#
from AlgorithmImports import *
class CalmApricotGalago(QCAlgorithm):
    def Initialize(self):
        # Set the start and end dates for the backtest
        self.SetStartDate(2020, 1, 1)
        self.SetEndDate(2023, 12, 31)

        # Add the AMD stock to the algorithm
        self.AddEquity("AMD", Resolution.Minute)

        # Get the parameter value from the algorithm settings
        self.parameter_value = self.GetParameter("parameter-name")

    def OnData(self, data):
        if not data.ContainsKey("AMD"): return
        close = data["AMD"].Close
        
class CalmApricotGalago(QCAlgorithm):
    def Initialize(self):
        self.SetStartDate(2020, 1, 1)
        self.SetEndDate(2023, 12, 31)
        self.AddEquity("AMD", Resolution.Minute)
        self.parameter_value = self.GetParameter("parameter-name")

    def OnData(self, data):
        if not data.ContainsKey("AMD"): return
        close = data["AMD"].Close
        self.check_entry_points(close)

    def check_entry_points(self, price):
        bullish_signals = self.has_bullish_signals(price)
        bearish_signals = self.has_bearish_signals(price)
        if bullish_signals and price >= self.support1:
            self.open_long_position("AMD", 0.1)
            self.set_stop_loss(price - 0.035)
        if bearish_signals and price <= self.resistance1:
            self.open_short_position("AMD", 0.1)
            self.set_stop_loss(price + 0.035)

    def has_bullish_signals(self, price):
        # Implement your logic here
        pass

    def has_bearish_signals(self, price):
        # Implement your logic here
        pass

    def open_long_position(self, stock, quantity=0.1):
        order = Order(stock, quantity, OrderSide.Buy)
        self.SubmitOrder(order)

    def open_short_position(self, stock, quantity=0.1):
        order = Order(stock, quantity, OrderSide.Sell)
        self.SubmitOrder(order)

    def set_stop_loss(self, stock, price):
        order = StopLossOrder(stock, price, OrderSide.SellShort if price < self.Portfolio.Cash else OrderSide.Buy)
        self.SubmitOrder(order)
        # Check for entry points based on price and market conditions
        self.check_entry_points(close)

    def check_entry_points(self, price):
        # Implement logic to determine bullish signals
        bullish_signals = self.has_bullish_signals(price)

        # Implement logic to determine bearish signals
        bearish_signals = self.has_bearish_signals(price)

        if bullish_signals and price >= self.support1:
            self.open_long_position("AMD", 0.1)
            self.set_stop_loss(price - 0.035)

        if bearish_signals and price <= self.resistance1:
            self.open_short_position("AMD", 0.1)
            self.set_stop_loss(price + 0.035)

def has_bullish_signals(self, price):
    # Implement your logic here
    if price > self.sma.Current.Value:
        return True
    else:
        return False

def has_bearish_signals(self, price):
    # Implement your logic here
    if price < self.sma.Current.Value:
        return True
    else:
        return False


    def has_bullish_signals(self, price):
        # Implement logic to determine bullish signals based on price
        pass

    def has_bearish_signals(self, price):
        # Implement logic to determine bearish signals based on price
        pass

    def open_long_position(self, stock, quantity=0.1):
        self.Log("Opening long position in {0}".format(stock))
        order = Order(stock, quantity, OrderSide.Buy)
        self.SubmitOrder(order)

    def open_short_position(self, stock, quantity=0.1):
        self.Log("Opening short position in {0}".format(stock))
        order = Order(stock, quantity, OrderSide.Sell)
        self.SubmitOrder(order)

    def set_stop_loss(self, stock, price):
        self.Log("Setting stop loss for {0} at {1}".format(stock, price))
        order = StopLossOrder(stock, price, OrderSide.SellShort if price < self.Portfolio.Cash else OrderSide.Buy)
        self.SubmitOrder(order)