from QuantConnect.Algorithm import QCAlgorithm
from QuantConnect.Data.Custom import *
from QuantConnect.Orders import *
from QuantConnect.Securities.Option import OptionPriceModels
from datetime import timedelta, datetime, date, timedelta
import csv
import pytz
import io
from io import StringIO
import pandas as pd
from QuantConnect import OptionRight
from QuantConnect import Resolution
from QuantConnect import DataNormalizationMode 

'''
REFERENCE:
https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/order-types/combo-leg-limit-orders
https://www.quantconnect.com/docs/v2/writing-algorithms/securities/asset-classes/us-equity/handling-data
'''
class SPXWTradingAlgorithm(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2023, 12, 29)
        #self.SetEndDate(2024, 1, 31)
        self.SetCash(10000)

        self.UniverseSettings.Asynchronous = True 
        # spx = self.AddIndex("SPX").Symbol
        # option = self.AddIndexOption(spx, "SPXW") # SPXW is the target non-standard contract
        self.resolution = Resolution.Minute
        self.equity = self.AddEquity('QQQ', self.resolution)
        self.equity.SetDataNormalizationMode(DataNormalizationMode.Raw)
        
        self.option = self.AddOption(self.equity.Symbol, self.resolution)
        self.option.SetFilter(self.option_chain_filter)  #.SetFilter(-5, 5, 0, 10)
        self.symbol = self.option.Symbol

        # trigger every 60 secs - during trading hours
        self.seconds_delta = 60
        # self.Schedule.On(self.DateRules.EveryDay(self.symbol), 
        #                  self.TimeRules.Every(timedelta(seconds=self.seconds_delta)), 
        #                  self.Trade)
        self.is_backtest = True
        self.relevant_row = None
        self.sheet_url = 'https://docs.google.com/spreadsheets/d/1wwadCU8msu6FEUJt1ANoZS2qMO2MWiheARrdm7zaQlM/export?format=csv'
        self.full_sheet = None
        self.last_trade_date = None
        # self.tz = pytz.timezone('America/New_York')

    def option_chain_filter(self, option_chain):
        return option_chain.IncludeWeeklys()\
                    .Strikes(-100, 100)\
                    .Expiration(timedelta(0), timedelta(1))
   
    def retry_with_backoff(self, fn, retries=10, min_backoff=5):
        x = 0
        while True:
            try:
                return fn()
            except:
                if x == retries:
                    tprint("raise")
                    raise
                sleep = min_backoff * x
                tprint(f"sleep: {sleep}")
                time.sleep(sleep)
                x += 1
    
    def download_sheet_data(self):
        csv_string = self.Download(self.sheet_url)
        df_sheet = pd.read_csv(StringIO(csv_string), sep=",")
        return df_sheet

    def fetch_sheet_data_update(self, current_time):
        """Download google sheet data and return row for the requested date"""
        # csv_string = self.Download(self.sheet_url)
        # df_sheet = pd.read_csv(StringIO(csv_string), sep=",")
        if (self.full_sheet is None) or (not self.is_backtest):
            self.full_sheet = self.retry_with_backoff(self.download_sheet_data)
            self.Debug(f'Downloaded Sheet has {len(self.full_sheet)} rows')

        
        self.full_sheet['trigger_datetime'] = self.full_sheet['Trigger Time'].apply(lambda x: datetime.fromtimestamp(int(x)))  # , tz=self.tz
        prev_cutoff = current_time - timedelta(seconds=self.seconds_delta)
        mask = self.full_sheet['trigger_datetime'].between(prev_cutoff, current_time, inclusive='left')
        next_trade = self.full_sheet[mask]

        if len(next_trade) == 1:
            self.Debug(f'Found a trade between {prev_cutoff} and {current_time}')
            return next_trade.squeeze().to_dict()
        elif len(next_trade) > 1:
            self.Debug(f'Multiple trades in sheet between {prev_cutoff} and {current_time}')
            return
        else:
            self.Debug(f'No trades found in sheet')
            return

        
    def get_right_for_option_type(self, option_type):
        """Map option type strings to QC `right` [C -> 0; P -> 1]"""
        if option_type =='C':
            return 0
        elif option_type == 'P':
            return 1
        else:
            self.Debug("Invalid option type: " + option_type)

    def get_nearest_contract(self, opt_chain, strike_threshold, option_type):
        """Select the contract with the largest strike less than the threshold for the option type """
        right = self.get_right_for_option_type(option_type)
        chosen_contract = None
        for x in opt_chain:
            if x.Right == right and x.Strike <= strike_threshold: 
                if chosen_contract is None or chosen_contract.Strike < strike_threshold:
                    chosen_contract = x

        if chosen_contract is not None:
            self.Debug(f"For {strike_threshold=} {option_type=}: using {chosen_contract.Strike}")
        else:
            self.Debug(f"Could not find any contract for {strike_threshold=} {option_type=}")
        
        return chosen_contract

    def compute_mid(self, sec):
        return 0.5 * (sec.BidPrice + sec.AskPrice)

    def get_side_multiplier(self, side: str) -> int:
        if side in ['BUY', 'B']:
            return 1
        elif side in ['SELL', 'S']:
            return -1
        else:
            self.Debug("Unknown side: " + side)
            return

    def create_leg(self, opt_chain, trade_details, leg_num) -> float:
        assert leg_num in (1, 2)  # Only two legs supported right now
        
        contract = self.get_nearest_contract(opt_chain, trade_details[f'Strike {leg_num}'], trade_details[f'Right {leg_num}'])
        if contract is None:
            return None, None

        mult = self.get_side_multiplier(trade_details[f'Action {leg_num}'])
        contribution_to_limit = self.compute_mid(contract) * mult

        leg = Leg.Create(contract.Symbol, mult)  # TODO: allow for different qty across legs

        return leg, contribution_to_limit


    def GenerateTrade(self, slice):
        if self.IsWarmingUp:
            return

        self.Debug(f'Triggered at {self.Time}')
        optionchain = slice.OptionChains.get(self.symbol)
        if optionchain is None:
            self.Debug(f"Current option chain does not contain {self.symbol}. Skipping.")
            return

        trade_details = self.fetch_sheet_data_update(self.Time)

        if trade_details is None:
            return

        # expiry is same as current date for 0DTE - check timezone of remote host
        expiry = datetime.strptime(str(trade_details['TWS Contract Date']), '%Y%m%d')
        contracts = [i for i in optionchain if i.Expiry == expiry]
        
        if len(contracts) == 0:
            self.Debug(f"Not enough option contracts for {self.symbol} and {expiry=}")
            return
        

        quantity = int(trade_details['Order Quantity'])

        legs = []
        limit_prc = 0 
        for leg_num in (1, 2):
            this_leg, this_limit_prc = self.create_leg(contracts, trade_details, leg_num)
            if this_leg is None:
                self.Debug(f'Skipping because no leg found for {leg_num=}')
                return
            legs.append(this_leg)
            limit_prc += this_limit_prc

        self.ComboLimitOrder(legs, quantity=quantity, limitPrice=limit_prc)
        self.last_trade_date = self.Time.date()
        self.Debug(f'Generated order with {limit_prc=}')

        # TODO: make limit price competeitive by modifying the combo order limit price every few seconds

      
    def OnOrderEvent(self, orderEvent):
        if orderEvent.Status == OrderStatus.Filled:
            self.Debug("Order filled: " + str(orderEvent))

    def OnData(self, slice):
        if self.last_trade_date != self.Time.date():
            self.GenerateTrade(slice)
        else:
            open_orders = self.Transactions.GetOpenOrders()
            if len(open_orders) > 0:
                self.refresh_order_price(open_orders)  # TODO: increase frequency for refresh

    def refresh_order_price(self, open_orders):
        pass  # TODO