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exaloop
codon
Python2022–2026
exaloop / codon

codon

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

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

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

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.

024682022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 8 mentions; 0 submissions, 8 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 8 mentions; 2 submissions, 6 comments20242025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments. Incomplete calendar period.2026*

* 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
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC312
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC808
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC826
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC101
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC101

What Hacker News says

1 sources
nimic is a lightweight pure Python package that emulates Nim types and constructions, making it straightforward to transpile to Nim and compile AOT. Key principle: nimic code is valid Python that runs unmodified in CPython and also transpiles to equivalent Nim code. Because nimic code is just standard Python with type hints and ctypes shims, it is a fully valid CPython script, so you can use the Python REPL during development, drop a breakpoint in the middle of a heavy algorithmic loop and inspect the variables natively. Zero Lock-In: You don't need a special runtime engine. If the Nim compiler is not available, your script still runs (albeit slower than standard Python due to some emulation overhead) on any machine with Python installed. Seamless Distribution: You can use this to develop high-performance logic natively in Python, debug i
Read the rest
t with Python tooling, and then compile to a native executable or C-extension via Nim. Why Nim? Its syntax maps well to Python, it is rather clear how to emulate its constructions in Python, and its performance is comparable to C (as it compiles to C). Port of the "trace-of-radiance" Nim project to nimic can be found in "ndsl_raytracer" in my GitHub repo (dima-quant). With the compiled executable the render time for a single 512x288 scene dropped from many hours in Python to just 10 minutes on a single M1 CPU core. The repo also includes nimic ppm to mp4 converter. Similar projects: - Pyccel (https://github.com/pyccel/pyccel): Python extension language using accelerators - SPy (https://github.com/spylang/spy) is a variant of Python specifically designed to be statically compilable while retaining a lot of the "useful" dynamic parts of Python. - Codon (https://github.com/exaloop/codon) is a high-performance Python implementation that compiles to native machine code without any runtime overhead. It is still work in progress, e.g. there is no JIT and multiprocessing support yet, but now I'm not sure what functionality would be best to implement next. Any suggestions?
In Show HN: Nimic – Pure Python as a systems language with AOT compilation

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