Discussing the article: "Building a Trade Analytics System (Part 1): Foundation and System Architecture"
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Check out the new article: Building a Trade Analytics System (Part 1): Foundation and System Architecture.
We design a simple external trade analytics pipeline for MetaTrader 5 and implement its backend in Python with Flask and SQLite. The article defines the architecture, data model, and versioned API, and shows how to configure the environment, initialize the database, and run the server locally. As a result, you get a clean base to capture closed-trade records from MetaTrader 5 and store them for later analysis.
Before we proceed, it is helpful to highlight a few basic requirements for following along with this series. This project brings together two environments: Python for the backend and MetaTrader 5 for the trading side. For that reason, a basic understanding of Python programming and general familiarity with MQL5 development will make the learning process smoother.
You do not need to be an expert in either. If you are comfortable reading simple Python code and understand how Expert Advisors work in MetaTrader 5, you will be able to follow along without difficulty. If some parts feel new, that is completely fine. The series is structured in a way that builds step-by-step, and each section focuses on practical implementation rather than theory. You are encouraged to move forward, experiment with the code, and learn through practice as the system gradually comes together.
Author: Chacha Ian Maroa