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OpenBacktesting
Open-source Python backtesting with a local visual workspace
Write Python strategies, run historical backtests locally, and inspect the trades behind each result. OpenBacktesting combines built-in indicators, execution costs, parameter optimization, and pandas reports. Add Studio to edit code, explore charts and drawdown, compare experiments, and reopen saved runs in your browser. Open source under Apache 2.0, with an independent Python core and an optional local visual workspace.
Hi Product Hunt! I'm sharing OpenBacktesting, an open-source Python framework for historical strategy research.
A headline return is only the start of a backtest. The useful questions are how orders filled, what costs were applied, where drawdown came from, and how results change with different parameters. OpenBacktesting brings those details into an inspectable local workflow.
You can:
• Write bar-by-bar Python strategies with built-in indicators and configurable inputs.
• Model fees and execution timing, then inspect orders, trades, equity, and risk statistics.
• Compare parameter experiments and save reports for later analysis.
• Add the optional Studio to edit local code, explore charts and logs, and reopen or share saved results.
The core works independently of Studio. The source is Apache 2.0 licensed, and the quickstart includes bundled data. Studio has a one-command macOS installer.
This release focuses on historical, single-asset research. What would make this workflow more useful for your strategy research? I'd love feedback on the API, result inspection, and Studio.
Get started: https://openbacktesting.com
Source: https://github.com/lucidcog/open...
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About OpenBacktesting on Product Hunt
“Open-source Python backtesting with a local visual workspace”
OpenBacktesting was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #161 on the daily leaderboard. Write Python strategies, run historical backtests locally, and inspect the trades behind each result. OpenBacktesting combines built-in indicators, execution costs, parameter optimization, and pandas reports. Add Studio to edit code, explore charts and drawdown, compare experiments, and reopen saved runs in your browser. Open source under Apache 2.0, with an independent Python core and an optional local visual workspace.
OpenBacktesting was featured in Open Source (69k followers), Investing (26.8k followers), Developer Tools (521.3k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 145.9k products, making this a competitive space to launch in.
Who hunted OpenBacktesting?
OpenBacktesting was hunted by Zane. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Zane