CheeseShop
pybind11
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CheeseShop | pybind11 | |
---|---|---|
2 | 42 | |
1 | 14,800 | |
- | 2.1% | |
3.8 | 8.6 | |
7 months ago | 6 days ago | |
Rust | C++ | |
MIT License | GNU General Public License v3.0 or later |
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CheeseShop
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Apache Spark UDFs in Rust
By comparison, PyO3 handles virtually all that boilerplate, so your Rust functions can accept and return many native Rust types and everything just works (for example). Or maybe I'm missing some fundamental difference with how JVM data are handled versus Python.
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PyO3: Rust Bindings for the Python Interpreter
At work, I'm using PyO3 for a project that churns through a lot of data (step 1) and does some pattern mining (step 2). This is the second generation of the project and is on-demand compared with the large, batch project in Spark that it is replacing. The Rust+Python project has really good performance, and using Rust for the core logic is such a joy compared with Scala or Python that a lot of other pieces are written in.
Learning PyO3, I cobbled together a sample project[0] to demonstrate how some functionality works. It's a little outdated (uses PyO3 0.11.0 compared with the current 0.13.1) and doesn't show everything, but I think it's reasonably clear.
One thing I noticed is that passing very large data from Rust and into Python's memory space is a bit of a challenge. I haven't quite grokked who owns what when and how memory gets correctly dropped, but I think the issues I've had are with the amount of RAM used at any moment and not with any memory leaks.
[0] https://github.com/aeshirey/CheeseShop
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.
What are some alternatives?
ffi-overhead - comparing the c ffi (foreign function interface) overhead on various programming languages
PyO3 - Rust bindings for the Python interpreter
whatlang-pyo3 - Python Binding for Rust WhatLang, a language detection library
nanobind - nanobind: tiny and efficient C++/Python bindings
dtparse - Fast datetime parser for Python written in Rust
Optional Argument in C++ - Named Optional Arguments in C++17
rust-numpy - PyO3-based Rust bindings of the NumPy C-API
setuptools-rust - Setuptools plugin for Rust support
pythran - Ahead of Time compiler for numeric kernels
sol2 - Sol3 (sol2 v3.0) - a C++ <-> Lua API wrapper with advanced features and top notch performance - is here, and it's great! Documentation:
rayon - Rayon: A data parallelism library for Rust
PEGTL - Parsing Expression Grammar Template Library