import pandas as pd
from io import StringIO

class CathieWoods1YearBacktest1Kcapital(QCAlgorithm):

    def Initialize(self):
        
        #BackTest start date one year 
        self.SetStartDate(2020, 9, 1)
        
        # Target market
        self.SetCash(100000)
        
        #Universe selection
        self.AddUniverse(self.Coarse)
        
        #using Hourly resolution for more data points.
        self.UniverseSettings.Resolution = Resolution.Hour
        
        self.run = False
        self.tickers = []
        self.tickers_value = []
        self.tickers_list = []
        self.date_list = []
        self.direction_list = []
        self.buying_stocks = []
        self.invested_stocks = []
        self.is_downloaded = False
                             
        #Run everyday at midnight to scrape the daily updates
        self.Schedule.On(self.DateRules.EveryDay(),  
                         self.TimeRules.At(0, 0),
                         self.DownloadTickers)
        # Set Fee Model to No trading fees to mimic new fee model                
        self.SetSecurityInitializer(lambda x: x.SetFeeModel(ConstantFeeModel(0)))
                     
    def DownloadTickers(self):
        
        #Reset
        self.run = False
        self.buying_stocks = []
        self.invested_stocks = []
        
        #Check if downloaded
        if self.is_downloaded == False:
            csv = self.Download("https://www.dropbox.com/s/sqjb76w2faer76l/Trade_Log.csv?dl=1")
            df = pd.read_csv(StringIO(csv))
            self.tickers_list = df["Ticker"].to_list()
            self.date_list = df["Date"].to_list()
            self.direction_list = df["Direction"].to_list()
            self.is_downloaded = True
            #once downloaded mark as downloaded
            
    def Coarse(self, coarse):
        filtered = [x for x in coarse if x.Symbol.Value in self.tickers_list and x.HasFundamentalData]
        return [x.Symbol for x in filtered]
        # Filter for stocks in the universe

    def OnSecuritiesChanged(self, changes):
        for stock in changes.RemovedSecurities:
            pass
        history = self.History([stock.Symbol for stock in changes.AddedSecurities], 50, Resolution.Hour)
        for stock in changes.AddedSecurities:
            symbol = stock.Symbol
            if symbol in history.index:
                self.tickers.append(symbol)
                self.tickers_value.append(symbol.Value)
        # make list of symbols and value
      
        
    def OnData(self, data):
        
        #Reset invested stocks list
        self.invested_stocks = []
   
        #Check order fills
        for kvp in self.Portfolio:
            security_holding = kvp.Value
            if security_holding.Invested:
                symbol = security_holding.Symbol
                self.invested_stocks.append(symbol.Value)
                average_price = security_holding.AveragePrice
                current_price = self.Securities[symbol].Price
                change = current_price / average_price
                
                #Check if invested stock's current price greater than or less than average price by 10% 0r 5%, if so, sell
                if change > 1.1 or change < 0.95:
                    self.Liquidate(symbol)
        
        #Check if logic ran today
        if self.run == False:
            today_date = (str(self.Time.month) + "/" + str(self.Time.day) + "/" + str(self.Time.year))
            for i in range(len(self.date_list)):
                if self.date_list[i] == today_date:
                    ticker = self.tickers_list[i]
                    direction = self.direction_list[i]
                    if ticker in self.tickers_value:
                        index = self.tickers_value.index(ticker)
                        if direction == "Buy" and ticker not in self.buying_stocks and ticker not in self.invested_stocks:
                            # if self.Portfolio.Cash > 1000:
                                self.SetHoldings(str(self.tickers[index]), 0.1)
                                self.buying_stocks.append(ticker)
                            # Code is front heavy, not true reflection of strategy
                            # set entry_price. Not yet code. If need to code, for change of strategy will change data.Pls ignore.
            
            #Only run logic once per day
            self.run = True