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backtrader

BackTesting Engine

With conditionsPyPI Software DevelopmentReleased Apr 2023327.9K downloads / moGPLv3+Pure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — backtrader-1.9.78.123-py2.py3-none-any.whl
v1.9.78.123 · released 2023-04-19

Yes, if you are building or testing trading strategies and can accept GPLv3+ licensing constraints. Backtrader is a mature, feature-rich backtesting engine with low install friction and no external dependencies (except for optional plotting). However, maintenance is dormant—the last release was April 2023—so expect no new features or timely bug fixes. It remains suitable for strategy development and testing, but evaluate whether its feature set meets your needs without ongoing updates.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Plotting requires matplotlib (minimum version 1.4.1).
  • Live trading with Interactive Brokers requires IbPy; Oanda integration requires oandapy.
  • Visual Chart support requires a fork of comtypes.

License · maintenance · safety

GPLv3+ (copyleft) — GPLv3+ copyleft license requires that any derivative work or distribution must also be open-source under a compatible license. Proprietary trading systems built on this package must be released under GPLv3+ or not distributed.

last release 2023-04-19 (1213 days) · last repo commit 2024-08-19 · 22,845 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 327,865 downloads/mo, #7,564 on PyPI

Verify before relying

from datetime import datetime
import backtrader as bt

class SmaCross(bt.SignalStrategy):
    def __init__(self):
        sma1, sma2 = bt.ind.SMA(period=10), bt.ind.SMA(period=30)
        crossover = bt.ind.CrossOver(sma1, sma2)
        self.signal_add(bt.SIGNAL_LONG, crossover)

cerebro = bt.Cerebro()
cerebro.addstrategy(SmaCross)
data0 = bt.feeds.YahooFinanceData(dataname='MSFT', fromdate=datetime(2011, 1, 1),
                                  todate=datetime(2012, 12, 31))
cerebro.adddata(data0)
cerebro.run()
cerebro.plot()
  • Whether Yahoo Finance data feeds continue to work reliably given the note about API changes in 2018.
  • Current compatibility with Python versions beyond 3.7, given classifiers list up to 3.7 only.
  • Whether pyfolio integration (noted as deprecated) is still functional or has been removed.
Same gist for agents: .md · .json

What it is and what it does

Backtrader is a self-contained backtesting and live trading platform for Python that lets you design and test trading strategies against historical market data before deploying them to live brokers. It supports multiple data sources (CSV, online feeds, pandas, blaze), multiple simultaneous data feeds and timeframes, and includes a built-in library of 122 technical indicators plus support for TA-Lib. The engine simulates realistic trading conditions with configurable commission schemes, slippage, volume filling strategies, and multiple order types (Market, Limit, Stop, StopTrail, OCO, bracket orders).

You can backtest strategies step-by-step or all at once, apply data filters (like Renko bricks or intraday simulation), resample and replay data, and analyze results with integrated analyzers for metrics like Sharpe Ratio and SQN. Live trading is supported with Interactive Brokers, Visual Chart, and Oanda. The platform includes plotting via matplotlib, automated position sizing, trading calendars, and schedulers. It runs on Python 3.2+ and also works with PyPy, though plotting is not available under PyPy.

Use it for

  • Backtest a moving-average crossover strategy against historical stock data before deploying it live.
  • Simulate intraday trading by breaking daily bars into smaller chunks and testing order fills at different price levels.
  • Compare multiple trading strategies across different timeframes and data feeds simultaneously to find the best performer.
  • Analyze trading performance with built-in metrics like Sharpe Ratio, total return, and drawdown to evaluate strategy robustness.
  • Live-trade a validated strategy through Interactive Brokers or Oanda with realistic commission and slippage modeling.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

With conditions

Yes, if you are building or testing trading strategies and can accept GPLv3+ licensing constraints.

Backtrader is a mature, feature-rich backtesting engine with low install friction and no external dependencies (except for optional plotting). However, maintenance is dormant—the last release was April 2023—so expect no new features or timely bug fixes. It remains suitable for strategy development and testing, but evaluate whether its feature set meets your needs without ongoing updates.

Install

backtrader on PyPI

Before you install

Low friction install with no runtime dependencies. Dormant maintenance status (last release 2023-04-19, last commit 2024-08-19) means bug fixes and feature updates are infrequent, though the repository remains active and is not archived.

Plotting requires matplotlib (minimum version 1.4.1). Live trading with Interactive Brokers requires IbPy; Oanda integration requires oandapy. Visual Chart support requires a fork of comtypes.

License in practice

GPLv3+ copyleft license requires that any derivative work or distribution must also be open-source under a compatible license. Proprietary trading systems built on this package must be released under GPLv3+ or not distributed.

Quickstart

from datetime import datetime
import backtrader as bt

class SmaCross(bt.SignalStrategy):
    def __init__(self):
        sma1, sma2 = bt.ind.SMA(period=10), bt.ind.SMA(period=30)
        crossover = bt.ind.CrossOver(sma1, sma2)
        self.signal_add(bt.SIGNAL_LONG, crossover)

cerebro = bt.Cerebro()
cerebro.addstrategy(SmaCross)
data0 = bt.feeds.YahooFinanceData(dataname='MSFT', fromdate=datetime(2011, 1, 1),
                                  todate=datetime(2012, 12, 31))
cerebro.adddata(data0)
cerebro.run()
cerebro.plot()

Verify before relying

  • Whether Yahoo Finance data feeds continue to work reliably given the note about API changes in 2018.
  • Current compatibility with Python versions beyond 3.7, given classifiers list up to 3.7 only.
  • Whether pyfolio integration (noted as deprecated) is still functional or has been removed.

Package facts

LicenseGPLv3+ copyleft
Python supportNot specified
Install frictionLow. Pure-Python wheel
Runtime dependenciesNone
MaintenanceDormant 1,213 days since the last release
Last repo commit
First released
Downloads327,865 / month, #7,564 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Financial and Insurance IndustryLicense :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)Operating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.2Programming Language :: Python :: 3.3Programming Language :: Python :: 3.4Programming Language :: Python :: 3.5Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Topic :: Office/Business :: FinancialTopic :: Software Development

Evidence: backtrader-1.9.78.123-py2.py3-none-any.whl

Tags

Capabilities
backtesting trading strategiesalgorithmic trading frameworklive trading enginetrading strategy simulatorfinancial data backtesterbroker integration tradingtechnical indicator framework
Topics
trading-backtestingfinancial-analysisalgorithmic-trading
PyPI keywords
tradingdevelopment

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