MQL5 vs. Python for Algorithmic Trading: Speed, Execution, and API Integration
Comparing native MQL5 compiled execution against external Python MT5 sockets for high-frequency scalping, machine learning, and institutional risk management.
1. Execution Speed: Compiled C++ vs. Interpreted Sockets
MQL5 is a statically-typed, object-oriented language that compiles directly into native 64-bit machine binaries (.EX5). Execution speeds are sub-millisecond (0.1ms to 0.5ms). In contrast, Python scripts communicate with MT5 via inter-process IPC sockets, introducing 15ms to 50ms of communication latency per tick.
2. Where Python Excels: Machine Learning and Vectorized Backtesting
Python remains the undisputed king of historical data crunching, neural network training (PyTorch, TensorFlow), and portfolio optimization (Pandas, NumPy). The optimal workflow is to train models in Python, extract the mathematical weights, and execute them in MQL5.
3. Cloud Compilation and Zero-Setup Deployment
Running Python bots requires maintaining virtual environments, package dependencies, and background daemons. A compiled MQL5 .EX5 binary runs natively inside MT5 with zero external dependencies.
Leverage Mako Trading Lab's 200+ compiled MQL5 algorithms to get the absolute lowest latency execution without writing thousands of lines of low-level C++ code.