serge-sans-paille

pythran

C++2013–2023

serge-sans-paille / pythran

pythran

Ahead of Time compiler for numeric kernels

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13Mentions

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2.1KGitHub stars

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What it is

Ahead of Time compiler for numeric kernels

GitHub

Where it is used

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year13 dated mentions

Observed mentions: 2013-08-12 15:27:22 UTC to 2023-03-13 21:29:07 UTC.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

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Period	Start (UTC)	End (exclusive, UTC)	Mentions	Submissions	Comments
2013	2013-01-01 00:00:00 UTC	2014-01-01 00:00:00 UTC	1	0	1
2014	2014-01-01 00:00:00 UTC	2015-01-01 00:00:00 UTC	1	1	0
2015	2015-01-01 00:00:00 UTC	2016-01-01 00:00:00 UTC	2	2	0
2016	2016-01-01 00:00:00 UTC	2017-01-01 00:00:00 UTC	3	0	3
2017	2017-01-01 00:00:00 UTC	2018-01-01 00:00:00 UTC	0	0	0
2018	2018-01-01 00:00:00 UTC	2019-01-01 00:00:00 UTC	1	0	1
2019	2019-01-01 00:00:00 UTC	2020-01-01 00:00:00 UTC	0	0	0
2020	2020-01-01 00:00:00 UTC	2021-01-01 00:00:00 UTC	0	0	0
2021	2021-01-01 00:00:00 UTC	2022-01-01 00:00:00 UTC	1	0	1
2022	2022-01-01 00:00:00 UTC	2023-01-01 00:00:00 UTC	3	0	3
2023	2023-01-01 00:00:00 UTC	2024-01-01 00:00:00 UTC	1	0	1

What Hacker News says

13 sources

peterhil·Mar 13, 2023

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

In How Python virtual environments work

tomthe·Sep 9, 2022

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.

In Accelerate Python code by importing Taichi

fwsgonzo·Jul 29, 2022

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.

In Omyyyy/pycom: A Python compiler, down to native code, using C++

cycomanic·May 17, 2022

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

In OpenAI Codex Python to C++ Code Generator

cycomanic·Jan 29, 2021

> Between pyodide, pyo3, rust-cpython, and rustpython, I think Pyo3 is the best way to drop in rust in a python project for a speed up, if that is your goal. Some of the demos show using python from rust, but to me the biggest feature is without a doubt compiling rust code to native python modules. I'm using it to speed up image manipulation backed by numpy arrays. > There’s a setuptools rust [0] extension package that can be used to hook the compilation of the rust into the wheel building or install from source. Maturin [1] seems to be regarded as the new and improved solution for this, but I found that it’s angled toward the using python from rust. > There’s also the rust numpy [2] package by the same org which is fantastic in that it lets you pass a numpy matrix to a native method written in rust and convert it to the rust equivalent d

Read the rest

ata structure, perform whatever transformation you want (in parallel using rayon [3]), and return the array. When building for release, I was seeing speed ups of 100x over numpy on the most matrix mathable function imaginable, and numpy is no joke. What sort of algorithm was that? Generally getting 100x speedup on vectorized code is highly unusual even using handcoded c++. So I suspect it was quite loop heavy? In those cases I have also seen very significant speed ups. I have been using pythran [1] for speeding up my python code. It generally achieves extremely good performance. I have blogged about it here [2] and recently a member used pythran to speed up some nbody benchmarks [3] which was used in an article to argue for using compiled languages. That said I find pyO3 quite exciting and have been contemplating to try it with some of my projects. [1] https://github.com/serge-sans-paille/pythran [2] https://jochenschroeder.com/blog/articles/DSP_with_Python2/ [3] https://github.com/paugier/nbabel

In PyO3: Rust Bindings for the Python Interpreter

accurrent·Apr 24, 2018

Link to the actual software: https://github.com/serge-sans-paille/pythran

In Pythran: Crossing the Python Frontier [pdf]

fuzzythinker·Oct 13, 2016

I'll say python isn't any more dynamic than ruby and groovy, and they have fairly stable and usable static compile target release/ports [1]. Python has a few [2] attempts, but none of them is close to stable or really useful. [1] https://crystal-lang.org/ http://groovy-lang.org/releasenotes/groovy-2.0.html [2] https://github.com/shedskin/shedskin https://github.com/codeblazer-io/blazescript https://github.com/serge-sans-paille/pythran

In Static types in Python

pmoriarty·Jul 3, 2016

You may be interested in an optimizing Python compiler called Pythran.[1][2] [1] - https://github.com/serge-sans-paille/pythran [2] - https://www.youtube.com/watch?v=Af8B30mXZ7E

In Why is Python slow

Joky·Jan 18, 2016

This seems to me to be very close to what Pythran [0] is doing (since 2011), except that Pythran includes some type inference and bridge with Python code. So view through that lens I'm not really seeing the novelty right now? [0]: http://github.com/serge-sans-paille/pythran/

In Show HN: Python to C++14 transpiler

maxmouchet·Nov 15, 2015Submission

Pythran: A Python subset to C++ compiler that takes advantage of SIMD

51 points · Open discussion

andrevoget·May 29, 2015Submission

Pythran – Python to C++ converter

2 points · Open discussion

pykello·Oct 23, 2014Submission

pythran: python to c++ converter

1 points · Open discussion

iskander·Aug 12, 2013

>cython, weave (C++ inline), numexpr (JIT for a limited set of NumPy functions), direct access to the BLAS (provided via a SciPy module), swig, f2py,.... I agree with your comment, I just want to add a few more Python performance options to the mix: * Numba (http://numba.pydata.org/) * Parakeet (https://github.com/iskandr/parakeet) * Pythran (https://github.com/serge-sans-paille/pythran)

In Julia and Python: a dynamic duo for scientific computing [video]