Oh, finally got it working, can you add this in documentation, or can I ?

@backtrader Is it possible to check if a candlestick pattern has been observed today? How should i return yes/no value ?

@backtrader yes, the ohlc prices seem to be read wrong, everything instead of 30-40 range is read as eg. 883637.92 can this be tweaked to work as expected in YahooFinanceCSVData()?

@backtrader the dataset seems ok

Date,High,Low,Open,Close,Volume,Adj Close
2002-07-01,39.138099670410156,38.48149871826172,38.847999572753906,38.878501892089844,4031529.0,30.347339630126953
2002-07-02,40.11539840698242,38.54249954223633,38.72579956054688,39.214500427246094,14152322.0,30.60960960388184
2002-07-03,39.764198303222656,38.86320114135742,39.03120040893555,39.56570053100586,8456845.0,30.883745193481445
2002-07-04,40.833099365234375,39.30609893798828,39.87110137939453,39.535099029541016,12745157.0,30.859865188598636
2002-07-05,40.00849914550781,39.01589965820313,40.00849914550781,39.351898193359375,6445895.0,30.71685791015625
2002-07-08,40.039100646972656,38.40510177612305,39.73360061645508,38.618900299072266,8225227.0,30.144695281982425
2002-07-09,39.15340042114258,37.88589859008789,38.2677001953125,37.977500915527344,10865999.0,29.64403915405273
2002-07-10,38.5884017944336,37.412498474121094,38.14550018310547,37.58050155639648,8238269.0,29.33416175842285
2002-07-11,38.14550018310547,36.86280059814453,37.412498474121094,37.85540008544922,12711851.0,29.548738479614254
2002-07-12,38.55780029296875,37.45840072631836,38.328800201416016,37.74850082397461,7378410.0,29.465293884277344
2002-07-15,37.8400993347168,35.290000915527344,37.824798583984375,35.7327995300293,12436803.0,27.89190673828125
2002-07-16,37.71789932250977,35.03030014038086,35.48849868774414,37.18349838256836,20568293.0,29.024272918701172
2002-07-17,37.1682014465332,36.08399963378906,36.8932991027832,36.6338005065918,9150981.0,28.595195770263672
2002-07-18,37.38199996948242,35.64120101928711,37.25979995727539,36.114601135253906,18480280.0,28.189922332763672
2002-07-19,37.45840072631836,36.23669815063477,36.23669815063477,36.51160049438477,14291424.0,28.49980354309082
2002-07-22,35.97710037231445,32.770301818847656,35.80910110473633,33.45750045776367,13678966.0,26.11587142944336
2002-07-23,34.75550079345703,32.23590087890625,33.54909896850586,34.46540069580078,15143604.0,26.902606964111328
2002-07-24,33.900299072265625,32.2510986328125,33.900299072265625,33.106300354003906,10235892.0,25.841739654541016
2002-07-25,35.09140014648437,33.060501098632805,34.297401428222656,33.518600463867195,7693444.0,26.1635684967041
2002-07-26,32.800899505615234,31.18219947814941,32.678699493408196,31.65559959411621,10417471.0,24.70936584472656
2002-07-29,32.35800170898437,30.23539924621582,30.54080009460449,30.663000106811523,12310549.0,23.93457794189453

Using default matplotlib or bokeh neither of them is showing candlestick chart properly.

Here is the code below, found on quickstart guide

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])
from backtrader_plotting import Bokeh
from backtrader_plotting.schemes import Tradimo
# Import the backtrader platform
import backtrader as bt


# Create a Stratey
class TestStrategy(bt.Strategy):
    params = (
        ('maperiod', 15),
    )

    def log(self, txt, dt=None):
        ''' Logging function fot 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.dataclose = self.datas[0].close

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

        # Add a MovingAverageSimple indicator
        self.sma = bt.indicators.SimpleMovingAverage(
            self.datas[0], period=self.params.maperiod)

        # Indicators for the plotting show
        bt.indicators.ExponentialMovingAverage(self.datas[0], period=25)
        bt.indicators.WeightedMovingAverage(self.datas[0], period=25,
                                            subplot=True)
        bt.indicators.StochasticSlow(self.datas[0])
        bt.indicators.MACDHisto(self.datas[0])
        rsi = bt.indicators.RSI(self.datas[0])
        bt.indicators.SmoothedMovingAverage(rsi, period=10)
        bt.indicators.ATR(self.datas[0], plot=False)

    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.dataclose[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.dataclose[0] > self.sma[0]:

                # BUY, BUY, BUY!!! (with all possible default parameters)
                self.log('BUY CREATE, %.2f' % self.dataclose[0])

                # Keep track of the created order to avoid a 2nd order
                self.order = self.buy()

        else:

            if self.dataclose[0] < self.sma[0]:
                # SELL, SELL, SELL!!! (with all possible default parameters)
                self.log('SELL CREATE, %.2f' % self.dataclose[0])

                # Keep track of the created order to avoid a 2nd order
                self.order = self.sell()


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

    # Add a strategy
    cerebro.addstrategy(TestStrategy)

    # 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, 'ZEEL.NS.csv')

    # Create a Data Feed
    data = bt.feeds.YahooFinanceCSVData(
        dataname=datapath,
        # Do not pass values before this date
        fromdate=datetime.datetime(2002, 1, 1),
        # Do not pass values before this date
        todate=datetime.datetime(2003, 12, 31),
        # Do not pass values after this date
        reverse=False)

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

    # Set our desired cash start
    cerebro.broker.setcash(1000.0)

    # Add a FixedSize sizer according to the stake
    cerebro.addsizer(bt.sizers.FixedSize, stake=10)

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

    # 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())

    # Plot the result
    cerebro.plot(style='candlestick')
    #b = Bokeh(filename='chart.html',style='bar', plot_mode="single", scheme=Tradimo())
    #cerebro.plot(b)

Does this still work ?
I am facing this https://pastebin.com/whb5g6eq

@ab_trader Morning star returns -100 or 0 or 100
How can I print what is being returned ?
For eg. print(self.rsi) prints a number, but print(self.morningstar) is printing an object.

also is it possible to circle a pattern like this ?

import backtrader as bt
from datetime import datetime

class firstStrategy(bt.Strategy):
    params = (
        ('period',21),
        )

    def __init__(self):
        self.startcash = self.broker.getvalue()
        self.rsi = bt.indicators.RSI_SMA(self.data.close, period=self.params.period)
        self.morningstar = bt.talib.CDLMORNINGSTAR(self.data.open,self.data.high,self.data.low, self.data.close, penetration=0.3)

    def next(self):
        print(self.morningstar)
        if not self.position:
            if self.rsi < 30:
                self.buy(size=5)
            if self.morningstar == 100:
                self.buy(size=2)
        else:
            if self.rsi > 70:
                self.sell(size=5)

if __name__ == '__main__':
    #Variable for our starting cash
    startcash = 10000

    #Create an instance of cerebro
    cerebro = bt.Cerebro(optreturn=False)

    #Add our strategy
    cerebro.optstrategy(firstStrategy, period=range(14,16))

    #Get Apple data from Yahoo Finance.
    data = bt.feeds.YahooFinanceData(
        dataname='IBULHSGFIN.NS',
        fromdate = datetime(2019,1,1),
        todate = datetime(2020,1,1),
        buffered= True
        )


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

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

    # Run over everything
    opt_runs = cerebro.run()

    # Generate results list
    final_results_list = []
    for run in opt_runs:
        for strategy in run:
            value = round(strategy.broker.get_value(),2)
            PnL = round(value - startcash,2)
            period = strategy.params.period
            final_results_list.append([period,PnL])

    #Sort Results List
    by_period = sorted(final_results_list, key=lambda x: x[0])
    by_PnL = sorted(final_results_list, key=lambda x: x[1], reverse=True)

    #Print results
    print('Results: Ordered by period:')
    for result in by_period:
        print('Period: {}, PnL: {}'.format(result[0], result[1]))
    print('Results: Ordered by Profit:')
    for result in by_PnL:
        print('Period: {}, PnL: {}'.format(result[0], result[1]))

    cerebro.optstrategy(firstStrategy, period=by_PnL[0])
    
    cerebro.plot(style='candlestick')
 

I am not able to access self.morningstar as a value in next() function.

@ab_trader finally found a method using Bokeh looks pretty good, thanks to @vbs :-).

When there are multiple datafeeds like 10 or more visualizing is difficult, can we have a different UI like arrow keys to navigate, scroll plots, or a dropdown to select datafeed etc. Plotly seems to have that but unfortunately that is not supported yet.