pybind11
nanobind
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pybind11 | nanobind | |
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42 | 11 | |
14,741 | 2,028 | |
1.7% | - | |
8.7 | 9.6 | |
6 days ago | 4 days ago | |
C++ | C++ | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pybind11
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Experience using crow as web server
I'm investigating using C++ to build a REST server, and would love to know of people's experiences with Crow-- or whether they would recommend something else as a "medium-level" abstraction C++ web server. As background, I started off experimenting with Python/FastAPI, which is great, but there is too much friction to translate from pybind11-exported C++ objects to the format that FastAPI expects, and, of course, there are inherent performance limitations using Python, which could impact scaling up if the project were to be successful.
- Swig – Connect C/C++ programs with high-level programming languages
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returning numpy arrays via pybind11
I have a C++ function computing a large tensor which I would like to return to Python as a NumPy array via pybind11.
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I created smooth_lines python module, great for drawing software
This is based on the Google Ink Stroke Modeler C++ library, and using pybind11 to make it available on python.
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Facial Landmark Detection with C++
pybind11 makes it easy to call C++ from Python if you want to mix.
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Python’s Multiprocessing Performance Problem
If you've never used Pybind before these pybind tests[1] and this repo[2] have good examples you can crib to get started (in addition to the docs). Once you handle passing/returning/creating the main data types (list, tuple, dict, set, numpy array) the first time, then it's mostly smooth sailing.
Pybind offers a lot of functionality, but core "good parts" I've found useful are (a) use a numpy array in Python and pass it to a C++ method to work on, (b) pass your python data structure to pybind and then do work on it in C++ (some copy overhead), and (c) Make a class/struct in C++ and expose it to Python (so no copying overhead and you can create nice cache-aware structs, etc.).
[1] https://github.com/pybind/pybind11/blob/master/tests/test_py...
- Making Python Web Application with C++ Backend
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Using pybind11 with minGW to cross compile pyhton module for Windows
I have a python module for which the logic is written in C++ and I use pybind11 to expose the objects and functions to Python.
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IPC communication between rust, c++, and python
Reading from Python requires a wrapper, using pybind11 this is fairly done.
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[ADVICE] Python to C++
Also I can highly recommend starting using C++ to augment your Python code, i.e. find the parts that are slow or undoable in Python and write those in C++ then expose them as Python functions. You can use https://github.com/pybind/pybind11 to call C++ code from Python.
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?
PyO3 - Rust bindings for the Python interpreter
awesome-cython - A curated list of awesome Cython resources. Just a draft for now.
Optional Argument in C++ - Named Optional Arguments in C++17
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.
setuptools-rust - Setuptools plugin for Rust support
matplotlibcpp17 - Alternative to matplotlibcpp with better syntax, based on pybind
sol2 - Sol3 (sol2 v3.0) - a C++ <-> Lua API wrapper with advanced features and top notch performance - is here, and it's great! Documentation:
epython - EPython is a typed-subset of the Python for extending the language new builtin types and methods
PEGTL - Parsing Expression Grammar Template Library
avendish - declarative polyamorous cross-system intermedia objects
sparsehash - C++ associative containers
warp - A Python framework for high performance GPU simulation and graphics