from System import *
from QuantConnect import *
from QuantConnect.Data.Consolidators import *
from QuantConnect.Data.Market import *
from QuantConnect.Orders import OrderStatus
from QuantConnect.Algorithm import QCAlgorithm
from QuantConnect.Indicators import *
import numpy as np
from datetime import timedelta, datetime
import decimal as d

class MultipleSymbolConsolidationAlgorithm(QCAlgorithm):

    def Initialize(self):
        
        BarPeriod = TimeSpan.FromMinutes(1)
        RollingWindowSize = 14
 
        SimpleMovingAveragePeriodfast = 14            ##USD CAD AUD GBP EUR CHF NZD

        self.Data = {}                              
        ForexSymbols =["EURUSD"]#, "EURCHF", "EURAUD", "EURGBP", "EURCAD", "EURNZD", "USDCHF", "USDCAD", "GBPCAD", "GBPAUD", "GBPCHF", "GBPUSD", "GBPNZD", "AUDCAD", "CADCHF", "NZDCAD", "AUDUSD", "AUDCHF", "AUDNZD", "NZDCHF", "NZDUSD"]
        self.SetStartDate(2018, 2, 5)
        self.SetEndDate(2018, 2, 10)
        self.SetCash(10000)                                                                                                          #Initialize
        self.SetWarmUp(14)
        self.SetTimeZone("Europe/Rome")
        
        StochasticPeriod = 14
        BollingerPeriod = 20
        KPeriod = 3
        DPeriod = 3
############################################################################################################################################################ 
        
        for symbol in ForexSymbols:
            
            forex = self.AddForex(symbol)
            self.Data[symbol] = SymbolData(forex.Symbol, BarPeriod, RollingWindowSize)
            self.Securities[symbol].SetLeverage(50)

        for symbol, symbolData in self.Data.items():
            
            symbolData.SMAfast = SimpleMovingAverage(self.CreateIndicatorName(symbol, "SMA" + str(SimpleMovingAveragePeriodfast), Resolution.Minute), SimpleMovingAveragePeriodfast)
            symbolData.STO = Stochastic(self.CreateIndicatorName(symbol, "STO" + str(StochasticPeriod), Resolution.Minute), StochasticPeriod, KPeriod, DPeriod)
            symbolData.BB = BollingerBand(self.CreateIndicatorName(symbol, "BB" + str(BollingerPeriod), Resolution.Hour), BollingerPeriod)
            
            consolidator = QuoteBarConsolidator(BarPeriod)
            consolidator.DataConsolidated += self.OnDataConsolidated
            self.SubscriptionManager.AddConsolidator(symbolData.Symbol, consolidator)
            
##########################################################################################################################################   
    
    def OnDataConsolidated(self, sender, bar):                              #ConsolidateData
        
        self.Data[bar.Symbol.Value].SMAfast.Update(bar.Time, bar.Close)
        self.Data[bar.Symbol.Value].STO.Update(bar)
        self.Data[bar.Symbol.Value].BB.Update(bar.Time, bar.Close)
        self.Data[bar.Symbol.Value].Bars.Add(bar)
   
#########################################################################################################################################        
        
    def OnData(self, data):     
        
        for symbol in self.Data.keys():
            symbolData = self.Data[symbol]
        
            if symbolData.IsReady() and symbolData.WasJustUpdated(self.Time):
             
                symbolData.smaWin.Add(symbolData.SMAfast.Current.Value)
                symbolData.Pricewin.Add(self.Securities[symbol].Price)

               
                if symbolData.Pricewin.Count == 5:
                    
 ###################################################################################################################################
                    
                    PipLoss = 10
                    Equity = self.Portfolio.TotalPortfolioValue*50                    
                    pips = self.Securities[symbol].SymbolProperties.MinimumPriceVariation * 10
                    ConversionRate = self.Portfolio.Securities[symbol].QuoteCurrency.ConversionRate
                    LotSize = ((Equity)/(PipLoss*ConversionRate)) ################### 1 = .01*100 = .01*100000/1000. If risk/trade is changed from 1% change that in Lot size equation
                    NowPrice = self.Securities[symbol].Price
                    

########################################################################################################################################

                    sma_list = [i for i in symbolData.smaWin]
                    
                    SMA = symbolData.SMAfast.Current.Value
                    STO =symbolData.STO.Current.Value
                    
                    
                    hour = self.Time.hour
                    minute = self.Time.minute
                    

                        
                            
                    self.Log("{0}, {1}, {2}, {3}".format(str(hour), str(minute), str(STO), str(NowPrice)))
                    
                    SMA = symbolData.SMAfast.Current.Value
                    
                    smaslope = (sma_list[0] - sma_list[1])

                    
 
                    
###############################################################################################################################
class SymbolData(object):
    
    def __init__(self, symbol, barPeriod, windowSize):
      
        self.Symbol = symbol
        self.BarPeriod = barPeriod
        self.Bars = RollingWindow[IBaseDataBar](windowSize)
        self.SMAfast = None
        self.STO = None
        self.BB = None

        self.smaWin = RollingWindow[float](5)

        self.Pricewin = RollingWindow[float](5)



    def IsReady(self):
        return self.Bars.IsReady and self.SMAfast.IsReady 

    def WasJustUpdated(self, current):
        return self.Bars.Count > 0 and self.Bars[0].Time == current - self.BarPeriod