AttributeError: 'ItemCollection' object has no attribute 'sharpe_ratio'

[A Former User]

Following the example from Backtrader for Backtesting (Python) – A Complete Guide, I've had an error which I can't resolve in the following line:

sharpe = strategy.analyzers.sharpe_ratio.get_analysis()

That's line 119 from the following code:

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import datetime
import os.path
import sys
import math

import backtrader as bt

STARTING_CASH = 1700

class maxRiskSizer(bt.Sizer):
    params = (('risk', 0.95),)

    def __init__(self):
        if self.p.risk > 1 or self.p.risk < 0:
            raise ValueError('The risk parameter is a percentage which must be'
                'entered as a float. e.g. 0.5')

    def _getsizing(self, comminfo, cash, data, isbuy):
        position = self.broker.getposition(data)

        if not position:
            size = comminfo.getsize(data.close[0], cash * self.p.risk)
        else:
            size = position.size

        return size

class DegiroCommission(bt.CommInfoBase):
    params = (('per_share', 0.004), ('flat', 0.5),)

    def _getcommission(self, size, price, pseudoexec):
        return self.p.flat + size * self.p.per_share

class SMAcrossover(bt.Strategy):
    params = (('fast', 20), ('slow', 50),)

    def log(self, txt, dt=None):
        dt = dt or self.datas[0].datetime.date(0)
        #print(f'{dt.isoformat()} {txt}') # Comment this line when running optimization

    def __init__(self):
        self.dataclose = self.datas[0].close
        self.order = None

        fast_sma, slow_sma = bt.ind.SMA(period=self.p.fast), bt.ind.SMA(period=self.p.slow)
        self.crossover = bt.indicators.CrossOver(fast_sma, slow_sma)
        #self.signal_add(bt.SIGNAL_LONGSHORT, bt.ind.CrossOver(sma1, sma2))

    def notify_trade(self, trade):
        if not trade.isclosed:
            return

        self.log(f'GROSS {trade.pnl:.2f}, NET {trade.pnlcomm:.2f}')

    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            # An active Buy/Sell order has been submitted/accepted - 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(f'BUY EXECUTED, {order.executed.price:.2f}')
            elif order.issell():
                self.log(f'SELL EXECUTED, {order.executed.price:.2f}')
            self.bar_executed = len(self)

        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected')

        # Reset orders
        self.order = None

    def next(self):
        # Check for open orders
        if self.order:
            return

        if self.crossover > 0:
            self.log(f'BUY CREATE {self.dataclose[0]:.2f}')
            self.order = self.buy()
        elif self.crossover < 0:
            self.log(f'SELL CREATE {self.dataclose[0]:.2f}')
            self.order = self.sell()

if __name__ == '__main__':
    cerebro = bt.Cerebro(optreturn=False)
    cerebro.optstrategy(SMAcrossover, fast=range(5,7), slow=range(50,52))
    #cerebro.optstrategy(SMAcrossover, fast=range(5,55,5), slow=range(60,310,10))
    cerebro.broker.set_cash(STARTING_CASH)
    cerebro.broker.set_coc(True)

    modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
    datapath = os.path.join(modpath, 'datas/CPE.csv')
    data = bt.feeds.YahooFinanceCSVData(
        dataname=datapath,
        # Do not pass values before this date
        fromdate=datetime.datetime(1990, 10, 1),
        # Do not pass values after this date
        todate=datetime.datetime(2020, 10, 15),
        reverse=False
    )
    cerebro.adddata(data)

    cerebro.addsizer(maxRiskSizer)
    comminfo = DegiroCommission()
    cerebro.broker.addcommissioninfo(comminfo)

    optimized_runs = cerebro.run()

    final_results_list = []
    for run in optimized_runs:
        for strategy in run:
            PnL = round(strategy.broker.get_value() - STARTING_CASH,2)
            sharpe = strategy.analyzers.sharpe_ratio.get_analysis()
            final_results_list.append([strategy.params.fast, 
                strategy.params.slow, PnL, sharpe['sharperatio']])

    sort_by_sharpe = sorted(final_results_list, key=lambda x: x[3], 
                             reverse=True)
    for line in sort_by_sharpe[:5]:
        print(line)

[vladisld]

your code is missing adding the actual analyzer (it appears in the original article):

cerebro.addanalyzer(bt.analyzers.SharpeRatio, _name='sharpe_ratio')