class WellDressedSkyBlueSardine(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2019, 1, 1)
        self.SetEndDate(2019, 3, 1)
        self.SetCash(100000)
        self.rebalanceTime = datetime.min
        self.activeStocks = set()
        self.AddUniverse(self.CoarseFilter)
        self.UniverseSettings.Resolution = Resolution.Daily
        self.universe = set()
        self.portfolioTargets = []
        self.indicators = {}
        self.EMA_Period_Fast = 20
        self.EMA_Period_Slow = 50
        #self.closeWindows = {}
        
    def CoarseFilter(self, coarse):
        # Rebalancing time
        if self.Time <= self.rebalanceTime:
            return self.Universe.Unchanged
        self.rebalanceTime = self.Time + timedelta(1) 
        
        sortedByDollarVolume = sorted(coarse, key=lambda x: x.DollarVolume, reverse=True)
        self.universe = [x.Symbol for x in sortedByDollarVolume if x.Price > 10 and x.HasFundamentalData][:10]
        return self.universe

    def OnSecuritiesChanged(self, changes):
        # close positions in removed securities
        for x in changes.RemovedSecurities:
            self.Liquidate(x.Symbol)  

        for security in changes.AddedSecurities:
            self.indicators[security.Symbol] = SymbolData(security.Symbol, self, self.EMA_Period_Fast, self.EMA_Period_Slow)

    def OnData(self, data):
        for symbol in self.universe:
            if not data.ContainsKey(symbol):
                continue
            if data[symbol] is None:           
                continue
            if not symbol in self.indicators: 
                continue
            if symbol in data.Bars:
                self.indicators[symbol].close_window.Add(data.Bars[symbol].Close)
            #-------------------------------------------------------
            if not (self.indicators[symbol].fast_ema_window.IsReady and self.indicators[symbol].slow_ema_window.IsReady): 
                continue    #return
            
            if (not self.Portfolio[symbol].Invested):# and (self.Portfolio.MarginRemaining > 0.9*self.percentagebuy*self.Portfolio.TotalPortfolioValue):
                if (self.indicators[symbol].fast_ema_window[1] >= self.indicators[symbol].slow_ema_window[2]):
                    self.SetHoldings(symbol, 0.2)
                    self.Debug("buying " + str(symbol.Value) + " for " + str(data[symbol].Price))
                    
                    #self.Debug("Close Window is: " + str(self.indicators[symbol].closeWindow[0]))


            if self.indicators[symbol].fast_ema_window[1] <= self.indicators[symbol].slow_ema_window[1] and (self.indicators[symbol].fast_ema_window[4] > self.indicators[symbol].slow_ema_window[4]):
                invested = [ x.Symbol.Value for x in self.Portfolio.Values if x.Invested ]
                self.Debug("invested: " + str(invested))
                self.Liquidate(symbol)
            

#-------------------------------------------------------      
class SymbolData(object):
    
    rolling_window_length = 5
    
    def __init__(self, symbol, context, fast_ema_period, slow_ema_period):
        
        self.symbol = symbol
        self.fast_ema_period = fast_ema_period
        self.slow_ema_period = slow_ema_period
        self.fast_ema = context.EMA(symbol, self.fast_ema_period, Resolution.Daily)    
        self.slow_ema = context.EMA(symbol, self.slow_ema_period, Resolution.Daily)  
        self.fast_ema_window = RollingWindow[float](self.rolling_window_length)
        self.slow_ema_window = RollingWindow[float](self.rolling_window_length)
        #self.daily_rw = RollingWindow[TradeBar](4)
        self.closeWindow = RollingWindow[float](4)
        #self.closeWindow = RollingWindow[float](4)
        self.close_window = RollingWindow[float](4)
        #self.closeWindows[symbol] = RollingWindow[float](4)
        
        # Warm up EMA indicators
        history = context.History([symbol], slow_ema_period + self.rolling_window_length, Resolution.Daily)
        for time, row in history.loc[symbol].iterrows():
            self.fast_ema.Update(time, row["close"])
            self.slow_ema.Update(time, row["close"])

            self.close_window.Add(row["close"])
            
            # Warm up rolling windows
            if self.fast_ema.IsReady:
                self.fast_ema_window.Add(self.fast_ema.Current.Value)
            if self.slow_ema.IsReady:
                self.slow_ema_window.Add(self.slow_ema.Current.Value)

           # if self.closeWindow.IsReady:
           #     self.closeWindow.Add(time, row["close"])
    
    #def CloseUpdated(self, sender, bar):
        '''Event holder to update the close Rolling Window values'''
      #  self.closeWindow.Add(bar.Close)
    
    
    def get_fast_EMA(self):
        return self.fast_ema.Current.Value
        
    def get_slow_EMA(self):
        return self.slow_ema.Current.Value