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

from QuantConnect import *
from QuantConnect.Parameters import *
from QuantConnect.Benchmarks import *
from QuantConnect.Brokerages import *
from QuantConnect.Util import *
from QuantConnect.Interfaces import *
from QuantConnect.Algorithm import *
from QuantConnect.Algorithm.Framework import *
from QuantConnect.Algorithm.Framework.Selection import *
from QuantConnect.Algorithm.Framework.Alphas import *
from QuantConnect.Algorithm.Framework.Portfolio import *
from QuantConnect.Algorithm.Framework.Execution import *
from QuantConnect.Algorithm.Framework.Risk import *
from QuantConnect.Indicators import *
from QuantConnect.Data import *
from QuantConnect.Data.Consolidators import *
from QuantConnect.Data.Custom import *
from QuantConnect.Data.Fundamental import *
from QuantConnect.Data.Market import *
from QuantConnect.Data.UniverseSelection import *
from QuantConnect.Notifications import *
from QuantConnect.Orders import *
from QuantConnect.Orders.Fees import *
from QuantConnect.Orders.Fills import *
from QuantConnect.Orders.Slippage import *
from QuantConnect.Scheduling import *
from QuantConnect.Securities import *
from QuantConnect.Securities.Equity import *
from QuantConnect.Securities.Forex import *
from QuantConnect.Securities.Interfaces import *
from datetime import date, datetime, timedelta
from QuantConnect.Python import *
from QuantConnect.Storage import *

QCAlgorithmFramework = QCAlgorithm
QCAlgorithmFrameworkBridge = QCAlgorithm


class SimpleTimeBasedAlgorithm(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2019, 12, 1)
        self.SetEndDate(2020, 12, 1)
        self.SetCash(1000000)  # Set Strategy Cash
        self.lastEntryDate = self.Time.date()
        self.lastEntryCheckDate = self.Time.date()
        self.totalTrades = 0
        self.stopOrder = None
        self.bestPrice = 0
        self.direction = 0
        self.amzn = self.AddEquity("MSFT", Resolution.Daily)
        self.amzn.SetDataNormalizationMode(DataNormalizationMode.Raw)
        self.fast = self.EMA(self.amzn.Symbol, 15, Resolution.Daily)
        self.slow = self.EMA(self.amzn.Symbol, 30, Resolution.Daily)
        self.macd = self.MACD(self.amzn.Symbol, 15, 30, 9, MovingAverageType.Exponential, Resolution.Daily)
        emas = Chart("EMAs")
        emas.AddSeries(Series("Fast", SeriesType.Line, 0))
        emas.AddSeries(Series("Slow", SeriesType.Line, 0))
        emas.AddSeries(Series("Price", SeriesType.Candle, 0))
        emas.AddSeries(Series("MACD", SeriesType.Line, 0, "int"))
        emas.AddSeries(Series("Trade", SeriesType.Scatter, 0))
        self.AddChart(emas)

    def OnData(self, data):

        self.Plot("EMAs", "Fast", self.fast.Current.Value)
        self.Plot("EMAs", "Slow", self.slow.Current.Value)
        self.Plot("EMAs", "MACD", self.macd.Current.Value-self.macd.Signal.Current.Value+150)
        self.Plot("EMAs", "Price", self.amzn.Price)


        if not self.slow.IsReady:
            return

        if self.stopOrder: 
            yes=True
        
        # enter a position if SMA and LMA diverge
        # exit a position based on trailing stop loss
        if not self.Portfolio.Invested:
            # We're not invested, so check if we should enter, and if so what direction
            self.direction = 0
            #if data.Time.date() != self.lastEntryCheckDate:
            if (self.macd.Current.Value > self.macd.Signal.Current.Value and self.fast.Current.Value > 1.01 * self.slow.Current.Value):
                self.direction = 1
            elif (self.macd.Current.Value < self.macd.Signal.Current.Value and self.slow.Current.Value > 1.01 * self.fast.Current.Value):
                self.direction = -1
            if (self.direction != 0):
                self.MarketOrder(self.amzn.Symbol, 100*self.direction, True)
                self.bestPrice = self.amzn.Price
                self.stopOrder = self.StopMarketOrder(self.amzn.Symbol, -100*self.direction, self.GetStopPrice())
        else:
            # if invested, update the stop order settings to trail the max of the previous and current price
            if (self.direction == 1):
                self.bestPrice = max(self.bestPrice, self.amzn.Price)
            elif (self.direction == -1):
                self.bestPrice = min(self.bestPrice, self.amzn.Price)
            self.stopOrder.UpdateStopPrice(self.GetStopPrice())

    # return the price at which a stop order should be placed, given the
    def GetStopPrice(self):
        stopPrice = (1 - 0.1 * self.direction) * self.bestPrice
        self.Debug("Setting stop to " + str(stopPrice))
        return stopPrice

    def OnOrderEvent(self, orderEvent):
        if orderEvent.Status == OrderStatus.UpdateSubmitted:
            self.Debug("Updated stop to " + str(orderEvent.StopPrice))
        if orderEvent.Status == OrderStatus.Filled:
            order = self.Transactions.GetOrderById(orderEvent.OrderId)
            self.totalTrades += 1
            self.Plot("EMAs", "Trade", self.amzn.Price)
            # if the event is an execution event, then log the price of trade
            self.Debug(str(self.Time.date()) + ": Completed " + str(
                self.totalTrades) + " trades. Traded AMZN " + " at price " + str(orderEvent.FillPrice) + ", at quantity " + str(orderEvent.Quantity) + ". Current price is " + str(self.amzn.Price))