YololTranslator
nanobind
| YololTranslator | nanobind | |
|---|---|---|
| 1 | 11 | |
| 5 | 2,083 | |
| - | - | |
| 0.0 | 9.6 | |
| 8 months ago | 6 days ago | |
| CMake | C++ | |
| - | BSD 3-clause "New" or "Revised" License |
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YololTranslator
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Create Python bindings for my C++ code with PyBind11
Back in the day, when I was still a student, during the end of one of my internships, instead of writing my report I wrote a generator of spelling mistake for French named YololTranslator. You probably have no idea what it looks like, if you speak French, I invite you to visit the online version. Otherwise, imagine that at first it would write your instead of you're and stuff like that. (But it became way more powerfull)
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?
CPM.cmake - 📦 CMake's missing package manager. A small CMake script for setup-free, cross-platform, reproducible dependency management.
pybind11 - Seamless operability between C++11 and Python
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
awesome-cython - A curated list of awesome Cython resources. Just a draft for now.
flextool - C++ compile-time programming (serialization, reflection, code modification, enum to string, better enum, enum to json, extend or parse language, etc.)
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.
matplotlibcpp17 - Alternative to matplotlibcpp with better syntax, based on pybind
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
nvk - Vulkan API for JavaScript/TypeScript
oead - Library for recent Nintendo EAD formats in first-party games