// who it's for
dgbit is for quantitative traders developing new strategies and developers building trading automation on Bybit. If you want a "buy this dip" button, look elsewhere — this is infrastructure.
Quant developers
You already write strategies in Python and want a simulator you can trust. Because dgbit targets Bybit directly, the fee model, kline boundaries, and order assumptions map one-to-one to live behavior — so a promising backtest is a promising signal, not a modeling artifact.
Run your first backtest →Trading automation engineers
You deploy to production and need more than a single-process script. dgbit ships a FastAPI REST API, an NNG service bus across data/backtest/strategy workers, a WebSocket event stream, and docker-compose orchestration — so the operational shape is there from day one.
See the architecture →Researchers building on Bybit
You want the data fetcher, position tracking, and risk handling ready for Bybit rather than abstracted across ten venues. dgbit's deliberate single-exchange scope means fewer abstractions to fight and more precision where it matters for your research.
See all features →Teams weighing frameworks
If you trade only on Bybit and value a backtester whose behavior you can map exactly to live, dgbit's scope is a feature, not a limitation. If you need many exchanges or market-making templates, the honest comparisons will point you elsewhere.
Compare vs Freqtrade & Hummingbot →Clone the repo, run the first backtest, and see whether dgbit matches how you think about markets.