class LogicalFluorescentOrangeDinosaur(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2019, 1, 7)
        self.SetEndDate(2019, 4, 1)
        self.SetCash(100000)
        self.UniverseSettings.Resolution = Resolution.Daily
        self.AddUniverse(self.CoarseSelectionFunction) 
        self.indicators = { }
        
    def CoarseSelectionFunction(self, universe):  
            selected = []
            universe = sorted(universe, key=lambda c: c.DollarVolume, reverse=True)  
            universe = [c for c in universe if c.Price > 10][:100]
    
            for coarse in universe:  
                symbol = coarse.Symbol
                
                if symbol not in self.indicators:
                    # 1. Call history to get an array of 200 days of history data
                    history = self.History(symbol, 200, Resolution.Daily)
                    
                    #2. Adjust SelectionData to pass in the history result
                    self.indicators[symbol] = SelectionData(history) 
    
                self.indicators[symbol].update(self.Time, coarse.AdjustedPrice)
                
                if  self.indicators[symbol].is_ready() and \
                    self.indicators[symbol].bollinger.UpperBand.Current.Value < self.indicators[symbol].keltner.UpperBand.Current.Value and \
                    self.indicators[symbol].bollinger.LowerBand.Current.Value > self.indicators[symbol].keltner.LowerBand.Current.Value:
                    
                    selected.append(symbol)
            
            return selected[:10]
            
class SelectionData():
    #3. Update the constructor to accept a history array
    def __init__(self, history):
        self.bollinger = BollingerBands(20, 2, MovingAverageType.Simple)
        self.keltner = KeltnerChannels(20, 1.5, MovingAverageType.Simple)
        #4. Loop over the history data and update the indicatorsc
        for bar in history.itertuples():
            tradeBar = TradeBar(bar.Index[1], bar.Index[0], bar.open, bar.high, bar.low, bar.close, bar.volume, timedelta(1))
            self.bollinger.Update(bar.Index[1], bar.close)
            self.keltner.Update(tradeBar)
    
   # @property
    #def BollingerUpper(self):
     #   return float(self.bollinger.UpperBand.Current.Value)
        
    #@property
    #def BollingerLower(self):
     #   return float(self.bollinger.LowerBand.Current.Value)
        
    #@property
    #def KeltnerUpper(self):
     #   return float(self.keltner.UpperBand.Current.Value)
        
    #@property
    #def KeltnerLower(self):
    #    return float(self.keltner.LowerBand.Current.Value)
    
    
    def is_ready(self):
        return self.bollinger.IsReady and self.keltner.IsReady
    
    def update(self, time, value):
        return self.bollinger.Update(time, value)