exaloop

codon

Python2022–2026

exaloop / codon

codon

A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support

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20Distinct people

21Mentions

0Explicit recommenders

16.9KGitHub stars

REPOSITORY AT A GLANCE

What to know before exploring

What it is

A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

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Also in these discussions

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This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 12:45:45 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 year21 dated mentions

Observed mentions: 2022-12-08 15:05:45 UTC to 2026-06-23 15:09:36 UTC.

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

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

View mention counts and date ranges

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Period	Start (UTC)	End (exclusive, UTC)	Mentions	Submissions	Comments
2022	2022-01-01 00:00:00 UTC	2023-01-01 00:00:00 UTC	3	1	2
2023	2023-01-01 00:00:00 UTC	2024-01-01 00:00:00 UTC	8	0	8
2024	2024-01-01 00:00:00 UTC	2025-01-01 00:00:00 UTC	8	2	6
2025	2025-01-01 00:00:00 UTC	2026-01-01 00:00:00 UTC	1	0	1
2026 (partial)	2026-01-01 00:00:00 UTC	2027-01-01 00:00:00 UTC	1	0	1

What Hacker News says

8 sources

tekknolagi·May 9, 2023

Their fannkuch benchmark seems to be a bit dishonest. They claim an enormous perf delta on https://exaloop.io/benchmarks.html but fannkuch uses factorial a lot and they define factorial with a very small (n=20) table: https://github.com/exaloop/codon/blob/fb461371613049539654c1... Disclaimer: I've worked on several Python runtimes and compilers, but I'm not by any means out to get Codon. Just happened across this by accident while looking at their inline LLVM, which is neat.

In Codon: Python Compiler

nighthawk454·May 8, 2023

Repo for more details: https://github.com/exaloop/codon > What is Codon? > Codon is a high-performance Python compiler that compiles Python code to native machine code without any runtime overhead. Typical speedups over Python are on the order of 10-100x or more, on a single thread. Codon's performance is typically on par with (and sometimes better than) that of C/C++. Unlike Python, Codon supports native multithreading, which can lead to speedups many times higher still. Codon grew out of the Seq project. > What isn't Codon? > While Codon supports nearly all of Python's syntax, it is not a drop-in replacement, and large codebases might require modifications to be run through the Codon compiler. For example, some of Python's modules are not yet implemented within Codon, and a few of Python's dynamic features are disallowed. The Codon comp

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iler produces detailed error messages to help identify and resolve any incompatibilities. > Codon can be used within larger Python codebases via the @codon.jit decorator. Plain Python functions and libraries can also be called from within Codon via Python interoperability.

In Codon: Python Compiler

mfld·May 3, 2023

Another "Python with high-performance compiled builds" would be https://github.com/exaloop/codon.

In Mojo – a new programming language for AI developers

ginko·Mar 15, 2023

nit: 'Python-based' would imply to me that it's written in Python, but it looks like it's mostly C++ & LLVM: https://github.com/exaloop/codon/tree/develop/codon

In Python-based compiler achieves orders-of-magnitude speedups

illuminated·Mar 12, 2023

Source: https://github.com/exaloop/codon Docs: https://docs.exaloop.io/codon/

In Show HN: Codon: A Compiler for High-Performance Pythonic Applications and DSLs [pdf]

adenozine·Feb 1, 2023

Sure, if it happens, then I'll change my tune pretty quick. I don't stay plugged in beyond reading the changelog whenever a new version comes out, so I didn't know that bit about the keynote. I've noticed as well that the Julia community produces an absolutely extraordinary amount of conference talks/video content, I don't have the time for the finer details. I've also noticed a distinct and crucial lack of long-term vision for Julia from the co-founders. I've also read some dramatic (unverified) claims that I won't repeat here about one of them. Frankly, I think a better group of people could be assembled to steward the language and its ecosystem, but I don't see much chance of that happening. Julia exists in a weird little place where being terrible to read and maintain doesn't matter as long as it lives up to its promises of being very

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, very fast, in most of the applications it is used for. That's all well and good, but you don't build a solid foundation for a community to really depend on that tool for bedrock tasks. I've been unfortunate enough to read some .jl code in '22, and it was dreadful. I truly don't understand how multiple dispatch makes anybody's life easier, it's an absolute nightmare of unmaintainable code that calls any of dozens or hundreds of methods, the performance of the entire application essentially dependent on whether or not that type is stable and of course, there's no way to know that without reading the definition of the unknown method that gets called. Personally, I have my eyes peeled for github.com/exaloop/codon for higher performance stuff with Python. It's already an order of magnitude faster than pypy for most cases, and equally more usable for practical work than Julia, imo. Anyhow, when it's all said and done, there's a lot of computing being done and a lot of money changing hands and so forth. All's well that ends well, despite never really being done well. /shrug

In My Journey from R to Julia

yencabulator·Jan 26, 2023

By that argument, Python is "native" too then, with e.g. https://github.com/exaloop/codon The reason why it doesn't quite work out is that typically such a thing, AOT-compiled into native code, still carries with it its limitations and assumptions. It's technically native, but experiencing the native APIs only through a narrow peephole in the fence. If we let this meaning of "native" take over, we're gonna need another word for actually native things. Sometimes, that works well enough, though!

In Kernel-WASM: Sandboxed kernel mode WebAssembly runtime for Linux

okaleniuk·Jan 10, 2023

Good point! However, you bring in a common misconception I'm fighting with within my company for a long time. Python is not an interpreted language. There is no such thing as an "interpreted language", a language is just a set or rules and keywords. Everything you can fit into Backus–Naur form is already a language even if it doesn't have any implementation nor compiler neither interpreter. Just as a piece of evidence, there are interpreted C++ (http://www.artificialworlds.net/wiki/IGCC/IGCC) and AOT Python (https://github.com/exaloop/codon) implementations.

In Show HN: Socketify.py: Http/Https and WebSockets servers for PyPy3 and Python3