Is backtrader still maintained? Status and four maintained alternatives
Published 11 Oct 2026 · repository data refreshes daily
Short answer. backtrader still installs and still runs, and plenty of people use it. But its repository shows no activity since 19 Aug 2024, so nobody is fixing bugs or keeping up with new releases of its dependencies. It is fine for learning and for strategies you already run. For a new project, pick something that is still being maintained.
What we can actually see
We snapshot every repository in this directory once a day. For backtrader the picture is simple: 23.4k GitHub stars, which puts it among the most-starred backtesting libraries in this directory, and a history that goes quiet after 19 Aug 2024. The repository is not archived, so the author could come back to it, but there has been no sign of that.
The README still describes what made it popular: an event-driven engine, data feeds from CSV files, online sources or pandas, and live trading through Interactive Brokers, Oanda and Visual Chart. The same README also shows its age. The Interactive Brokers connection depends on the old IbPy package, and the Oanda integration is described as REST only.
What a quiet repository costs you
- Dependency drift. Python, pandas, NumPy and matplotlib keep changing. When a new release breaks something, the fix has to come from you or from a fork.
- Broker connections decay first. Backtesting on your own data keeps working for years. Live connections depend on third-party APIs that change without asking.
- Open issues stay open. You can still learn a lot from the existing documentation and community posts, but you should not expect answers upstream.
- The licence is GPL-3.0. That has not changed, and it matters if you plan to ship software built on it.
Four alternatives that are still being worked on
| Tool | GitHub stars | Last activity | Licence | Style | Scope |
|---|---|---|---|---|---|
| backtrader | 23.4k | 19 Aug 2024 | GPL-3.0 | Event-driven | Backtesting and live trading (Interactive Brokers, Oanda, Visual Chart) |
| vectorbt | 9.3k | 9 Oct 2026 | Apache 2.0 with Commons Clause | Vectorized | Backtesting and strategy research |
| zipline-reloaded | 2k | 10 Oct 2026 | Apache-2.0 | Event-driven | Backtesting |
| nautilus_trader | 29.8k | 11 Oct 2026 | LGPL-3.0 | Event-driven, Rust core | Backtesting and live trading with the same code |
| PyBroker | 3.6k | 5 Oct 2026 | Apache 2.0 with Commons Clause | Vectorized engine, rule and model based | Backtesting, machine-learning strategies |
Stars and last activity (the most recent push GitHub reports for the repository) come from our daily snapshots and can lag by a few days. Licence and scope were checked against each repository on 11 Oct 2026.
vectorbt: when you want to test thousands of variations
vectorbt takes the opposite approach to backtrader. Instead of stepping through bars one strategy at a time, it packs many parameter combinations into NumPy arrays and runs them together, with Numba and an optional Rust engine doing the heavy lifting. That makes it a good fit for parameter sweeps and research. Two things to know before you commit: the licence is Apache 2.0 with a Commons Clause, which lets you use it for free but not sell a product that is mainly this software, and several features such as limit orders, leverage and parallelization live in the separate paid PRO edition.
zipline-reloaded: the closest thing to a classic event-driven engine
The original zipline was Quantopian's engine, and Quantopian closed in late 2020. Its repository shows no activity since 13 Feb 2024. zipline-reloaded is the fork that Stefan Jansen keeps up to date for readers of his machine-learning trading book and the wider community. It supports Python 3.9 and later and has been updated for pandas 2 and NumPy 2. If you like writing strategies as plain Python event handlers, this is the smallest mental jump from backtrader. It is also the slowest-moving of the four: when we checked, the latest release was 3.1.1 from July 2025, with occasional commits since. Its README presents it as a backtesting library, so plan on a separate route to live trading.
NautilusTrader: when backtest and live must be the same code
NautilusTrader has a Rust core with a Python layer for strategy logic, and its central promise is that the same strategy code runs in a backtest and in live trading. It ships adapters for Interactive Brokers and for crypto venues such as OKX, Kraken and Hyperliquid. It is the most demanding option here: the concepts are closer to a production trading system than to a research notebook. The licence is LGPL-3.0.
PyBroker: when your strategy is a model
PyBroker is built around machine-learning strategies. It offers walk-forward analysis, bootstrapped performance metrics, and data loaders for Alpaca, Yahoo Finance and AKShare, on top of a NumPy and Numba engine. Like vectorbt, it uses Apache 2.0 with a Commons Clause.
One that looks maintained but is not
QSTrader often appears in lists like this one, and its README still says it is under active development. The repository tells a different story: no activity since 30 Jun 2024. This is the main reason to check activity dates rather than descriptions.
How to choose
- You are learning backtesting. backtrader is still a reasonable teacher, because there is so much written about it. Just do not build your long-term stack on it.
- You research many strategy variations. vectorbt.
- You want event-driven backtests in familiar Python. zipline-reloaded.
- You intend to trade live with the code you backtest. NautilusTrader.
- Your signals come from trained models. PyBroker.
A listing here is not a recommendation to trade, and a backtest is not evidence that a strategy will make money. See also this week's trending tools.