from datetime import timedelta


class BasicTemplateFrameworkAlgorithm(QCAlgorithmFramework):

    def Initialize(self):

        # Set requested data resolution
        self.UniverseSettings.Resolution = Resolution.Minute

        self.SetStartDate(2018, 8, 28)   #Set Start Date
        self.SetEndDate(2019, 2, 28)    #Set End Date
        self.SetCash(100000)           #Set Strategy Cash

        self.SetUniverseSelection(CoarseFundamentalUniverseSelectionModel(self.CoarseSelectionFunction))
        
        self.SetAlpha(CustomAlphaModel())
        
        self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
        
        self.SetExecution(ImmediateExecutionModel())
        
        self.SetRiskManagement(NullRiskManagementModel())
        

    # sort the data by daily dollar volume and take the top '5'
    def CoarseSelectionFunction(self, coarse):
        # sort descending by daily dollar volume
        sortedByDollarVolume = sorted(coarse, key=lambda x: x.DollarVolume, reverse=True)
        
        # return the symbol objects of the top entries from our sorted collection
        return [ x.Symbol for x in sortedByDollarVolume[:5] ]


class CustomAlphaModel:
    ''' This is where you might design a custom Alpha Model that
        will interact with the SymbolData class you create below'''
        
    def __init__(self):
        self.symbolDataBySymbol = {}
        
    def Update(self, algorithm, data):
        insights = []

        ## this is where you can evaluate technical indicators, etc. to generate insights

        return insights
        
    def OnSecuritiesChanged(self, algorithm, changes):
        symbols = [ x.Symbol for x in changes.AddedSecurities ]
        
        for symbol in symbols:
        ## Create SymbolData objects for any new assets
            symbolData = SymbolData(algorithm, symbol)
        ## Assign object to a dictionary so you can access it later in the Update() method
            self.symbolDataBySymbol[symbol] = symbolData


class SymbolData:
    
    def __init__(self, algorithm, symbol):
        self.Symbol = symbol
        self.five_consolidator = TradeBarConsolidator(timedelta(days = 5))    ## 5-period TradeBar Consolidator
        self.five_consolidator.DataConsolidated += self.FiveMinuteConsolidator  ## Add fuction to do what you want every 5-minutes with your data
        
        self.fifteen_consolidator = TradeBarConsolidator(timedelta(days = 15))    ## 5-period TradeBar Consolidator
        self.fifteen_consolidator.DataConsolidated += self.FifteenMinuteConsolidator  ## Add fuction to do what you want every 5-minutes with your data
        
        algorithm.SubscriptionManager.AddConsolidator(symbol, self.five_consolidator)  ## Register consolidator
        algorithm.SubscriptionManager.AddConsolidator(symbol, self.fifteen_consolidator)  ## Register consolidator
        
    def FiveMinuteConsolidator(self, sender, bar):
        #algorithm.Log('New 5 minute Bar for ' + str(self.Symbol) + '!')
        pass
        
    def FifteenMinuteConsolidator(self, sender, bar):
        #algorithm.Log('New 15 minute Bar for ' + str(self.Symbol) + '!')
        pass