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faster-cpython
ideas
OPEN SOURCE2021–2025
faster-cpython / ideas

ideas

Discover this repository through its Hacker News conversations.

33Distinct people
44Mentions
0Explicit recommenders
1.7KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A public description has not been verified.

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

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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, 8:59:20 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 year44 dated mentions

Observed mentions: 2021-05-13 10:05:48 UTC to 2025-12-25 16:28:05 UTC.

0510152021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 10 mentions; 5 submissions, 5 comments20212022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 16 mentions; 6 submissions, 10 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 9 mentions; 2 submissions, 7 comments20232024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 5 mentions; 3 submissions, 2 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 4 mentions; 2 submissions, 2 comments2025

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
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC1055
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC16610
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC927
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC532
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC422

From the project README

An excerpt from the repository, fetched Nov 13, 2026.

Read the project’s introduction
Faster CPython Ideas Discussion and work tracker for Faster CPython project. New ideas should be created as new issues. It is ok if the idea is not fully formed -- we treat them as discussions to arrive at something actionable. (We had previously used discussions for this, but that is now deprecated). The CPython issue tracker should be used for actual work-in-progress. Some links to presentations and other preliminary documentation: Guido's slides at the 2021 Python Language Summit Mark's slides explaining Tiers of Execution PEP 659 Published Results Benchmarking and pystats results are published to the benchmarking-public repo.
Read the full README on GitHub

What Hacker News says

10 sources
> My personal view is that the world has largely moved on from dynamically typed languages for anything non-trivial or that isn't essentially plumbing. For good reason. Of course people will bring up Javascript but it has a captive market as being the only thing that'll universally run code in a browser and the likes of TypeScript can ease that burden anyway. This is not correct. There is a lot of data analysis code in the research and scientific community written in python. A lot of PyCon attendees and speakers come from these communities. Oftentimes, it’s not easy to write code to perform a task entirely in numpy, and then you incur massive slowdowns (often 20-100x). This is a common and contemporary problem in the python ecosystem. GVR initially didn’t think that python needed to be faster either, but recently changed his mind. You can
Read the rest
find a presentation on his motivations here: https://github.com/faster-cpython/ideas/blob/main/FasterCPyt... Sam Gross comes out of that community so he’s familiar with the motivations for making raw python faster.
In A viable solution for Python concurrency
I thought of this idea as well, but don’t think this is really the right approach. Many of these issues relate to specific features which developers subsequently avoid using. I think these types of initiatives should be more broadly targeted and probably curated by the maintainers/users of the software. E.g. the faster-cpython project is focusing on improving general Python interpreter performance: https://github.com/faster-cpython/ideas
In Show HN: Work for Performance – Open performance issues on open-source

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