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python
cpython
Python2014–2026
python / cpython

cpython

The Python programming language

Languages & Compilers
Explore on GitHubRead Hacker News discussions
400Distinct people
547Mentions
3Explicit recommenders
78.2KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

The Python programming language

GitHub

Where it is used

  • AWS Lambda — AWS Lambda provides a managed runtime and container base image for Python 3.11 that runs on CPython’s interpreter improvements. It uses CPython’s specialization adaptive interpreter features to improve Lambda workloads’ performance. Source
  • abridging clinical conversations using python — “In addition to the above-mentioned instances, we also use Python widely in conjunction with several Google Cloud Platform (GCP) services and to set up other monitoring and debugging tools.” Source
  • 4 more documented examples

What people are saying

I love the description in the draft PR: 'Twas the night before Christmas, when all through the code Not a core dev was merging, not even Guido; The CI was spun on the PRs with…

divbzero used a recommendation phrase. 3 indexed comments match. This is a phrase match, not a verdict.

Favorable Commenters discuss Tim Peters' contributions to CPython, including int-to-str conversion and Timsort. The tone is respectful and appreciative of his technical achievements.

This week’s discussion is favorable. This is not a standing endorsement. Read the supporting reply

Also in these discussions

  • golang/go · linked in 2 of the same discussions
  • nodejs/node · linked in 2 of the same discussions
  • ruby/ruby · linked in 2 of the same discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Favorable

Commenters discuss Tim Peters' contributions to CPython, including int-to-str conversion and Timsort. The tone is respectful and appreciative of his technical achievements.

Supporting reply 1 · Supporting reply 2 · 2 discussions summarized

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

Tim Peters has died direct repository linkDebated

The discussion centers on the death of Python contributor Tim Peters, with widespread tributes to his technical legacy like Timsort and the Zen of Python clashing with heated disagreements over his controversial suspension by the Python Software Foundation. While many users urge focusing solely on his contributions, others argue that ignoring the PSF's handling of his ban is a disservice to his memory and an endorsement of flawed community governance.

189 readable replies · Supporting reply 1 · Supporting reply 2 · Supporting reply 3 · Supporting reply 4
Timsort direct repository link

Read the discussion on HN. A full-thread summary is not available yet.

Adapting CPython for Yk project name in title

Read the discussion on HN. A full-thread summary is not available yet.

Showing the three threads with the most distinct people linking this repo, from 5 threads this week.

Mentions over time

HN mentions by year547 dated mentions

Observed mentions: 2014-12-30 12:04:55 UTC to 2026-10-27 17:34:51 UTC.

0204060802014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20142015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 20 mentions; 2 submissions, 18 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 36 mentions; 4 submissions, 32 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 28 mentions; 2 submissions, 26 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 33 mentions; 4 submissions, 29 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 54 mentions; 2 submissions, 52 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 62 mentions; 3 submissions, 59 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 63 mentions; 6 submissions, 57 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 64 mentions; 4 submissions, 60 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 70 mentions; 6 submissions, 64 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 72 mentions; 6 submissions, 66 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 40 mentions; 5 submissions, 35 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
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC101
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC404
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC20218
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC36432
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC28226
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC33429
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC54252
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC62359
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC63657
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC64460
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC70664
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC72666
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC40535

What Hacker News says

62 sources
mschuster91·Dec 16, 2021
If you're doing user-supplied CSVs, definitely... but if you are ingesting CSVs from a known source with known format (<insert audible sigh here>) it can definitely make sense to use a high-speed optimized ingester. One might wonder if it might be worth the time to look into optimising the runtimes of various languages. I took a look, all operate on naive byte-by-byte scanning, and all sans PHP are written in the respective language which means any form of SIMD optimization is right off the table (okay, maybe something could be done in Java, but it seems incredibly complex, see https://www.morling.dev/blog/fizzbuzz-simd-style/): - PHP isn't optimized anywhere, but at least it's C: https://github.com/php/php-src/blob/1c0e613cf1a24cdc159861e4... - Python's C implementation is the same: https://github.com/python/cpython/blob/main/Modules/_cs
Read the rest
v.c - Java doesn't have a "standard" way at all (https://www.baeldung.com/java-csv-file-array), and OpenCSV seems the usual object-oriented hell (https://sourceforge.net/p/opencsv/source/ci/master/tree/src/...). - Ruby's CSV is native Ruby: https://github.com/ruby/ruby/blob/bd65757f394255ceeb2c958e87...
In Leveraging SIMD: Splitting CSV Files at 3Gb/S
raymondh·Nov 23, 2021
If the OP has time, it might be nice to experiment with the hash table technique used by sets in Python. It has a variant of open addressing the runs several linear probes before jumping to another location in hash table. The premise is that probing consecutive memory addresses is cheap because of cache locality and because the address computation is a simple increment. This should be cheaper than resolving hash collisions with additional random probes or by chasing linked list references to random memory locations for each link. https://github.com/python/cpython/blob/f840398a5fd8741653c26...
In A Tale of Java Hash Tables
kgm·Nov 14, 2021
One thing to note, in the gritty details of Python's actual implementation of the list type, is that there's a little more to say about how list resizing works than is immediately obvious. The relevant source is here: https://github.com/python/cpython/blob/main/Objects/listobje... As the article points out, the size progression, as detailed in the comment in that source, is relatively modest. Your "classic" dynamic array will simply double the size as needed. This progression does less than that: 16, 24, 32, 40, and so on. But: The underlying implementation is using the standard C library function realloc(). This will perform some amount of in-place resizing on its own, and will lend a lot to the performance of a Python list, albeit in a way that might be difficult to nail down, since it depends on the overall usage of the C library's hea
Read the rest
p.
In How Python List Works
MarkSweep·Nov 14, 2021
In languages that have immutable string semantics and can detect that they are the exclusive owner of a string, they can modify them in place. For reference counting languages like Python, they can easily determine they are the exclusive owner by checking for a reference count of 1. See: https://github.com/python/cpython/blob/main/Objects/unicodeo... Rust's ownership system ensures that there cannot exist mutable and immutable references to the same object at the same time. So if you have a mutable reference to a string it is ok to modify in place. I have not confirmed either the Python example or the Rust example too deeply, since I'm replying to 5 day old comment. But the general principal holds. GC languages like C# and Java don't have easy ways to check ownership so they always copy strings when mutating them. Maybe I'll write a blogp
Read the rest
ost on this in the future.
In A terrible schema from a clueless programmer
perth·Nov 10, 2021
The most insane thing about Python is how you can override single methods in classes and use the class like normal. One time I was working on getting FIFO working on Windows, and none of the Python built-ins were set up to handle any random process writing to a named pipe that wasn't within the same Python instance. So what I did was I took the closest implementation Python offered, which was in the multiprocessing module [1], and overrode a single one of the methods to do what I wanted it to do. The module still handled all of the cleanup so I was confident there weren't any memory leak issues, and I was able to make a simple change to the flags it was passing Windows to allow for the functionality I wanted. A language that has a hackable standard library itself is insane and I don't think I've seen it on any other language. In addition,
Read the rest
I've found the C/C++ bindings for Python wonderful and intuitive to work with. The setup takes no effort at all and it "just works", batteries included, via ctypes. https://github.com/python/cpython/blob/main/Lib/multiprocess...
In Ask HN: How did Python become the lingua franca of ML/AI?
shoo·Nov 6, 2021
I first learned about this while trying to understand processes being killed by OOM in production. We had python 2.x batch jobs being executed by long-running python worker processes -- some of the arbitrary application code in some of the arbitrary batch jobs would occasionally want to execute some command line tool in a new process, and to create the new process under the hood python's subprocess library would fork/exec, and if the parent worker process had already accumulated a large virtual memory footprint, linux's approximate memory accounting heuristics would kick in during the attempted "fork", decide that we were obviously going to run out of physical memory, and kill the process. We didn't actually want to fork anything and share gigabytes of virtual memory with the child process, we wanted to spawn an almost entirely independe
Read the rest
nt process to do something and report results, but that got implemented under the hood by fork. Spawning processes is one area where Windows is more elegant than linux: windows offers spawn. Apparently macos and solaris implement a posix_spawn that avoid the complications of fork/exec. linux offers posix_spawn, apparently which may may or may not call fork under the hood depending on which libc you're using. If libc implements posix_spawn by calling fork then you're back in the same mess with linux heuristic memory accounting and overcommit. E.g. old versions of glibc will fork when you posix_spawn, newer versions of glibc may vfork . musl apparently will always vfork. It looks like cpython's subprocess.Popen was patched in python 3.8 to detect some cases where posix_spawn can be used -- it reads as if it will only kick in on linux if it detects a sufficiently new version of glibc: https://github.com/python/cpython/blob/main/Lib/subprocess.p... edit: Python 3.10 now supports using vfork for linux inside subprocess: https://bugs.python.org/issue35823 docker run --rm -it --entrypoint=/bin/sh python:3.9-alpine # apk add strace # strace python -c "import subprocess; subprocess.run(['ls', '-l'])" 2>&1 >/dev/null | grep fork fork() = 88 docker run --rm -it --entrypoint=/bin/sh python:3.10-alpine # apk add strace # strace python -c "import subprocess; subprocess.run(['ls', '-l'])" 2>&1 >/dev/null | grep fork vfork() = 15 edit 2: here's a similar tale from go, replacing use of fork in fork/exec: https://github.com/golang/go/issues/5838 https://go-review.googlesource.com/c/go/+/37439/ https://about.gitlab.com/blog/2018/01/23/how-a-fix-in-go-19-...
In In C, how do you know if the dynamic allocation succeeded?
__s·Nov 3, 2021
JIT can be considered an optimization. If you F12 in your browser you have a javascript REPL, no need to know about JIT or not CPython doesn't have a JIT, it has an interpreter. So it spends a lot of time in this loop: https://github.com/python/cpython/blob/main/Python/ceval.c But you still have a repl with pypy. The downsides of JIT is that compiling bytecode to assembly can take up time (hurting startup performance, but that can be mitigated by not applying jit aggressively) & some programs have very dynamic behavior which the JIT has to eventually give up on (& go back to interpreting) or run off some pathological performance cliff where it takes up a bunch of memory & runs 10x slower than interpreter Ruby 3 introduced a jit to their reference implementation
In Python interpreter written in rust reaches 10000 commits
epage·Nov 2, 2021
The main arg parser for Rust (clap) was looking at using sysexits for usage but then got feedback from burntsushi (of ripgrep fame) for how rarely it is used and instead encouraged 2. In looking at it, it seems like 2 is the most consistent code and for clap v3 will be using it. - 2 is "misuse of shell built-ins" for bash [1] - Python's argparse uses 2 [2] I feel like we looked at more but can't remember which all they were [0] https://github.com/clap-rs/clap/pull/1637#issuecomment-58103... [1] https://tldp.org/LDP/abs/html/exitcodes.html [2] https://github.com/python/cpython/blob/main/Lib/argparse.py#...
In Sysexits – preferable exit codes for programs

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