Running Backtrader

Backtrader_Run.py

import backtrader as bt
import yfinance as yf

def get_yf_data(ticker="BTC-USD", interval="1d", period="max", **kwargs): 
    """
    A function that returns a Backtrader data feed using Yahoo Finance API
    
    Parameters
    --------------------------------------
    ticker - Yahoo Finance Ticket to fetch
    interval - Interval defined by yfinance docs
    period - Time period of return as defined by yfinance
    kwargs - Further key word arguments for yfinance history interaction
    """
    
    ticker_yf = yf.Ticker(ticker)
    hist = ticker_yf.history(period=period, interval=interval, kwargs)
    hist.ffill(inplace=True)
    return bt.feeds.PandasData(dataname = hist)

class ComissionInfo(bt.CommissionInfo):
    """
    Commission Object mainly used to define getsize
    getsize allows for the buying or selling of fractional shares
    """
    
    params = (
        ("commission", 0.00075),
        ("margin", None),
        ("commtype", None)
    )

    def getsize(self, price, cash):
        """Returns fractional size for cash operation @price"""
        return self.p.leverage * (cash / price)

class CashMarket(bt.analyzers.Analyzer):
    """
    Analyzer returning a dict of account value
    """
    def create_analysis(self):
        self.rets = {}

    def notify_cashvalue(self, cash, value):
        total = cash + value
        self.rets[self.strategy.datetime.datetime()] = math.floor(total)

    def get_analysis(self):
        return self.rets
      
data = get_yf_data()
cerebro = bt.Cerebro()
# Add Data and Strategy to the bt instance
cerebro.adddata(data)
cerebro.addstrategy(DollarCostAverage)
# Add TimeReturn and our own Cash Market Analyser, cerbero returns these as a list
# results.analyzer[]
ankwargs = dict(timeframe=bt.TimeFrame.Years)
cerebro.addanalyzer(bt.analyzers.TimeReturn, fund=True, **ankwargs)
cerebro.addanalyzer(CashMarket)
## Add Comm for fractional shares
cerebro.broker.addcommissioninfo(ComissionInfo())
# Set our starting cash on the account
cerebro.broker.set_cash(1000)
results = cerebro.run()
cerebro.plot(iplot=False, style='candlestick')
return results