@azuric This is how I add Pandas Dataframe to datafeeds

cerebro = bt.Cerebro()  
feed = pd.read_csv('test.csv',index_col = 'Date',parse_dates = True)
data = bt.feeds.PandasData(dataname = feed)

and this is how I used talib library to calculate indicators (you can get indicator calculations from backtrader itself too)

class SmaCross(bt.Strategy):    
        params = dict(pslow=20,order_percentage= 0.99,ticker = 'NEPSE')         
            def __init__(self):    
            sma = bt.talib.SMA(self.data.close,timeperiod=self.p.pslow)    
            self.crossover = bt.ind.CrossOver(self.data.close, sma, plot = True)  
    
        ``

Hi, I'm trying to create round_trip_tearsheet using pyfolio because it has trade stats like profit factor, average winning trade, average losing trade, percent profitable, etc. I found two ways to do it. One is by adding round_trips= True in pf.create_full_tearsheet and another is using pf.create_round_trip_tear_sheet but I failed in both.

upon running the first one, I get some stats and charts but not the stats I want with RuntimeError: Selected KDE bandwidth is 0. Cannot estiamte density.

Second alternative with create_round_trip_tear_sheet gives KeyError: ('block_dir', 'block_time')

Please shed some light here on how I can get those trade stats. Thank you in advance. @ab_trader Below is my full code.

%matplotlib inline
from datetime import datetime
import backtrader as bt
import pandas as pd
import math
import pyfolio as pf
import backtrader.analyzers as btanalyzers
class SmaCross(bt.Strategy):
    params = dict(pslow=20,order_percentage= 0.99,ticker = 'NEPSE')
    
    def log(self, txt, dt=None):
            dt = dt or self.datas[0].datetime.date(0)
            print('%s, %s' % (dt.isoformat(), txt))
            
    def __init__(self):
        sma = bt.talib.SMA(self.data.close,timeperiod=self.p.pslow)
        self.crossover = bt.ind.CrossOver(self.data.close, sma, plot = True)  
    
    def next(self):
        if not self.position:  
            if self.crossover > 0: 
                
                amount_to_invest = (self.p.order_percentage*self.broker.cash)
                self.size = math.floor(amount_to_invest/self.data.close)
                self.buy(size=self.size)           
#                 self.log('%s,Buy, %d,%d 0,%.0f' % (self.params.ticker,self.size,self.data.close[0],cerebro.broker.getvalue()))
        elif self.crossover < 0: 
                self.close() 
#                 self.log('%s,Sell, %d,%d 0,%.0f' % (self.params.ticker,self.size,self.data.close[0],cerebro.broker.getvalue()))
    
cerebro = bt.Cerebro()  
feed = pd.read_csv('test.csv',index_col = 'Date',parse_dates = True)
data = bt.feeds.PandasData(dataname = feed)
cerebro.adddata(data) 
cerebro.addstrategy(SmaCross)  
print('Starting Portfolio Value: %.0f' % cerebro.broker.getvalue())
# strat = cerebro.run()
print('Final Portfolio Value: %.0f' % cerebro.broker.getvalue())
cerebro.addanalyzer(bt.analyzers.PyFolio, _name='pyfolio')
results = cerebro.run()
strat = results[0]
pyfoliozer = strat.analyzers.getbyname('pyfolio')
returns, positions, transactions, gross_lev = pyfoliozer.get_pf_items()
pf.create_round_trip_tear_sheet(returns, positions, transactions)
# pf.create_full_tear_sheet(
#     returns,
#     positions=positions,
#     transactions=transactions,
#     round_trips=True)

@azuric This is how I add Pandas Dataframe to datafeeds

cerebro = bt.Cerebro()  
feed = pd.read_csv('test.csv',index_col = 'Date',parse_dates = True)
data = bt.feeds.PandasData(dataname = feed)

and this is how I used talib library to calculate indicators (you can get indicator calculations from backtrader itself too)

class SmaCross(bt.Strategy):    
        params = dict(pslow=20,order_percentage= 0.99,ticker = 'NEPSE')         
            def __init__(self):    
            sma = bt.talib.SMA(self.data.close,timeperiod=self.p.pslow)    
            self.crossover = bt.ind.CrossOver(self.data.close, sma, plot = True)  
    
        ``

I feel ashamed for such mistakes. Thank you very much sir. What I thought was if it was parenthesis related problem, I thought it would be indicated in the error but it looks something different. Thank you. God Bless you.

from datetime import datetime
import backtrader as bt
import pandas as pd
import math

class SmaCross(bt.Strategy):
    params = dict(pslow=20,order_percentage= 0.99,ticker = 'NEPSE')
    
    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):
        sma = bt.talib.SMA(self.data.close,timeperiod=self.p.pslow)
        self.crossover = bt.ind.CrossOver(self.data.close, sma)  
    
    def notify_trade(self, trade):
                    if not trade.isclosed:
                        return
                    self.log('%.2f, %s, %.2f, %.2f, %.2f' %
                     (trade.pnl, self.params.ticker, self.size, self.data.close[0], cerebro.broker.getvalue()  
                           
    def next(self):
        if not self.position:  
            if self.crossover > 0: 
                
                amount_to_invest = (self.p.order_percentage*self.broker.cash)
                self.size = math.floor(amount_to_invest/self.data.close)
                self.buy(size=self.size) 
    
        elif self.crossover < 0:  
                self.close() 
    
cerebro = bt.Cerebro()  
feed = pd.read_csv('test.csv',index_col = 'Date',parse_dates = True)
data = bt.feeds.PandasData(dataname = feed)
data
cerebro.adddata(data) 
cerebro.addstrategy(SmaCross)  

print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.run() 
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.plot()  


  File "<ipython-input-29-9a6b79c4a5d7>", line 25
    def next(self):
      ^
SyntaxError: invalid syntax

I hope followed your instructions.

@ab_trader It seems that the immediate code that follows notify_trade is shown as invalid syntax.

@ab_trader I got an error in def next(self): as invalid syntax. I've posted my whole code below so that you can get a clear picture. Thank you very much for your help. It means a lot to me. God bless you.

from datetime import datetime
import backtrader as bt
import pandas as pd
import math

class SmaCross(bt.Strategy):
params = dict(pslow=20,order_percentage= 0.99,ticker = 'NEPSE')

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):
    sma = bt.talib.SMA(self.data.close,timeperiod=self.p.pslow)
    self.crossover = bt.ind.CrossOver(self.data.close, sma)  
    
    

def notify_trade(self, trade):
    if not trade.isclosed:
        return
    self.log('%.2f' %
             (trade.pnl))   
                      
def next(self):
    if not self.position:  
        if self.crossover > 0:  
            amount_to_invest = (self.p.order_percentage*self.broker.cash)
            self.size = math.floor(amount_to_invest/self.data.close)
            self.log(
                '%s, BUY, %.2f, %.2f, %.2f' %
                (self.params.ticker,
                 self.size,
                 self.data.close[0],
                cerebro.broker.getvalue()
                ))
            self.buy(size=self.size) 

    elif self.crossover < 0:  
            self.log(
                '%s, Sell, %.2f, %.2f, %.2f' %
                (self.params.ticker,
                 self.size,
                 self.data.close[0],
                 cerebro.broker.getvalue()
                 ))
            self.close() 

cerebro = bt.Cerebro()
feed = pd.read_csv('test.csv',index_col = 'Date',parse_dates = True)
data = bt.feeds.PandasData(dataname = feed)
data
cerebro.adddata(data)
cerebro.addstrategy(SmaCross)

print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.run()
cerebro.addwriter(bt.WriterFile, csv = True, out='your_strategy_results')
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.plot()

Hi, I'm new to python and backtrader. I'm trying to replicate a price and SMA crossover strategy and when I run the program I get the following result. Everything is fine but I want to print that pnl for every trade on the same row as Date, Ticker,...etc.

I printed Date, ticker, cost, size,... here by using :
self.log(
'%s, BUY, %.2f, %.2f, %.2f' %
(self.params.ticker,
self.size,
self.data.close[0],
cerebro.broker.getvalue()
))

and pnl using :

def notify_trade(self, trade):
    if not trade.isclosed:
        return
    self.log('%.2f' %
             (trade.pnl))