Hi there,
While backtesting works well for me, I run into problems with optimizing with respect to sharpe ratio when using my below code, see the below output.
It seems that the final_results_list does get only NoneType values for the Sharpe Rations. Any idea what went wrong? Thanks!

Output:

File "C:\Users\User\Desktop\Python for Finance\MACD_Strategy\BackTrader_MACD_Example\btmain.py", line 174, in <module>
  sort_by_sharpe = sorted(final_results_list, key=lambda x: x[3], reverse=True)

TypeError: '<' not supported between instances of 'NoneType' and 'NoneType'

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 the backtrader platform
import backtrader as bt
import backtrader.indicators as btind

import pandas as pd
import numpy as np

from strategies import *

###--------------------------------
###--------------------------------
###--------------------------------
### FOR OPTIMIZATION

#Instantiate Cerebro engine
cerebro = bt.Cerebro(optreturn=False, optdatas=True)

modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
datapath = os.path.join(modpath, 'C:/Users/User/Desktop/Python for Finance/MACD_Strategy/BackTrader_MACD_Example/ohlc.csv')

data = bt.feeds.GenericCSVData(
    dataname=datapath,
    #add or remove do in-sample and out-of-sample tests (i.e. optimize in one and backtest in next years)
    #settings for in-sample optimization
    #fromdate=datetime.datetime(2020, 5, 4, 0, 0, 0),
    #todate=datetime.datetime(2020, 6, 4, 0, 0, 0),
    #settings for out-of-sample backtest
    #fromdate=datetime.datetime(2020, 6, 4, 0, 0, 0),
    #todate=datetime.datetime(2020, 6, 23, 0, 0, 0),  
    nullvalue=0.0,
    dtformat=('%Y-%m-%d %H:%M:%S'),
    datetime=0,
    time=-1,
    high=2,
    low=3,
    open=1,
    close=4,
    volume=5,
    openinterest=-1,
    timeframe=bt.TimeFrame.Minutes)

cerebro.adddata(data)

#Add strategy to Cerebro
cerebro.addanalyzer(bt.analyzers.SharpeRatio, _name='sharpe_ratio')
cerebro.optstrategy(MAcrossover, pfast=range(5, 20), pslow=range(50, 100)) 

#Default position size / 1 = 1 underlying share
cerebro.addsizer(bt.sizers.SizerFix, stake=1)

if __name__ == '__main__':
    optimized_runs = cerebro.run()

    final_results_list = []
    for run in optimized_runs:
        for strategy in run:
            PnL = round(strategy.broker.get_value() - 10000,2)
            sharpe = strategy.analyzers.sharpe_ratio.get_analysis()
            final_results_list.append([strategy.params.pfast, 
                strategy.params.pslow, 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)

Strategy:

class MAcrossover(bt.Strategy): 
    #Moving average parameters
    params = (('pfast',20),('pslow',50),)
    
    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.datetime(0)
        #print('%s, %s' % (dt.isoformat(), txt))
        print("%s, %s" % (dt, txt))
        
    def __init__(self):     
        self.dataclose = self.datas[0].close     
        # Order variable will contain ongoing order details/status
        self.order = None     
        # Instantiate moving averages     
        self.slow_sma = bt.indicators.MovingAverageSimple(self.datas[0],                                       
                        period=self.params.pslow)     
        self.fast_sma = bt.indicators.MovingAverageSimple(self.datas[0], 
                        period=self.params.pfast)
    
    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            #Active Buy/Sell order 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('BUY EXECUTED, %.2f' % order.executed.price)         
            elif order.issell():             
                self.log('SELL EXECUTED, %.2f' % order.executed.price)
                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):
        if self.order:
            return
        #Check if we are in the market
        if not self.position:
        #We are not in the market, look for a signal to OPEN trades
            #If the 20 SMA is above the 50 SMA
            if self.fast_sma[0] > self.slow_sma[0] and self.fast_sma[-1] < self.slow_sma[-1]:
                 self.log('BUY CREATE, %.2f' % self.dataclose[0])
                 #Keep track of the created order to avoid a 2nd order
                 self.order = self.buy()
            #Otherwise if the 20 SMA is below the 50 SMA
            elif self.fast_sma[0] < self.slow_sma[0] and self.fast_sma[-1] > self.slow_sma[-1]:
                self.log('SELL CREATE, %.2f' % self.dataclose[0])
                #Keep track of the created order to avoid a 2nd order
                self.order = self.sell()
        else:
            # We are already in the market, look for a signal to CLOSE trades
            if len(self) >= (self.bar_executed + 5):
               self.log('CLOSE CREATE, %.2f' % self.dataclose[0])
               self.order = self.close()