# https://www.quantconnect.com/forum/discussion/2607/important-universe-selection-in-python-algorithms

from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Indicators")
AddReference("QuantConnect.Common")

from System import *
from QuantConnect import *
from QuantConnect.Data import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *
from System.Collections.Generic import List
import decimal as d

class EmaCrossUniverseSelectionAlgorithm(QCAlgorithm):
    def Initialize(self):
        self.SetCash(100000)         
        self.SetStartDate(2017,10,1) 
        self.SetEndDate(  2017,11,1) 
        self.UniverseSettings.Resolution = Resolution.Daily
        self.UniverseSettings.Leverage   = 2
        self.coarse_max = 10
        self.averages = {}
        self.AddUniverse(self.CoarseSelectionFunction)

    def CoarseSelectionFunction(self, coarse):
        for cf in coarse:
            if cf.Symbol not in self.averages:
                self.averages[cf.Symbol] = SymbolData(cf.Symbol)

            # Update the SymbolData object with current EOD price
            avg = self.averages[cf.Symbol]
            avg.update(cf)

            prc = 0.0
            if self.Securities.ContainsKey(cf.Symbol):
                prc  = self.Securities[cf.Symbol].Price 
                sma1 = self.averages[cf.Symbol].sma1.Current.Value
                sma2 = self.averages[cf.Symbol].sma2.Current.Value
                sma1 = sma1 if sma1 else 0.0
                sma2 = sma2 if sma2 else 0.0
                diff = sma1 - sma2
                self.Log('{}  prc {}  sma1 {}  sma2 {}   diff {} '.format(cf.Symbol, '%.2f' % prc, 
                    '%.3f' % sma1, '%.3f' % sma2, '%.5f' % diff))
        
        ''' TODO
        Find out why log is this limited ...
            2017-10-11 00:00:00 Z UYE69C59FN8L  prc 42.14  sma1 41.987  sma2 41.752   diff 0.23467 
            2017-10-11 00:00:00 Z UYE69C59FN8L  prc 42.14  sma1 41.810  sma2 41.829   diff -0.01900 
            2017-10-12 00:00:00 Z UYE69C59FN8L  prc 41.87  sma1 41.633  sma2 41.783   diff -0.14967 
            2017-10-12 00:00:00 Z UYE69C59FN8L  prc 41.87  sma1 41.433  sma2 41.745   diff -0.31167 
            2017-10-13 00:00:00 Z UYE69C59FN8L  prc 41.42  sma1 41.463  sma2 41.747   diff -0.28367 
            2017-10-13 00:00:00 Z UYE69C59FN8L  prc 41.42  sma1 41.467  sma2 41.741   diff -0.27433 
            2017-10-14 00:00:00 Z UYE69C59FN8L  prc 41.70  sma1 41.550  sma2 41.680   diff -0.13000 
            2017-10-14 00:00:00 Z UYE69C59FN8L  prc 41.70  sma1 41.460  sma2 41.634   diff -0.17400 
            2017-10-17 00:00:00 Z UYE69C59FN8L  prc 41.52  sma1 41.363  sma2 41.534   diff -0.17067 
            2017-10-17 00:00:00 Z UYE69C59FN8L  prc 41.52  sma1 41.213  sma2 41.446   diff -0.23267 
            2017-10-17 00:00:00 Z UYE69C59FN8L  prc 41.14  sma1 41.283  sma2 41.423   diff -0.13967 
            2017-10-17 00:00:00 Z UYE69C59FN8L  prc 41.14  sma1 41.407  sma2 41.413   diff -0.00633        
        Place diff's in a sortable object
        Sort them
        Select top or bottom coarse_max
        ''' 
            
        # Filter the values of the dict: wait for indicator to be ready
        vals = filter(lambda x: x.is_ready, self.averages.values())

        # need to return only the symbol objects
        return [ x.symbol for x in vals ]
        
        # Error: 'filter' object is not subscriptable
        return [ x.symbol for x in vals[:self.coarse_max] ]

    # this event fires whenever have changes to universe
    def OnSecuritiesChanged(self, changes):
        # want n% allocation in each security in universe
        for security in changes.AddedSecurities:
            self.SetHoldings(security.Symbol, 0.1)

        return
        # liquidate removed securities
        for security in changes.RemovedSecurities:
            if security.Invested:
                self.Liquidate(security.Symbol)

class SymbolData(object):
    def __init__(self, symbol):
        self.symbol = symbol
        self.sma1 = SimpleMovingAverage(3)
        self.sma2 = SimpleMovingAverage(10)
        self.is_ready = False

    def update(self, value):
        self.is_ready = self.sma1.Update(value.EndTime, value.Price) and self.sma2.Update(value.EndTime, value.Price)