@run-out Awesome thanks! I will make those changes this weekend and get back!

Sorry, I don't know why it didn't markdown the whole code.

@run-out Sure, this is just a simple strategy for my learning purposes of BT and python:

`from future import (absolute_import, division, print_function,
unicode_literals)
from datetime import datetime
import backtrader as bt

Create a Strategy

class TestStrategy(bt.Strategy):
params = (('order_pct', 0.95), ("buy_price_adjust", 0.0), ("buy_limit_adjust", 0.02), ("buy_stop_adjust", 0.02))

def log(self, txt, dt=None):
    """ Logging function for this strategy"""
    dt = dt or self.datas[0].datetime.date(0)
    print('%s, %s' % (dt.isoformat(), txt))

def __init__(self):
    # Keep a reference to the "close" line in the data[0] dataseries
    self.bar_executed = len(self)
    self.dataclose = self.datas[0].close

    # Create an order list
    self.o_li = list()

    # To keep track of pending orders and buy price/commission
    self.order = None
    self.buyprice = None
    self.buycomm = None

    # Add EMA and TRIX
    self.ema = bt.indicators.ExponentialMovingAverage((self.datas[0].high + self.datas[0].low) / 2, period=50,
                                                      plotname="EMAMid")
    self.ema2 = bt.indicators.ExponentialMovingAverage((self.datas[0].high + self.datas[0].low) / 2, period=15,
                                                      plotname="EMAMid")
    self.atr = bt.indicators.ATR(period=50, movav=bt.indicators.MovAv.Exponential)

    # Indicators for plotting
    bt.indicators.ExponentialMovingAverage(self.datas[0], period=50)

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

    # Check if an order has been completed
    # Attention: broker could reject order if not enough cash
    if order.status in [order.Completed, order.Canceled, order.Margin]:
        if order.isbuy():
            self.log(
                'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f, Size %.2f' %
                (order.executed.price,
                 order.executed.value,
                 order.executed.comm,
                 order.executed.size))

            self.buyprice = order.executed.price
            self.buycomm = order.executed.comm
        else:  # Sell
            self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f, Size %.2f' %
                     (order.executed.price,
                      order.executed.value,
                      order.executed.comm,
                      order.executed.size))
        self.bar_executed = len(self)

    elif order.status in [order.Canceled, order.Margin, order.Rejected]:
        self.log('Order Canceled/Margin/Rejected')

    # Clean up the order list.
    if not order.alive() and order in self.o_li:
        self.o_li.remove(order)

    # Write down: no pending order
    self.order = None

def notify_trade(self, trade):
    if not trade.isclosed:
        return

    self.log('OPERATION PROFIT, GROSS %.2f, NET %.2f' % (trade.pnl, trade.pnlcomm))

def next(self):
    # Check if an order is pending ... if yes, we cannot send a 2nd one
    if self.order:
        return
    # Check if we are in the market
    if not self.position:

        if self.ema[0] >= self.ema[-1] and (self.ema2[0] >= self.ema2[-1]):
            price = self.data.close[0] * (1.0 - self.p.buy_price_adjust)
            price_limit = price + self.atr[0]
            price_stop = price - self.atr[0]

            self.long_buy_order = self.buy_bracket(
                data=self.datas[0],
                size=None,
                exectype=bt.Order.Limit,
                plimit=price,
                stopprice=price_stop,
                stopexec=bt.Order.Stop,
                limitprice=price_limit,
                limitexec=bt.Order.Limit,
            )

        if self.ema[0] <= self.ema[-1] and (self.ema2[0] <= self.ema2[-1]):
            price = self.data.close[0] * (1.0 - self.p.buy_price_adjust)
            price_limit = price - self.atr[0]
            price_stop = price + self.atr[0]

            self.short_sell_order = self.sell_bracket(
                data=self.datas[0],
                size=None,
                exectype=bt.Order.Limit,
                plimit=price,
                stopprice=price_stop,
                stopexec=bt.Order.Stop,
                limitprice=price_limit,
                limitexec=bt.Order.Limit,
            )

    if self.position.size > 0 and (self.ema[0] <= self.ema[-1] or (self.ema2[0] <= self.ema2[-1])):
        self.close()

    if self.position.size < 0 and (self.ema[0] >= self.ema[-1] or (self.ema2[0] >= self.ema2[-1])):
        self.close()

if name == 'main':
# Variable for our starting cash
startcash = 100000

# Create a cerebro entity
cerebro = bt.Cerebro()

# Add a strategy
cerebro.addstrategy(TestStrategy)

# Create a Data Feed
data = bt.feeds.YahooFinanceData(dataname='AAPL',
                                 fromdate=datetime(2019, 6, 1),
                                 todate=datetime(2020, 11, 9),
                                 buffered=True)

# Add the Data Feed to Cerebro
cerebro.adddata(data)

# Set our desired cash start
cerebro.broker.setcash(startcash)

# Add a FixedSize sizer according to the stake
cerebro.addsizer(bt.sizers.FixedSize, stake=50)

# Set the commission
cerebro.broker.setcommission(commission=0.0)

# Add Analyzers:
cerebro.addanalyzer(bt.analyzers.SharpeRatio, _name="mySharpe", riskfreerate=0.001)
cerebro.addanalyzer(bt.analyzers.Returns, _name='returns')
cerebro.addanalyzer(bt.analyzers.SQN, _name='sqn')

# Print out the starting conditions
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

# Run over everything
cerebro.run()

portvalue = cerebro.broker.getvalue()
pnl = portvalue - startcash

# Print out the final result
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
print('Final Portfolio Value: ${}'.format(portvalue))
print('P/L: ${}'.format(pnl))

# Plot the results
cerebro.plot(style='bar', bardown='grey', barup="0.75", volume=False, grid=False)`

@run-out I am still fairly new to BT and python. Basically there are 3 signals generated - long, short or out. I have just learned on how to put in brackets if I want to use a PT and SL. But there are times when none of those gets hit and a signal to get out of the position hits (goes flat) and that leaves the PT and SL open if I use the brackets. So I assume I need to do it another way (issue PT and SL separately, and have them cancelled when the position == 0) instead of the brackets, unless there was a way to cancel the brackets if I went flat. Make sense?

Hi @Rumen-Nenov...did you get this figured out? I am at a similar junction you were when you wrote this. Thanks!

@vladisld Thanks for your help! Figured it out....feel a little dumb, still a n00b with BT :-)

@Jonny8 So if the path is to a csv file on the desktop, what should I use? Or do I need to drop that file into a python project directory and point to that?

Here is the data feed:

if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Datas are in a subfolder of the samples. Need to find where the script is
    # because it could have been called from anywhere
    modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
    datapath = os.path.join(modpath, '../../datas/orcl-1995-2014.txt')

    # Create a Data Feed
    data = bt.feeds.YahooFinanceCSVData(
        dataname=datapath,
        # Do not pass values before this date
        fromdate=datetime.datetime(2000, 1, 1),
        # Do not pass values after this date
        todate=datetime.datetime(2000, 12, 31),
        reverse=False)

And the error:

Traceback (most recent call last):
  File "C:/Users/chris/PycharmProjects/BT/main.py", line 40, in <module>
    cerebro.run()
  File "C:\Users\chris\AppData\Local\Programs\Python\Python38\lib\site-packages\backtrader\cerebro.py", line 1127, in run
    runstrat = self.runstrategies(iterstrat)
  File "C:\Users\chris\AppData\Local\Programs\Python\Python38\lib\site-packages\backtrader\cerebro.py", line 1210, in runstrategies
    data._start()
  File "C:\Users\chris\AppData\Local\Programs\Python\Python38\lib\site-packages\backtrader\feed.py", line 203, in _start
    self.start()
  File "C:\Users\chris\AppData\Local\Programs\Python\Python38\lib\site-packages\backtrader\feeds\yahoo.py", line 94, in start
    super(YahooFinanceCSVData, self).start()
  File "C:\Users\chris\AppData\Local\Programs\Python\Python38\lib\site-packages\backtrader\feed.py", line 674, in start
    self.f = io.open(self.p.dataname, 'r')
FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\chris\\PycharmProjects\\BT\\../../datas/orcl-1995-2014.txt'

Process finished with exit code 1

That's from the 1to100 example. I'm mainly trying to figure out how to read any csv data feed. Thanks!

I cannot figure out where to put a csv file in a datapath to be read for the datafeed. Even in the 1to100 example of importing ORCL datafeed I get an error it cannot find the path. IDE is Pycharm.

Thanks!

I have been racking my brain (still a somewhat newbie to BT) on how to setup this simple strategy:

You have two sma's (or any indicator really) and you LONG when both are rising (together), you EXIT LONG when either/or are falling. Reverse for SHORT. You SHORT when both are falling (together) and you EXIT SHORT when either/or are rising.

So you have 3 possible positions: LONG, SHORT OR OUT. I can code a LONG only with an EXIT(OUT) fine, but I cannot figure out how to combine the LONG and SHORT together. I have looked at bt.SIGNAL_LONGSHORT signals, other peoples code and I just can't figure it out. Thanks for any help!!