@michael172 Hi there, I'm having the same issue that you did: the error message "module 'backtrader.feeds' has no attribute 'symbolroll'" (symbolroll being my own creation). So I think my data feeder isn't being accepted. Could you perhaps share your code or portion of your code that you changed to solve the issue? Many thanks!
@Osofuego Could you share what changes to Michael's code would have fixed this issue? Many thanks again!
Hi, thanks in advance for anyone's assistance here. I'm trying to backtest using my own data stored in a local CSV file. It's a relatively straightforward project (it's a riff on the Quickstart guide model). but I have hit a wall that has left me spinning my wheels for too long. (There doesn't appear to be a current thread that addresses this specific error message...). My CSV has 6 columns of data: one datetime time series, and 5 custom indicators (no OHLC data). When I upload my data with the custom parameters adjusted for my custom data and I run it, I get a "TypeError: must be real number, not str" stemming from an issue "self.array[self.idx + ago] = value" stemming from line 222 in the linebuffer.py. I'm pretty sure my data is uploading correctly (printing the head shows everything is normal) but clearly I'm producing strings where I need to have only int. Can someone please advise if they know where this newbie got trapped? Many thanks!
Relevant code:
lines = (
'Date',
'Abra1',
'Abra2',
'Abra3',
'Abra4',
'Abra5',
)
params = (
('dtformat', '%m/%d/%Y'),
('Date', 0),
('time', -1),
('open', -1),
('high', -1),
('low', -1),
('close', -1),
('volume', -1),
('openinterest', -1),
('Abra1', 1),
('Abra2', 2),
('Abra3', 3),
('Abra4', 4),
('Abra5', 5),
)
datafields = btfeeds.PandasData.datafields + (['Date', 'Abra1', 'Abra2', 'Abra3', "Abra4", "Abra5"])
mydict = dict(lines=tuple(lines), params=params, datafields=bt.feeds.PandasData.datafields + list(lines),)
PandasDataAbra = type('PandasDataAbra', (btfeeds.PandasData,), mydict)
dataframe = pd.read_csv("C:/Users/user/PycharmProjects/sampledata.csv",
skiprows=0,
header=0,
parse_dates=True,
)
data = PandasDataAbra(dataname=dataframe)
Error:
File "C:\Users\user\PycharmProjects\venv\lib\site-packages\backtrader\linebuffer.py", line 222, in __setitem__
self.array[self.idx + ago] = value
TypeError: must be real number, not str
Head (to check out underlying data):
Date Abra1 Abra2 Abra3 Abra4 Abra5
0 3/26/2007 1.2628 1.3365 16.632 18.135 0.845
1 3/27/2007 2.4871 0.1935 16.776 18.265 0.875
2 3/28/2007 -1.3629 -0.4005 17.268 18.577 0.450
3 3/29/2007 -2.8490 -0.1530 17.376 18.577 0.140
4 3/30/2007 -0.8008 -0.3105 17.400 18.603 0.415
All code:
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import datetime # For datetime objects
import os.path # To manage paths
import sys # To find out the script name (in argv[0])
import pandas as pd
import backtrader as bt
import pandas as pd
import backtrader.feeds as btfeeds
from backtrader.feeds import GenericCSVData
from backtrader.feeds import PandasData
from backtrader import Cerebro
from backtrader import feed
lines = (
'Date',
'Abra1',
'Abra2',
'Abra3',
'Abra4',
'Abra5',
)
params = (
('dtformat', '%m/%d/%Y'),
('Date', 0),
('time', -1),
('open', -1),
('high', -1),
('low', -1),
('close', -1),
('volume', -1),
('openinterest', -1),
('Abra1', 1),
('Abra2', 2),
('Abra3', 3),
('Abra4', 4),
('Abra5', 5),
)
datafields = btfeeds.PandasData.datafields + (['Date', 'Abra1', 'Abra2', 'Abra3', "Abra4", "Abra5"])
mydict = dict(lines=tuple(lines), params=params, datafields=bt.feeds.PandasData.datafields + list(lines),)
PandasDataAbra = type('PandasDataAbra', (btfeeds.PandasData,), mydict)
class TestStrategy(bt.Strategy):
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.dataAbra4 = self.datas[0].Abra4
# To keep track of pending orders and buy price/commission
self.order = None
self.buyprice = None
self.buycomm = None
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]:
if order.isbuy():
self.log(
'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
(order.executed.price,
order.executed.value,
order.executed.comm))
self.buyprice = order.executed.price
self.buycomm = order.executed.comm
else: # Sell
self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
(order.executed.price,
order.executed.value,
order.executed.comm))
self.bar_executed = len(self)
elif order.status in [order.Canceled, order.Margin, order.Rejected]:
self.log('Order Canceled/Margin/Rejected')
# 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):
# Simply log the closing price of the series from the reference
self.log('Close, %.2f' % self.Abra4[0])
# 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:
# Not yet ... we MIGHT BUY if ...
if self.Abra4[0] > self.Abra2[0] and self.Abra4[0] > 0:
# BUY, BUY, BUY!!! (with default parameters)
self.log('BUY CREATE, %.2f' % self.Abra4[0])
# Keep track of the created order to avoid a 2nd order
self.order = self.buy()
else:
# Already in the market ... we might sell
if self.Abra4[0] < self.Abra2[0]:
# SELL, SELL, SELL!!! (with all possible default parameters)
self.log('SELL CREATE, %.2f' % self.F4[0])
# Keep track of the created order to avoid a 2nd order
self.order = self.sell()
if __name__ == '__main__':
cerebro: Cerebro = bt.Cerebro()
cerebro.addstrategy(TestStrategy)
dataframe = pd.read_csv("C:/Users/user/PycharmProjects/sampledata.csv",
skiprows=0,
header=0,
parse_dates=True,
)
data = PandasDataAbra(dataname=dataframe)
cerebro.adddata(data)
cerebro.broker.setcash(100000.0)
cerebro.addsizer(bt.sizers.FixedSize, stake=10)
cerebro.broker.setcommission(commission=0.001)
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
print(dataframe.head())
cerebro.run()
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
# cerebro.plot()
@michael172 Hi there, I'm having the same issue that you did: the error message "module 'backtrader.feeds' has no attribute 'symbolroll'" (symbolroll being my own creation). So I think my data feeder isn't being accepted. Could you perhaps share your code or portion of your code that you changed to solve the issue? Many thanks!
@Osofuego Could you share what changes to Michael's code would have fixed this issue? Many thanks again!