
For a researcher, the performance of a Tester is a crucial indicator. It would be good to provide the memory consumption of your tester.
0.2 million ticks/second is, unfortunately, a strong limitation. Perhaps Numba will help improve your performance.
Please add sections (for different numbers of trading symbols):
benchmark_python vs benchmark_MT5tester, (single/optimization). RAM_python vs RAM_MT5tester, (single/optimization).
Thanks for the article!
- 2025.06.26
- www.mql5.com
For a researcher, the performance of a Tester is a crucial indicator. It would be good to provide the memory consumption of your tester.
0.2 million ticks/second is, unfortunately, a strong limitation. Perhaps Numba will help improve your performance.
Please add sections (for different numbers of trading symbols):
Thanks for the article!
Thanks for the suggestions, I will in the next few articles.
The goal was to implement first then improve later, a long way still to go😊
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Check out the new article: Python-MetaTrader 5 Strategy Tester (Part 04): Tester 101.
In this fascinating article, we build our very first trading robot in the simulator and run a strategy testing action that resembles how the MetaTrader 5 strategy tester works, then compare the outcome produced in a custom simulation against our favorite terminal.
In previous articles of this series, we laid the groundwork for building a MetaTrader 5–like strategy tester from scratch. With the core structure in place, several critical components are still missing in our project.
To this stage, we are yet to process ticks and bars sequentially, we lack mechanisms for monitoring open orders and the simulated trading account, and we do not have performance metrics such as profit and loss, drawdown, win rate, risk–reward ratios, and detailed trade statistics in the simulator.
This article aims to address these gaps and further improve our project.
Author: Omega J Msigwa