GlowBack

High‑performance quantitative backtesting platform built in Rust with Python bindings and a Streamlit UI.

Highlights

• Event‑driven simulation engine with realistic execution models
• Data ingestion (CSV, Alpha Vantage, sample data)
• Arrow/Parquet storage with SQLite metadata catalog
• Strategy library (6 built‑in strategies, including an experimental covered-call workflow; the quickstart smoke path exercises four of them)
• Python bindings with async support
• Streamlit UI for strategy development and analysis

Quickstart

git clone https://github.com/LatencyTDH/GlowBack.git
cd GlowBack
./scripts/quickstart.sh

cd ui
python setup.py
# Opens http://localhost:8501

The quickstart script is exercised in CI and validates the expected success markers from the basic usage example.

Where to go next

• Getting Started for the 5-minute first run and exact success markers
• Assumptions & Limitations for the current product boundaries
• Concepts for data model and execution details
• Tutorials for common workflows
• API Reference for bindings and crate docs