CheeseShop
pythran
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| CheeseShop | pythran | |
|---|---|---|
| 2 | 7 | |
| 1 | 1,965 | |
| - | - | |
| 3.8 | 8.1 | |
| 7 months ago | 4 days ago | |
| Rust | C++ | |
| MIT License | 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.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
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 It's a little outdated (uses PyO3 0.11.0 compared with the current 0.13.1) and doesn't show everything, but I think it's reasonably clear.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
pythran
- Codon: Python Compiler
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How Python virtual environments work
Numpy and Scipy are good reasons. Unfortunately Scipy does not even compile on FreeBSD lately, and I have opened three issues about it against Scipy and Pythran (and the fix was with xsimd).
https://github.com/serge-sans-paille/pythran/issues/2070
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S6: A standalone JIT compiler library for CPython
In someone lands here seeking a maintained compiler for Python, there's a lot, on top of my head:
- Pythran (https://pythran.readthedocs.io) (ahead of time compiler)
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Accelerate Python code 100x by import taichi as ti
Yes, I mean Pythran ( https://github.com/serge-sans-paille/pythran ). Thank you.
Was Nuitka better? Pythran is quite simple to install and use in Jupyter.
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Omyyyy/pycom: A Python compiler, down to native code, using C++
The only project that compares 1:1 is Pythran: https://github.com/serge-sans-paille/pythran
Pythran is fairly nice, and it really does work. I tried it last year and it compiles down to modifiable templated C++. I was able to use it to build Python for a highly specialized environment.
All the others compile down to dynamically linked binaries, and that just puts them in the "other" box.
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OpenAI Codex Python to C++ Code Generator
You might want to contact the author of Pythran [1], maybe something can be learned from what they do.
[1] https://github.com/serge-sans-paille/pythran/commits/master
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PyO3: Rust Bindings for the Python Interpreter
[1] https://github.com/serge-sans-paille/pythran
What are some alternatives?
ffi-overhead - comparing the c ffi (foreign function interface) overhead on various programming languages
rust-numpy - PyO3-based Rust bindings of the NumPy C-API
whatlang-pyo3 - Python Binding for Rust WhatLang, a language detection library
setuptools-rust - Setuptools plugin for Rust support
dtparse - Fast datetime parser for Python written in Rust
RustPython - A Python Interpreter written in Rust
codex_py2cpp - Converts python code into c++ by using OpenAI CODEX.
rayon - Rayon: A data parallelism library for Rust
shedskin - Shed Skin is a restricted-Python-to-C++ compiler. Read the introduction below to learn about the restrictions.
py2many - Transpiler of Python to many other languages
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.