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Backtrader Target Values Example Error Message
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Hello,
I am attempting to run the sample code from:
https://www.backtrader.com/docu/order_target/order_target.html
and receiving the following error:
Traceback (most recent call last):
File "C:/Users/Sam/PycharmProjects/Test/.ipynb_checkpoints/Backtrader Target Values & Stop Order.py", line 217, in <module>
runstrat()
File "C:/Users/Sam/PycharmProjects/Test/.ipynb_checkpoints/Backtrader Target Values & Stop Order.py", line 115, in runstrat
args = parse_args(args)
File "C:/Users/Sam/PycharmProjects/Test/.ipynb_checkpoints/Backtrader Target Values & Stop Order.py", line 192, in parse_args
help=('Use order_target_size'))
File "C:\Users\Sam\Anaconda64Best\lib\argparse.py", line 1348, in add_argument
return self._add_action(action)
File "C:\Users\Sam\Anaconda64Best\lib\argparse.py", line 1571, in _add_action
raise ValueError(msg)
ValueError: mutually exclusive arguments must be optionalI have tried to set:
pgroup = parser.add_mutually_exclusive_group(required=True)to both True, False, and None. But error keeps coming up.
I have set target size to = true for both of the following lines in the code:
params = ( # define target size, value, or percent as order type ('use_target_size', True), ('use_target_value', False), ('use_target_percent', False), )and
pgroup.add_argument('--target-size', required=True, action='store_true', # use target size help=('Use order_target_size')) pgroup.add_argument('--target-value', required=False, action='store_true', # use target value help=('Use order_target_value')) pgroup.add_argument('--target-percent', required=False, # use target percentage action='store_true', help=('Use order_target_percent'))Error still comes up though for the mutually exclusive thing. Am I missing something in terms of not setting something to True or to None that still needs to be set? Thanks a lot in advance. Entire code is below for reference:
from __future__ import (absolute_import, division, print_function, unicode_literals) import argparse import datetime # For datetime objects from datetime import datetime import backtrader as bt import backtrader.feeds as btfeeds class TheStrategy(bt.Strategy): ''' This strategy is loosely based on some of the examples from the Van K. Tharp book: *Trade Your Way To Financial Freedom*. The logic: - Enter the market if: - The MACD.macd line crosses the MACD.signal line to the upside - The Simple Moving Average has a negative direction in the last x periods (actual value below value x periods ago) - Set a stop price x times the ATR value away from the close - If in the market: - Check if the current close has gone below the stop price. If yes, exit. - If not, update the stop price if the new stop price would be higher than the current # The logic in the sample is rather dumb and only meant for testing: During odd months (Jan, Mar, ...), use the day as TARGET (in the case of order_target_value multiplying the day by 1000) This mimics an increasing target During even months (Feb, Apr, ...) use 31 - day as the TARGET This mimics an decreasing target ''' params = ( # define target size, value, or percent as order type ('use_target_size', True), ('use_target_value', False), ('use_target_percent', False), ) def notify_order(self, order): if order.status == order.Completed: pass if not order.alive(): self.order = None # indicate no order is pending def start(self): self.order = None # sentinel to avoid operations on pending order def next(self): dt = self.data.datetime.date() portfolio_value = self.broker.get_value() print('%04d - %s - Position Size: %02d - Value %.2f' % (len(self), dt.isoformat(), self.position.size, portfolio_value)) data_value = self.broker.get_value([self.data]) # portfolio value for that specific stock if self.p.use_target_value: # if we use target value as order execution print('%04d - %s - data value %.2f' % (len(self), dt.isoformat(), data_value)) elif self.p.use_target_percent: # if we use target percentage as order execution port_perc = data_value / portfolio_value print('%04d - %s - data percent %.2f' % (len(self), dt.isoformat(), port_perc)) if self.order: # if order is placed return # pending order execution size = dt.day # size of order is based on the day (odd or even months) if (dt.month % 2) == 0: size = 31 - size # if it is an even month, use 31 - day as the target (for odd months, use the day as the target) # determine if we base our order on either: target size, target value, or target percentage if self.p.use_target_size: # if we use target size as the order execution target = size # target is the size of the trade (number of shares) print('%04d - %s - Order Target Size: %02d' % (len(self), dt.isoformat(), size)) # based on size self.order = self.order_target_size(target=size) # place order based on order target size (number of shares) elif self.p.use_target_value: # if we use target value, target value = size (number of shares * 1000) as we are multiplying the day by 1000 value = size * 1000 print('%04d - %s - Order Target Value: %.2f' % (len(self), dt.isoformat(), value)) # based on value self.order = self.order_target_value(target=value) elif self.p.use_target_percent: # if we use target percentage of portfolio to place orders (number of shares (size) divided by 100 to see what % of the portfolio it is) percent = size / 100.0 print('%04d - %s - Order Target Percent: %.2f' % (len(self), dt.isoformat(), percent)) # based on percentage self.order = self.order_target_percent(target=percent) def runstrat(args=None): args = parse_args(args) cerebro = bt.Cerebro() cerebro.broker.setcash(args.cash) # set brokerage cash value dkwargs = dict() if args.fromdate is not None: dkwargs['fromdate'] = datetime.strptime(args.fromdate, "%m/%d/%Y") if args.todate is not None: dkwargs['todate'] = datetime.strptime(args.todate, "%m/%d/%Y") # data data = btfeeds.GenericCSVData( dataname='C:\\Users\\Sam\\PycharmProjects\\Test\\.ipynb_checkpoints\\orcl-1995-2014.csv', fromdate=datetime.datetime.strptime("1/1/2000", "%m/%d/%Y"), todate=datetime.datetime.strptime("12/31/2000", "%m/%d/%Y"), nullvalue=0.0, # missing values to be replaced with 0 dtformat=('%m/%d/%Y'), datetime=0, time=-1, open=1, high=2, low=3, close=4, adjclose=5, volume=6, openinterest=-1, ) cerebro.adddata(data) # strategy cerebro.addstrategy(TheStrategy, use_target_size=args.target_size, use_target_value=args.target_value, use_target_percent=args.target_percent) cerebro.run() if args.plot: # plot strategy pkwargs = dict(style='bar') if args.plot is not True: # evals to True but is not True npkwargs = eval('dict(' + args.plot + ')') # args were passed pkwargs.update(npkwargs) cerebro.plot(**pkwargs) def parse_args(pargs=None): parser = argparse.ArgumentParser( formatter_class=argparse.ArgumentDefaultsHelpFormatter, description='Sample for Order Target') parser.add_argument('--data', required=False, default='C:\\Users\\Sam\\PycharmProjects\\Test\\.ipynb_checkpoints\\orcl-1995-2014.csv', help='Specific data to be read in') parser.add_argument('--fromdate', required=False, default='2005-01-01', help='Starting date in MM/DD/YYYY format') parser.add_argument('--todate', required=False, default='2006-12-31', help='Ending date in MM/DD/YYYY format') parser.add_argument('--cash', required=False, action='store', # ending cash at end of date type=float, default=1000000, help='Ending date in MM/DD/YYYY format') pgroup = parser.add_mutually_exclusive_group(required=True) pgroup.add_argument('--target-size', required=True, action='store_true', # use target size help=('Use order_target_size')) pgroup.add_argument('--target-value', required=False, action='store_true', # use target value help=('Use order_target_value')) pgroup.add_argument('--target-percent', required=False, # use target percentage action='store_true', help=('Use order_target_percent')) # Plot options parser.add_argument('--plot', '-p', nargs='?', required=False, metavar='kwargs', const=True, help=('Plot the read data applying any kwargs passed\n' '\n' 'For example:\n' '\n' ' --plot style="candle" (to plot candles)\n')) if pargs is not None: return parser.parse_args(pargs) return parser.parse_args() if __name__ == '__main__': runstrat() -
@samk said in Backtrader Target Values Example Error Message:
I am attempting to run the sample code from:
https://www.backtrader.com/docu/order_target/order_target.htmlNo you are not. You are running a modified version, hence the error.
@samk said in Backtrader Target Values Example Error Message:
pgroup.add_argument('--target-size', required=True, action='store_true', # use target size help=('Use order_target_size')) pgroup.add_argument('--target-value', required=False, action='store_true', # use target value help=('Use order_target_value')) pgroup.add_argument('--target-percent', required=False, # use target percentage action='store_true', help=('Use order_target_percent'))At leas there the code has been modified.
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Below is the original code pasted from the site exactly as it is. Getting error:
C:\Users\Sam\Anaconda64Best\python.exe "C:/Users/Sam/PycharmProjects/Test/.ipynb_checkpoints/Backtrader Target Value Example.py"
usage: Backtrader Target Value Example.py [-h] [--data DATA]
[--fromdate FROMDATE]
[--todate TODATE] [--cash CASH]
(--target-size | --target-value | --target-percent)
[--plot [kwargs]]
Backtrader Target Value Example.py: error: one of the arguments --target-size --target-value --target-percent is requiredI have tried to set either size, target value, or target percent to 'True' to from its current default 'False' to try to resolve in the block of code:
params = ( # define target size, value, or percent as order type ('use_target_size', False), ('use_target_value', False), ('use_target_percent', False), )However, error still comes up. Is there somewhere else in the code that needs to be set to 'True' instead that I am not seeing and changing? Thanks for the help in advance. Full code is below from the website:
from __future__ import (absolute_import, division, print_function, unicode_literals) import argparse import datetime # For datetime objects from datetime import datetime import backtrader as bt import backtrader.feeds as btfeeds class TheStrategy(bt.Strategy): ''' This strategy is loosely based on some of the examples from the Van K. Tharp book: *Trade Your Way To Financial Freedom*. The logic: - Enter the market if: - The MACD.macd line crosses the MACD.signal line to the upside - The Simple Moving Average has a negative direction in the last x periods (actual value below value x periods ago) - Set a stop price x times the ATR value away from the close - If in the market: - Check if the current close has gone below the stop price. If yes, exit. - If not, update the stop price if the new stop price would be higher than the current # The logic in the sample is rather dumb and only meant for testing: During odd months (Jan, Mar, ...), use the day as TARGET (in the case of order_target_value multiplying the day by 1000) This mimics an increasing target During even months (Feb, Apr, ...) use 31 - day as the TARGET This mimics an decreasing target ''' params = ( # define target size, value, or percent as order type ('use_target_size', False), ('use_target_value', False), ('use_target_percent', False), ) def notify_order(self, order): if order.status == order.Completed: pass if not order.alive(): self.order = None # indicate no order is pending def start(self): self.order = None # sentinel to avoid operations on pending order def next(self): dt = self.data.datetime.date() portfolio_value = self.broker.get_value() print('%04d - %s - Position Size: %02d - Value %.2f' % (len(self), dt.isoformat(), self.position.size, portfolio_value)) data_value = self.broker.get_value([self.data]) # portfolio value for that specific stock if self.p.use_target_value: # if we use target value as order execution print('%04d - %s - data value %.2f' % (len(self), dt.isoformat(), data_value)) elif self.p.use_target_percent: # if we use target percentage as order execution port_perc = data_value / portfolio_value print('%04d - %s - data percent %.2f' % (len(self), dt.isoformat(), port_perc)) if self.order: # if order is placed return # pending order execution size = dt.day # size of order is based on the day (odd or even months) if (dt.month % 2) == 0: size = 31 - size # if it is an even month, use 31 - day as the target (for odd months, use the day as the target) # determine if we base our order on either: target size, target value, or target percentage if self.p.use_target_size: # if we use target size as the order execution target = size # target is the size of the trade (number of shares) print('%04d - %s - Order Target Size: %02d' % (len(self), dt.isoformat(), size)) # based on size self.order = self.order_target_size(target=size) # place order based on order target size (number of shares) elif self.p.use_target_value: # if we use target value, target value = size (number of shares * 1000) as we are multiplying the day by 1000 value = size * 1000 print('%04d - %s - Order Target Value: %.2f' % (len(self), dt.isoformat(), value)) # based on value self.order = self.order_target_value(target=value) elif self.p.use_target_percent: # if we use target percentage of portfolio to place orders (number of shares (size) divided by 100 to see what % of the portfolio it is) percent = size / 100.0 print('%04d - %s - Order Target Percent: %.2f' % (len(self), dt.isoformat(), percent)) # based on percentage self.order = self.order_target_percent(target=percent) def runstrat(args=None): args = parse_args(args) cerebro = bt.Cerebro() cerebro.broker.setcash(args.cash) # set brokerage cash value dkwargs = dict() if args.fromdate is not None: dkwargs['fromdate'] = datetime.strptime(args.fromdate, "%m/%d/%Y") if args.todate is not None: dkwargs['todate'] = datetime.strptime(args.todate, "%m/%d/%Y") # data data = btfeeds.GenericCSVData( dataname='C:\\Users\\Sam\\PycharmProjects\\Test\\.ipynb_checkpoints\\orcl-1995-2014.csv', fromdate=datetime.datetime.strptime("1/1/2000", "%m/%d/%Y"), todate=datetime.datetime.strptime("12/31/2000", "%m/%d/%Y"), nullvalue=0.0, # missing values to be replaced with 0 dtformat=('%m/%d/%Y'), datetime=0, time=-1, open=1, high=2, low=3, close=4, adjclose=5, volume=6, openinterest=-1, ) cerebro.adddata(data) # strategy cerebro.addstrategy(TheStrategy, use_target_size=args.target_size, use_target_value=args.target_value, use_target_percent=args.target_percent) cerebro.run() if args.plot: # plot strategy pkwargs = dict(style='bar') if args.plot is not True: # evals to True but is not True npkwargs = eval('dict(' + args.plot + ')') # args were passed pkwargs.update(npkwargs) cerebro.plot(**pkwargs) def parse_args(pargs=None): parser = argparse.ArgumentParser( formatter_class=argparse.ArgumentDefaultsHelpFormatter, description='Sample for Order Target') parser.add_argument('--data', required=False, default='C:\\Users\\Sam\\PycharmProjects\\Test\\.ipynb_checkpoints\\orcl-1995-2014.csv', # set file path help='Specific data to be read in') parser.add_argument('--fromdate', required=False, default='2005-01-01', help='Starting date in MM/DD/YYYY format') # set file format parser.add_argument('--todate', required=False, default='2006-12-31', help='Ending date in MM/DD/YYYY format') # set file format parser.add_argument('--cash', required=False, action='store', # ending cash at end of date type=float, default=1000000, help='Ending date in MM/DD/YYYY format') # set file format pgroup = parser.add_mutually_exclusive_group(required=True) pgroup.add_argument('--target-size', required=False, action='store_true', # use target size help=('Use order_target_size')) pgroup.add_argument('--target-value', required=False, action='store_true', # use target value help=('Use order_target_value')) pgroup.add_argument('--target-percent', required=False, # use target percentage action='store_true', help=('Use order_target_percent')) # Plot options parser.add_argument('--plot', '-p', nargs='?', required=False, metavar='kwargs', const=True, help=('Plot the read data applying any kwargs passed\n' '\n' 'For example:\n' '\n' ' --plot style="candle" (to plot candles)\n')) if pargs is not None: return parser.parse_args(pargs) return parser.parse_args() if __name__ == '__main__': runstrat()