What does it do?
Backtrader lets you describe a trading idea in code, buy when the price crosses above its 50-day average, sell when it drops below, and then rewinds through years of historical price data to show exactly how that idea would have performed, trade by trade. It tracks profit, loss, drawdowns, and dozens of performance metrics automatically, and can plot results as a chart with buy and sell markers on the price history. It supports multiple assets and timeframes at once, and can plug into live broker connections once you’re ready to move from testing to real trading. Essentially, it’s a rehearsal stage for financial decisions you haven’t made yet.
See it in action
This defines a simple trading rule that buys a stock when its short-term price trend crosses above its long-term trend, and sells when it crosses back below.
import backtrader as bt
class SmaCross(bt.Strategy):
def __init__(self):
sma1 = bt.ind.SMA(period=10)
sma2 = bt.ind.SMA(period=30)
self.crossover = bt.ind.CrossOver(sma1, sma2)
def next(self):
if self.crossover > 0:
self.buy()
elif self.crossover < 0:
self.sell()Why would a non-developer care?
Testing a trading idea on real money first is how people lose real money; testing it against history first, cheaply and repeatedly, is how professional strategies actually get built. It brings that kind of rigor within reach of anyone willing to learn a bit of Python, not just quant funds with in-house infrastructure.
Real-world examples
It’s one of the most commonly referenced backtesting engines in algorithmic-trading tutorials and forums, popular precisely because it’s free, well-documented, and doesn’t require a brokerage account to start experimenting. Plenty of hobbyist trading bots on GitHub use it as their testing backbone before ever touching a live account.
Who uses it
Retail algorithmic traders and quant hobbyists validating a trading strategy against history before risking real capital.
How it compares to alternatives
It’s a close rival to zipline-reloaded, the revived backtester originally built for the Quantopian platform, with backtrader generally seen as more actively maintained and beginner-accessible while zipline appeals to those wanting closer fidelity to the old Quantopian workflow.