Discussing the article: "Building a Trade Analytics System (Part 4): Summary Metrics and Dashboard"
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Check out the new article: Building a Trade Analytics System (Part 4): Summary Metrics and Dashboard.
This article extends the existing Flask backend to compute performance analytics from stored MetaTrader 5 closed trades and deliver them as both JSON and a simple web view. It calculates total trades, total profit, win rate, average profit, and trade duration metrics, returning JSON at /api/v1/analytics/summary and rendering a dashboard at /api/v1. The result provides a quick, consistent way to review trading performance from persisted SQLite records.
In this series, we set out to build a trade analytics system for MetaTrader 5. We have already established the data capture, transmission, and storage layers. This final part focuses on using that stored data to compute meaningful performance metrics and to present them in a simple, accessible way.
The goal here is practical. We will extend the existing analytics endpoint to calculate summary statistics from the stored trades and return them as JSON. In addition, we will update the API root to render a minimal web page that displays these statistics for quick inspection in a browser. This completes the system by connecting stored data to a clear and usable representation.
Author: Chacha Ian Maroa