In algorithmic trading, the Python-vs-C++ debate is usually framed as flexibility versus speed — rapid strategy development on one side, ultra-low-latency execution on the other. But with C++26 reflection, that trade-off starts to disappear, making it possible to generate Python bindings automatically while keeping the core logic running at native C++ performance.

Stop Choosing: Get C++ Performance in Python Algos with C++26

by Richard Hickling

From the article:

The “religious war” between Python and C++ in algorithmic trading usually boils down to a single trade-off: Python is faster for getting ideas to market, while C++ is faster for getting orders into the book.

But why choose? With the advent of C++26 Reflection, you can now have the flexibility of a Python-based strategy without the performance penalty of slow loops.

Bring in C++ Rapidly: How Reflection Works

The biggest hurdle in hybrid trading systems has always been the “bridge.” Traditionally, if you wrote a complex pricer in C++, you had to manually write “boilerplate” code to tell Python how to talk to it. If you added a new function, you had to update the bridge. It was tedious and error-prone.

Reflection changes the game by allowing the code to “look in the mirror”. Instead of you manually describing your C++ functions to Python, the compiler does it for you. It programmatically inspects your classes and generates the bindings automatically.