12 @@ def cross_stop_order(self):
         for stop_order in list(self.active_stop_orders.values()):
             # Check whether stop order can be triggered.
             long_cross = (
-                stop_order.direction == Direction.LONG 
+                stop_order.direction == Direction.LONG
                 and stop_order.price <= long_cross_price
             )
 
             short_cross = (
-                stop_order.direction == Direction.SHORT 
+                stop_order.direction == Direction.SHORT
                 and stop_order.price >= short_cross_price
             )
 
@@ -911,10 +911,10 @@ def send_order(
         return [vt_orderid]
 
     def send_stop_order(
-        self, 
-        direction: Direction, 
-        offset: Offset, 
-        price: float, 
+        self,
+        direction: Direction,
+        offset: Offset,
+        price: float,
         volume: float
     ):
         """"""
@@ -936,15 +936,15 @@ def send_stop_order(
         return stop_order.stop_orderid
 
     def send_limit_order(
-        self, 
+        self,
         direction: Direction,
         offset: Offset,
-        price: float, 
+        price: float,
         volume: float
     ):
         """"""
         self.limit_order_count += 1
-        
+
         order = OrderData(
             symbol=self.symbol,
             exchange=self.exchange,
@@ -1008,13 +1008,13 @@ def write_log(self, msg: str, strategy: CtaTemplate = None):
         """
         msg = f"{self.datetime}\t{msg}"
         self.logs.append(msg)
-    
+
     def send_email(self, msg: str, strategy: CtaTemplate = None):
         """
         Send email to default receiver.
         """
         pass
-    
+
     def sync_strategy_data(self, strategy: CtaTemplate):
         """
         Sync strategy data into json file.
@@ -1145,7 +1145,7 @@ def optimize(
     Function for running in multiprocessing.pool
     """
     engine = BacktestingEngine()
-    
+
     engine.set_parameters(
         vt_symbol=vt_symbol,
         interval=interval,