Global Moderators

@mtucker502 I believe your question is well documented here. Use compression.

We would like to help you but your question is not very informative. Please Include all of your code. Please also include the full log print out that has the error. Also please follow the instructions at the very top of this page for using three back ticks to wrap around your code.

For example:

put code here.

@t3chap Here is a working example: Make sure you have install openpyxl

import backtrader as bt
import pandas as pd



class CashMarket(bt.analyzers.Analyzer):
    """
    Analyzer returning cash and market values
    """

    def create_analysis(self):
        self.rets = {}
        self.vals = 0.0

    def notify_cashvalue(self, cash, value):
        self.vals = (
            self.strategy.datetime.datetime().strftime("%Y-%m-%d"),
            cash,
            value,
        )
        self.rets[len(self)] = self.vals

    def get_analysis(self):
        return self.rets


class Strategy(bt.Strategy):
    def __init__(self):
        self.rsi = bt.ind.RSI(period=14)

    def next(self):
        if not self.position:
            if self.rsi <= 35:
                self.buy()
        elif self.rsi >= 65:
            self.close()


if __name__ == "__main__":

    cerebro = bt.Cerebro()

    data = bt.feeds.GenericCSVData(
        dataname="data/2006-day-001.txt",
        dtformat=("%Y-%m-%d"),
        timeframe=bt.TimeFrame.Days,
        compression=1,
    )
    cerebro.adddata(data)

    cerebro.addstrategy(Strategy)

    cerebro.addanalyzer(CashMarket, _name="cash_market")

    # Execute
    results = cerebro.run()

    # Dictionary
    dictionary = results[0].analyzers.getbyname("cash_market").get_analysis()
    df = pd.DataFrame(dictionary).T
    df.columns = ["Date", "Cash", "Value"]
    df.to_excel("Your file name here.xlsx", engine="openpyxl", index=False)

@goldcar Did you get a chance to look at backfilling?

@vypy1 Your logs are not informative enough. Try using some or all of the following and then you'll get better data as to what's happening with your trades.

   def notify_order(self, order):
        """ Triggered upon changes to orders. """

        # Suppress notification if it is just a submitted order.
        if order.status == order.Submitted:
            return

        # Print out the date, security name, order number and status.
        dt, dn = self.datetime.date(), order.data._name
        type = "Buy" if order.isbuy() else "Sell"
        self.log(
            f"{order.data._name:<6} Order: {order.ref:3d}\tType: {type:<5}\tStatus"
            f" {order.getstatusname():<8} \t"
            f"Size: {order.created.size:9.4f} Price: {order.created.price:9.4f} "
            f"Position: {self.getposition(order.data).size}"
        )
        if order.status == order.Margin:
            return

        # Check if an order has been completed
        if order.status in [order.Completed]:
            self.log(
                f"{order.data._name:<6} {('BUY' if order.isbuy() else 'SELL'):<5} "
                # f"EXECUTED for: {dn} "
                f"Price: {order.executed.price:6.2f} "
                f"Cost: {order.executed.value:6.2f} "
                f"Comm: {order.executed.comm:4.2f} "
                f"Size: {order.created.size:9.4f} "
            )

@jplaza This is a bit hacky, but you could also load the data in the __init__ of your strategy. It's not highly recommended, and you would need to be diligent about your dates and forward looking bias.

@vypy1 Hi can you include your logs showing the trades? Thanks.

@jplaza Seems like backtrader is expecting floats:

he code expects all fields to be in place and be convertible to floats, except for the datetime which has a fixed YYYY-MM-DD format and can be parsed without using datetime.datetime.strptime.

I tried myself running text into backtrader and backtrader is definitely expecting floats (or convertable to floats) values.

I cannot see your data, but I wonder if there's a way to categorize your data into numbers and preprosses it before loading?

@willt Can you please elaborate on your error and start a new thread? Thanks.