@run-out I've tried it with the attached attribute, but unfortunately, I get an AttributeError: 'Lines_LineSeries_DataSeries_OHLC_OHLCDateTime_Abst' object has no attribute 'enter_price

@run-out well, whatever I do now with self.datas[0].enter_price in terms of multiplication or addition, I get a TypeError: unsupported operand type(s) for *: 'float' and 'NoneType'
I'm considering to discard this idea. This is actually an alternative try-out for a percentage-based take profit, which I couldn't get working in another way.
Maybe I should post the initial code in a new post

@run-out Your solution works very nice, but this won't work live, will it? At least it reads in the doc's that there's no live support with oco's, although I see reports that binance api can deal with oco orders. I'm intenting to trade live on a crypto exchange. Do you have experience with oco / live ?

@run-out nonetheless, thank you for sharing the idea! I just made a new post with the initial code with my take profit problem

Hello
I'm trying to set up two TP's with sell-limit orders and one SL with a sell-stop order.
The problem I'm encountering is that the first trades seem to be correct, but later bt creates multiple sell-limit orders without the buy order.
What am I doing wrong?

import backtrader as bt
from datetime import datetime

  
class SmaCross(bt.Strategy):
    # list of parameters which are configurable for the strategy
    params = dict(
        pfast=100,  # period for the fast moving average
        pslow=50   # period for the slow moving average
    )

    def __init__(self):
        self.sma0 = bt.ind.SMA(period=800) 
        sma1 = bt.ind.SMA(period=self.p.pfast)  # fast moving average
        sma2 = bt.ind.SMA(period=self.p.pslow)  # slow moving average
        self.crossover = bt.ind.CrossOver(sma1, sma2)  # crossover signal

        
    def log(self, txt, dt=None):
        #Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))
        
        
    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            # Buy/Sell order submitted/accepted to/by broker - Nothing to do
            return
        if order.status in [order.Completed]:
            if order.isbuy():
                self.sell(exectype=bt.Order.Limit, size=1, price=self.data.close[0] * 1.03) 
                self.sell(exectype=bt.Order.Limit, size=1, price=self.data.close[0] * 1.06) 
                self.sell(exectype=bt.Order.Stop, size=2, price=self.data.close[0] * 0.98)
                self.log('BUY EXECUTED, %.2f' % order.executed.price)

            elif order.issell():
                self.log('SELL EXECUTED, %.2f' % order.executed.price)
                
                
    def next(self):
        if not self.position:  # not in the market
            if self.crossover > 0 and self.datas[0] < self.sma0:  # if fast crosses slow to the upside
                self.buy_order = self.buy(exectype=bt.Order.Market, size=2)  # enter long

startcash = 10000
cerebro = bt.Cerebro()  # create a "Cerebro" engine instance

# Create a data feed
data = bt.feeds.GenericCSVData(
    dataname='data/1inch_perp_28-02_09-03_10S.csv',
    fromdate=datetime(2021, 3, 7),
    todate=datetime(2021, 3, 21),
    timeframe=bt.TimeFrame.Seconds,
    headers=False,
    separator=";",
    volume=5,
    openinterest=-1,
    dtformat=('%d.%m.%Y %H:%M:%S'),
)

cerebro.adddata(data)  # Add the data feed

cerebro.addstrategy(SmaCross)  # Add the trading strategy
cerebro.run()  # run it all

portvalue = cerebro.broker.getvalue()
pnl = portvalue - startcash
print('Final Portfolio Value: ${}'.format(portvalue))
print('P/L: ${}'.format(pnl))

cerebro.plot()  # and plot it with a single command

2021-03-07, BUY EXECUTED, 38.52
2021-03-07, SELL EXECUTED, 39.67
2021-03-07, SELL EXECUTED, 40.82
2021-03-07, BUY EXECUTED, 40.28
2021-03-07, SELL EXECUTED, 39.52
2021-03-07, BUY EXECUTED, 39.05
2021-03-07, SELL EXECUTED, 38.29
2021-03-07, BUY EXECUTED, 37.97
2021-03-08, SELL EXECUTED, 39.13
2021-03-08, SELL EXECUTED, 40.24
2021-03-08, SELL EXECUTED, 40.27
2021-03-08, SELL EXECUTED, 41.41
2021-03-08, SELL EXECUTED, 41.53
2021-03-08, SELL EXECUTED, 42.74

link csv file

@run-out well, whatever I do now with self.datas[0].enter_price in terms of multiplication or addition, I get a TypeError: unsupported operand type(s) for *: 'float' and 'NoneType'
I'm considering to discard this idea. This is actually an alternative try-out for a percentage-based take profit, which I couldn't get working in another way.
Maybe I should post the initial code in a new post

@run-out I've tried it with the attached attribute, but unfortunately, I get an AttributeError: 'Lines_LineSeries_DataSeries_OHLC_OHLCDateTime_Abst' object has no attribute 'enter_price

Hello everyone,

I'm trying to exit a position if price > executed price + x.
How can I fetch the order.executed.price?

I tried it with _orders[data][0]but it doesn't work:

def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            return
        if order.status in [order.Completed]:
            if order.isbuy():
                
                DISTCALC = ((self.ema1[0]-order.executed.price)/order.executed.price*100)
                self.log('BUY EXECUTED, %.2f' % order.executed.price)
                self.log('EMA Price, %.2f' % self.ema1[0])
                self.log('Price distance to EMA, %.2f' % DISTCALC + str('%'))
                
            elif order.issell():
                self.log('SELL EXECUTED, %.2f' % order.executed.price)
           
    def next(self):
        if not self.position and self.order==None: 
            if self.distance and self.below800EMA:
                self.price = self.sma1[0]
                self.order = self.buy(self.datas[0], exectype=bt.Order.Market, size=1)
                  
            if self.sma1[0] > self._orders[data][0]+10:
                
                self.order = self.close()

The error is:
TypeError: list indices must be integers or slices, not GenericCSVData