class UpgradedFluorescentOrangeCaterpillar(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2022, 2, 16)  # Set Start Date
        self.SetEndDate(2022, 2, 17)
        self.SetCash(100000)  # Set Strategy Cash
       
        res = Resolution.Minute
        
        symbols = [ Symbol.Create("SPY", SecurityType.Equity, Market.USA) , Symbol.Create("TSLA", SecurityType.Equity, Market.USA) , Symbol.Create("HES", SecurityType.Equity, Market.USA) ]
        self.SetUniverseSelection( ManualUniverseSelectionModel(symbols) )
        
        self.tsla = self.AddEquity("TSLA",res, Market.USA, True, 0, False).Symbol
        self.spy = self.AddEquity("SPY", res, Market.USA, True, 0, False).Symbol
        self.hes = self.AddEquity("HES", res, Market.USA, True, 0, False).Symbol
        
        self.symbolDataBySymbol = {}
        
        for symbol in symbols:
            symbolData = self.symbolDataBySymbol.get(symbol)
            if symbolData is None: 
                symbolData = SymbolData(self, symbol, 5, 2)
                self.symbolDataBySymbol[symbol] = symbolData
            else:
                #    # a security that was already initialized was re-added, reset the indicators
                symbolData.RSI_MultiMin.Reset()



        
        

    def OnData(self, data):
        for symbol, symbolData in self.symbolDataBySymbol.items():
            if symbolData.WasJustUpdatedMins(self.Time):
                if self.Time.hour == 9 and self.Time.minute >= 30 and self.Time.minute <= 35:
                    if symbolData.Symbol == self.spy:
                        self.Log("Start time: "+ str(symbolData.MultiMinsBar.Time) + " EndTime: " + str(str(symbolData.MultiMinsBar.EndTime) +" Bar: "+ symbolData.MultiMinsBar.ToString()+ " data Time: " +str(data.Time) ))
                        minhistory = self.History(symbolData.Symbol, 5, Resolution.Minute).loc[symbolData.Symbol]
                        volumeSum = minhistory.volume.sum()
                        self.Log(minhistory)
                        self.Log(volumeSum)
            
 
            
            
    def OnSecuritiesChanged(self, changes):
        '''Event fired each time the we add/remove securities from the data feed
        Args:
            algorithm: The algorithm instance that experienced the change in securities
            changes: The security additions and removals from the algorithm'''

        
        
        
        
    
    def OnEndOfAlgorithm(self):
        for symbol, symbolData in self.symbolDataBySymbol.items():
            self.Debug( str(symbol) + "   " )

class SymbolData:
    '''Contains data specific to a symbol required by this model'''
    def __init__(self, selfabove, security, ConsidMin, lookbackdays):
        
        
        self.Symbol =  security
        self.ConsidMin = ConsidMin
        self.lookbackdays = lookbackdays

        self.df_min = pd.DataFrame()

        self.df_min = selfabove.History(self.Symbol, timedelta(days=self.lookbackdays), Resolution.Minute).loc[self.Symbol]
        #if self.Symbol == selfabove.spy:
        #    selfabove.Log(self.df_min.head(10))
    
        self.lengthofMinWin = self.df_min.index.size
        self.lengthofMultiMinWin= math.ceil(self.df_min.index.size/(self.ConsidMin))

        self.rolling_windowMin = RollingWindow[TradeBar](self.lengthofMultiMinWin)
        self.rolling_windowMultiMin = RollingWindow[TradeBar](self.lengthofMultiMinWin)

        self.MultiMinsBar = None
        
        self.RSI_MultiMin = RelativeStrengthIndex(14, MovingAverageType.Simple)

        self.Mins = timedelta(minutes= self.ConsidMin)

        self.tradeBarWindowMultiMinsBar = None 

        self.consolidatorMins = TradeBarConsolidator(self.Mins)
        self.consolidatorMins.DataConsolidated += self.consolidation_handler_Mins
        selfabove.SubscriptionManager.AddConsolidator(self.Symbol, self.consolidatorMins)

        selfabove.RegisterIndicator(self.Symbol, self.RSI_MultiMin, self.consolidatorMins, Field.Close)
        
        
        for time, row in self.df_min.iterrows():
            tradebarbar = TradeBar(time-timedelta(minutes= 1), self.Symbol, row.open, row.high, row.low, row.close, row.volume )
            self.rolling_windowMin.Add(tradebarbar)
            self.consolidatorMins.Update(tradebarbar)
            if time.hour == 9 and (time.minute- 1) >= 30 and (time.minute- 1) <= 36 and self.Symbol == selfabove.spy:
                selfabove.Log((str( "1 min bar:  " + tradebarbar.ToString())+ " start of bar: "+str(tradebarbar.Time)+" EndTime of bar: " +str(tradebarbar.EndTime)))
                if (time.minute - 1) == 35: 
                    selfabove.Log((str(self.MultiMinsBar.EndTime - self.MultiMinsBar.Time) + " 5 min bar: " + self.MultiMinsBar.ToString())+" Endtime of Bar: " +str(self.MultiMinsBar.EndTime) )

        self.df_MultiMin = selfabove.PandasConverter.GetDataFrame[TradeBar](self.rolling_windowMultiMin)
        self.df_MultiMin = self.df_MultiMin.reset_index(level='symbol')
        self.df_MultiMin = self.df_MultiMin.drop(['symbol'], axis=1)
        self.df_MultiMin = self.df_MultiMin.sort_index()
        
 
    def consolidation_handler_Mins(self, sender, bar):
        self.rolling_windowMultiMin.Add(bar)
        self.MultiMinsBar = bar
        #self.Log(str(bar.EndTime - bar.Time) + " " + bar.ToString())


    def WasJustUpdatedMins(self, current):
        return self.MultiMinsBar is not None and self.MultiMinsBar.Time == current - self.Mins