Andrey Miguzov / ニュースフィード

This article introduces a lightweight OS-like helper for MQL5 that streamlines file and path operations using a Python-inspired interface. We implement getcwd, listdir, scandir with DirEntry, remove, rmdir, rename, mkdir, stat, and an os.path subset (exists, isfile, isdir, join, split, pardir). You will learn how to work consistently within the terminal Files/common sandbox and simplify everyday filesystem tasks.

Code and build Python-based trading robots just like MQL5 Expert Advisors (EAs). In this article, we develop a Python-based replica of the MetaTrader 5 Python package, providing methods that closely resemble those of MetaTrader 5 during simulation. This allows us to backtest Python EAs in a simplified environment, using an approach similar to developing and testing Expert Advisors in MQL5.

This article presents reusable MQL5 utilities for managing trailing and break-even stops. It covers fixed-point, moving average, ATR, Parabolic SAR, money-based, and time-periodic trailing, plus break-even by points and by money, with activation thresholds, step logic, reverse-move protection, and broker-level validation. Code examples and Bootstrap classes show how to integrate these helpers into Expert Advisors to standardize position control and reduce duplicate code.

This article presents a unified news model and a set of reusable MQL5 classes for working with the MetaTrader 5 Economic Calendar. You will retrieve, filter, and cache events by time, currency, country, and importance using a single interface across three providers: built-in calendar, CSV, and SQLite. The framework supports export/import, next/previous event lookup, and reliable strategy‑tester backtesting without changing trading logic.