binder
nanobind
| binder | nanobind | |
|---|---|---|
| 1 | 11 | |
| 304 | 2,049 | |
| 0.7% | - | |
| 7.4 | 9.6 | |
| about 1 month ago | 8 days ago | |
| C++ | C++ | |
| MIT License | BSD 3-clause "New" or "Revised" License |
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binder
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The future of Clang-based tooling
Have you seen https://github.com/RosettaCommons/binder ?
python aside, having gone down this rabbithole, and still not infrequently revisiting said rabbithole, I don't believe using *clang like this a winning strategy. Because of the number of corner cases there are in eg C++17, you will end reimplementing effectively all of the "middle-end" (the parts that lower to llvm) for your target language. At that point you're building bindings anymore but a whole-ass transpiler. Binder fails to be complete in the way.
My current theory is to try "synthesize" bindings from the llvm ir (a much smaller representational surface). Problems abound here too (ABI).
nanobind
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Progress on No-GIL CPython
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.
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Advanced Python Mastery – A Course by David Beazley
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.
- Swig – Connect C/C++ programs with high-level programming languages
- Nanobind: Tiny and efficient C++/Python bindings
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Create Python bindings for my C++ code with PyBind11
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.
- Nanobind – Seamless operability between C++17 and Python
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Cython Is 20
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
- GitHub - wjakob/nanobind: nanobind — Seamless operability between C++17 and Python
What are some alternatives?
ClangSharp - Clang bindings for .NET written in C#
pybind11 - Seamless operability between C++11 and Python
awesome-cython - A curated list of awesome Cython resources. Just a draft for now.
g3logPython - Python bindings for g3log
Nuitka - Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module.
godopy - [WIP] Python scripting for the Godot game engine
matplotlibcpp17 - Alternative to matplotlibcpp with better syntax, based on pybind
node-webrtc - node-webrtc is a Node.js Native Addon that provides bindings to WebRTC M87
epython - EPython is a typed-subset of the Python for extending the language new builtin types and methods
avendish - declarative polyamorous cross-system intermedia objects
warp - A Python framework for high performance GPU simulation and graphics