When building quant systems, trading dashboards, or live monitoring tools, stable, low-latency, reproducible 1‑minute candlestick data is the foundation. In my experience, relying on third-party K-line APIs or HTTP polling leads to consistent issues with latency, rate limits, and data consistency. A far more reliable approach is to consume raw tick data via WebSocket and generate candles locally. This article walks through a complete, production-ready implementation: real-time data access, tick aggregation, and data storage. Use Case & Core Requirements For financial applications, minute-level data needs three key properties: Low latency: Real-time updates for live signals High stability: No data loss, no disconnections, no throttling Consistency: Identical logic for backtesting and live trading Traditional methods fail at all three. A WebSocket + tick aggregation architecture solves them cleanly.…