dear_bindings VS nanobind

> create a proper C binding to the C++ interface

That's the generally recommended way of exposing your C++ library to any kind of non-C++ code.

I'm not aware of any software which directly helps with that, unfortunately. You either do it manually or write a bunch of custom scripts. Here's a recent example of the latter, from Dear ImGui:

https://github.com/dearimgui/dear_bindings

Take a look at https://github.com/wjakob/nanobind

> More concretely, benchmarks show up to ~4× faster compile time, ~5× smaller binaries, and ~10× lower runtime overheads compared to pybind11.

People should not take that an endorsement of Swig.

Please use ctypes, cffi or https://github.com/wjakob/nanobind

Beazley himself is amazed that it (Swig) is still in use.

Nanobind made by the creator of PyBind11, it has a similar interface, but it takes leverage of C++17 and it aims to have more efficient bindings in space and speed.

I would recommend using NanoBind, the follow up of PyBind11 by the same author (Wensel Jakob), and move as much performance critical code to C or C++. https://github.com/wjakob/nanobind

If you really care about performance called from Python, consider something like NVIDIA Warp (Preview). Warp jits and runs your code on CUDA or CPU. Although Warp targets physics simulation, geometry processing, and procedural animation, it can be used for other tasks as well. https://github.com/NVIDIA/warp

Jax is another option, by Google, jitting and vectorizing code for TPU, GPU or CPU. https://github.com/google/jax