@backtrader

Ha! Finally figured out two things! One: why my own data feeder wasn't getting accepted and Two: who the bigger idiot is... hopefully was. Thanks for helping out.. saved a lot of my time.

thanks.. I noticed that and made the correction. I was hoping that he ran into a problem that has puzzled me for a bit. Here is the code that reproduces the problem for me. I simply modified the above code to keep it clean. The customized datafeeder is not recognized. It's not a typo, but must be something else I am missing???

thanks again as always,

 from __future__ import (absolute_import, division, print_function,
                         unicode_literals)
 import backtrader as bt
 import pandas as pd
 from backtrader.feeds import GenericCSVData
 import backtrader.feeds as btfeeds
 import datetime as datetime
 import backtrader.indicators as btind
 import numpy as np
 
 from backtrader.feeds import GenericCSVData
 
 class GenericCSV_PE(GenericCSVData):
 
     # Add a 'pe' line to the inherited ones from the base class
     lines = ('pe_ttm',)
 
     # openinterest in GenericCSVData has index 7 ... add 1
     # add the parameter to the parameters inherited from the base class
     params = (('pe_ttm', 8),)
 
 class MyStrategy(bt.Strategy):
 
 
     def log(self, txt, dt=None):
         ''' Logging function for this strategy'''
         dt = self.datas[0].datetime.date(0)
         dt_time = self.datas[0].datetime.time(0)
         dt_weekday = datetime.datetime.weekday(dt)
         print('%s, %s' % (dt.isoformat(), txt))
 
 
     def __init__(self):
         # Keep a reference to the "close" line in the data[0] dataseries
         # init stop loss and take profit order variables
         self.sl_order, self.tp_order = None, None
         self.datavolume = self.datas[0].volume
         self.pe = self.datas[0].pe_ttm
 
 
     def next(self):
         if self.datavolume[0] / np.mean(self.datavolume.get(size=10, ago=-1)) >= 1.25:
             self.buy()
             print(self.pe[0])
 
 
 
 if __name__ == '__main__':
     # Create a cerebro entity
     cerebro = bt.Cerebro()
 
 
     data = btfeeds.GenericCSV_PE(
 #    data = btfeeds.GenericCSVData(    
         dataname='E:\\Michael\\R\\Stocks\\300Index_New_Combined_Corrected\\000001.csv',
 
         nullvalue=0.0,
 
         dtformat=('%Y-%m-%d'),
 
         datetime=0,
         time=-1,
         high=2,
         low=3,
         open=1,
         close=4,
         volume=5,
         openinterest=-1,
         pe_ttm = 6
     )
 
     # Add the Data Feed to Cerebro
     cerebro.adddata(data)
 
     # Set our desired cash start
     cerebro.broker.setcash(100000.0)
 
     # Add a strategy
     cerebro.addstrategy(MyStrategy)
 
     # Print out the starting conditions
     print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
 
     # Run over everything
     cerebro.run()
 
     # Print out the final result
     print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
 
     cerebro.plot(style='bar')

error output:

     AttributeError                            Traceback (most recent call last)
     <ipython-input-21-26c81b63c6dc> in <module>()
          51 
          52 
     ---> 53     data = btfeeds.GenericCSV_PE(
          54 #    data = btfeeds.GenericCSVData(
          55         dataname='E:\\Michael\\R\\Stocks\\300Index_New_Combined_Corrected\\000001.csv',
     
     AttributeError: module 'backtrader.feeds' has no attribute 'GenericCSV_PE'

@samk

Hi,

What was your mistake that you corrected. You just said you got it to work. I am getting the same error.

valueError: time data '"2016-12-31' does not match format '%m/%d/%Y'

thanks..

@backtrader Thanks for the quick reply. I understand what you are saying. It would be nice if I had intrady data when I do my backtest, then this wold work perfectly with data playback. Unfortunatly, I only have access to Open, High, Low, Close data, so I'll have to dig around to see if there is a sample code that does what I need or god forbid... have to write my own... :)

Hi, thanks for the post. I realize this is an old post, but I like to clarify something. In an "ideal" back test, my traillig stop orders are based off high for each trading day for a buy (long) position, and off the low of the day for sell (short) postion. So, the trailing stop orders are updated each day after the close based on the highs and lows reached. If the next day, the low is below the trailing stop order, the long trade is closed for the day at the traling stop limit price, neglecting slippage. I see your example here all trail stops are based off the close, is there a way that I can impliment my way of testing? Can I choose the data set that the trailing stop orders are adjusted and executed based on? thanks.

@backtrader Thanks for the summary. As I suspected, there is much more to it, I'll have to think about it. There are just too many "unknow unknows".

Hi all,

I am just asking this question in general since I can't find a satisfactory answer on google. I am getting real time tick data (last trade price) for the markets I trade. What's the best way to process and store this data? I want to capture the data, resample it into 1 minute bars, calculate signals on the data and store it. Are there any modules that I can use along with Pandas to do this easily or is this a much bigger project than I think? I did find one asnwer to this on stackoverflow, but I don't think it's entirely correct.

thanks,

https://stackoverflow.com/questions/31141292/real-time-data-processing-with-pandas#

Right, I have searched the forum and saw you guys had a lot of discussion on this back in Dec, 2016 and made many changes along the way. I'll keep reading and researching, but is there a github depository or somewhere else where the latest working version of this example reside? That would save a lot of time.

thanks

Michael

Just curious to know how did you solve it? I get the same error when I run it. My data is definitely shorter than 10000 lines (even though there is no such limit anyway).. I am also studying paris trading. What is the problem and solution ?

thanks

Michael

Yup, that's it. That did it. I thought the second "order" was to keep track of the order, not to create another one. Lesson learned! Thanks.

By the way, thanks creating backtrader, I am sure everyone in the community is very thankful for you guys' great work.

Michael