Does it require the MetaTrader 5 GUI to be open?

No, it supports headless execution via Wine, allowing for automated data exports and indicator validation without initializing the MetaTrader 5 graphical interface.

Is this compatible with macOS or Linux?

Yes, it is pre-configured for Wine and CrossOver environments, specifically addressing the common challenges of running MetaTrader 5 Python integrations on non-Windows systems.

How does the skill ensure indicator accuracy during translation?

It employs a validation-driven workflow that gates work based on a 0.999 correlation requirement between the original MQL5 reference data and the new Python implementation.

Can this skill access custom MQL5 indicators?

Due to MT5 API restrictions, it can only export OHLCV and built-in indicators directly, but it is specifically designed to translate custom MQL5 source code into functional Python equivalents.

MQL5-Python Workspace

Name: MQL5-Python Workspace
Author: terrylica

byterrylica

•

Data Science & ML

Synchronizes MetaTrader 5 and Python environments to automate market data exports and translate MQL5 indicators into validated Python code.

About

This skill establishes a high-fidelity bridge between MetaTrader 5 and Python, enabling developers to translate complex MQL5 indicators into Python scripts with autonomous validation. It features a headless data export workflow via Wine, allowing for cold-start market data retrieval without GUI interaction. By enforcing a 0.999 correlation threshold, it ensures that Python-based recreations of financial indicators match their MQL5 references perfectly, streamlining the path from MetaTrader development to data-driven Python analysis and algorithmic trading research.

Key Features

Automated MQL5-to-Python indicator translation logic
Headless market data export using Wine and MetaTrader 5 API
Validation engine enforcing 0.999+ correlation accuracy
5 GitHub stars
Autonomous self-correction based on documented failure patterns
Support for OHLCV data and built-in technical indicators

Use Cases

Automating bulk export of historical market data for machine learning models
Validating Python indicator accuracy against MetaTrader 5 reference values
Translating proprietary MQL5 indicators into Python for algorithmic trading

About

Key Features

Automated MQL5-to-Python indicator translation logic
Headless market data export using Wine and MetaTrader 5 API
Validation engine enforcing 0.999+ correlation accuracy
5 GitHub stars
Autonomous self-correction based on documented failure patterns
Support for OHLCV data and built-in technical indicators

Use Cases

Automating bulk export of historical market data for machine learning models
Validating Python indicator accuracy against MetaTrader 5 reference values
Translating proprietary MQL5 indicators into Python for algorithmic trading