Learn how this real-time trading infrastructure was built from the ground up. Detailed walkthrough of architecture decisions, WebSocket streaming, and production deployment.
Read the blog postMore implementation guides and tutorials coming soon
A complete stack for streaming, storing, and visualizing market data in real-time
WebSocket ingestion builds 1-minute candles on the fly. Celery workers resample into 5m, 15m, 1h, 4h, and daily intervals with automatic reconnect logic.
Pre-built models for assets, candles, watchlists, and paper trades. Query rich data with Django ORM and extend with custom endpoints or notebooks.
Professional charting interface with real-time updates. Built with React and TradingView components for a familiar trading experience.
Complete Docker Compose stack with Django, Postgres, Redis, Celery, and Flower. Launch everything with one command and hot reload everywhere.
Create and manage watchlists directly in the UI. Store them in Django, sync with Alpaca, and keep everything ready for research or automation.
NX monorepo with unified commands, Vite hot reload, purposeful logging, and included tooling like Ruff, Black, Prettier, Pytest, and Vitest.
Production-grade stack that you can understand and extend
Django REST API, Channels WebSocket, Celery workers, Redis cache, and PostgreSQL database behind Docker Compose.
Vite + React with TradingView charting, watchlists, and real-time visuals powered by RTK Query and WebSocket connections.
Streams up to 30 symbols on Alpaca's free API key with resilience, resubscribe logic, and cached aggregates for optimal performance.
Professional trading interface with real-time data and powerful features
Create and organize watchlists with drag-and-drop interface and real-time price updates.
TradingView-powered charts with multiple timeframes and technical indicators.
Search and filter thousands of assets with instant results and detailed information.
Deploy in minutes with Docker Compose or Render. Shape it into your research lab or trading cockpit.