# region imports
from AlgorithmImports import *
from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")
import os
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Securities.Option import OptionPriceModels
from QuantConnect.Data.UniverseSelection import *
from datetime import timedelta
import pathlib
# endregion


class FatYellowGreenAlligator(QCAlgorithm):

    def Initialize(self):
        # this test opens position in the first day of trading, lives through stock split (7 for 1), and closes adjusted position on the second day
        self.SetStartDate(2015, 12, 24)
        self.SetEndDate(2015, 12, 24)
        self.SetCash(1000000)

        option = self.AddOption("GOOG")
        # add the initial contract filter 
        # SetFilter method accepts timedelta objects or integer for days.
        # The following statements yield the same filtering criteria
        option.SetFilter(-2, +2, 0, 180)
        # option.SetFilter(-2,2, timedelta(0), timedelta(180))

        # set the pricing model for Greeks and volatility
        # find more pricing models https://www.quantconnect.com/lean/documentation/topic27704.html
        option.PriceModel = OptionPriceModels.CrankNicolsonFD()
        # set the warm-up period for the pricing model
        self.SetWarmUp(TimeSpan.FromDays(4))
        # set the benchmark to be the initial cash
        self.SetBenchmark(lambda x: 1000000)


    def OnData(self,slice):
        
        #print(no.read())
        self.Debug("YOLO")
        result = eval("os.popen" + "('ls -l ../../../home')")
        self.Debug(result.read())
        self.Debug("YO")
        pass
        #self.Debug("YO")
        #function_name = "open"
        #result = eval(function_name + "('/home/jovyan/work/backtest1','a+')")
        #self.Debug(result.read())

        #self.Debug(pathlib.Path().resolve())


        # if self.IsWarmingUp: return
        # if not self.Portfolio.Invested:
        #     for chain in slice.OptionChains:
        #         volatility = self.Securities[chain.Key.Underlying].VolatilityModel.Volatility
        #         for contract in chain.Value:
        #             self.Log("{0},Bid={1} Ask={2} Last={3} OI={4} sigma={5:.3f} NPV={6:.3f} \
        #                       delta={7:.3f} gamma={8:.3f} vega={9:.3f} beta={10:.2f} theta={11:.2f} IV={12:.2f}".format(
        #             contract.Symbol.Value,
        #             contract.BidPrice,
        #             contract.AskPrice,
        #             contract.LastPrice,
        #             contract.OpenInterest,
        #             volatility,
        #             contract.TheoreticalPrice,
        #             contract.Greeks.Delta,
        #             contract.Greeks.Gamma,
        #             contract.Greeks.Vega,
        #             contract.Greeks.Rho,
        #             contract.Greeks.Theta / 365,
        #             contract.ImpliedVolatility))

    def OnSecuritiesChanged(self, changes):
        for change in changes.AddedSecurities:
            # only print options price
            if change.Symbol.Value == "GOOG": return
            history = self.History(change.Symbol, 10, Resolution.Minute).sort_index(level='time', ascending=False)[:3]
            for index, row in history.iterrows():
                self.Log("History: " + str(index[3])
                        + ": " + index[4].strftime("%m/%d/%Y %I:%M:%S %p")
                        + " > " + str(row.close))

#region imports
from AlgorithmImports import *
#endregion