The State of Python Profiling in 2026
Comments on “The State of Python Profiling in 2026”
Claim-checked. Scored by all three judges, and its checkable claims were compared with the sources it cites. How far stories are checked
Austin's maintainer surveys Python profiling as CPython 3.15 adds Tachyon (profiling.sampling) to the standard library, built on 3.14's remote-debugging interface. Tachyon only profiles 3.15 and later, whereas py-spy lacks free-threaded support and Scalene profiles from inside the process. Austin 4.1 adds native-stack mode and asyncio task tracking. The author's own CI benchmark, on Linux x86_64 with Python 3.13, shows repeated-stack detection lifting the maximum sampling rate from 121,000 to 166,000 samples/s; the figure comes from the author and wasn't independently checked, and the gain varies with workload.
Why it ranked
No. 20 of 137 with a score of 0.66. The panel rated it highest on new information (0.92) and technical depth (0.91), lowest on significance (0.58). Placed No. 20, No. 30 by score alone: the fourth Programming & dev tools story of the day (−0.020). The placement terms move stories; they are not part of the score.
- AI judgeJudge 2claude-haiku-5-5
- Detailed, technically rich comparison of Python profilers and an Austin 4.1 release; author is self-promoting the tool they maintain, with unverified benchmark claims, but the technical substance is strong and new.
- AI judgeJudge 3gpt-5.6-luna
- A technically detailed, actionable comparison of Python profilers and Austin 4.1, with benchmarks and implementation specifics. It is highly relevant and novel, though the author's ownership of Austin introduces modest promotional bias.
Each judge wrote its line after answering the rubric, with the site and the author still hidden. Every answer behind this is in the table under Score.
Score
0.66total under rubric v2.3
- Significance0.58
- Reader interest0.79
- Audience breadth0.59
- Practical relevance0.82
- Substantiated0.76
- Technical depth0.91
- New information0.92
- Counts against: Promotional0.24
- Counts against: Overclaim0.22
Each judge’s answer per question (0–1), their mean and spread, and what the question adds to the score (weight × mean).
| Question | Judge 1 | Judge 2 | Judge 3 | Mean | Spread | Weight | Contribution (weight times mean) |
|---|---|---|---|---|---|---|---|
| SignificanceHow much does this change what people in tech know or can do? | 0.63 | 0.50 | 0.62 | 0.58 | 0.13 | +0.24 | +0.140 |
| Reader interestWould a well-informed senior engineer or tech founder want to read this today, and likely pass it on? | 0.71 | 0.80 | 0.86 | 0.79 | 0.15 | +0.26 | +0.205 |
| Audience breadthHow many people who build technology does it concern? | 0.60 | 0.60 | 0.58 | 0.59 | 0.02 | +0.13 | +0.077 |
| Practical relevanceHow useful is it to someone who builds software or tech products? | 0.88 | 0.75 | 0.82 | 0.82 | 0.13 | +0.22 | +0.179 |
| SubstantiatedHow well is it backed? Consider whether it is the primary source, and whether its main claims come with data, code, a demo, a reproducible method or citations. | 0.91 | 0.60 | 0.78 | 0.76 | 0.31 | +0.05 | +0.038 |
| Technical depthHow technically substantive is it? | 0.99 | 0.85 | 0.88 | 0.91 | 0.14 | +0.05 | +0.045 |
| New informationDoes it contain information absent from the stories covered in the last 7 days (list provided)? | 0.93 | 0.85 | 0.97 | 0.92 | 0.12 | +0.05 | +0.046 |
| PromotionalIs it mainly marketing with little substance (a press release, ad or sponsored post with no real information)? A launch post that carries real news is not promotional. | 0.08 | 0.35 | 0.28 | 0.24 | 0.27 | −0.19 | −0.045 |
| OverclaimDo the headline or conclusions claim more than the body supports? | 0.19 | 0.30 | 0.18 | 0.22 | 0.12 | −0.11 | −0.025 |
| Sum of contributions | +0.661 | ||||||
| Claim-check penalty | 0.000 | ||||||
| Total, as published | 0.661 | ||||||
Spread is the highest minus the lowest judge answer. marks a spread above 0.40: the judges disagree, and the story is marked contested.
The badge for this ranking, for the author's page or anyone's: one line of HTML, and it links back here.
<a href="https://rubric.hrih.si/editions/2026-11-04/20/"><img src="https://rubric.hrih.si/badge/2026-11-04/20.svg" alt="Ranked #20 on Rubric, 4 Nov 2026" width="238" height="28"></a>Claim check
Claim check: 2 matches source · 2 couldn’t check. Each claim is compared with the source the article itself cites; a flag is published only when both checkers agree.
Matches sourceBenchmark result
The Scalene team's 2022 study concluded that sampling profilers are both more efficient and often more accurate than tracing profilers.
The cited source says the same thing.
The article says “sampling profilers are "both more efficient and often more accurate" than tracing ones”
The source says “Sampling-based profilers are both more efficient and often more accurate than the deterministic profilers”
Source cited by the article: arxiv.org/abs/2212.07597
Couldn’t checkBenchmark result
In the Scalene team's study, Austin, py-spy and Scalene added between 0% and 2% to run time in CPU mode, compared with 73% for cProfile and more than 200% for some others.
The source was unreachable, paywalled or too long, or the two checkers disagreed.
The article says “adding between 0% and 2% to the run time, compared with 73% for cProfile and more than 200% for some others”
The source says No passage could be compared.
Source cited by the article: arxiv.org/abs/2212.07597
Matches sourceNumber
The study found one tracing profiler reporting that a function took 80% of the run time when it actually took 25%.
The cited source says the same thing.
The article says “The study found one tracing profiler reporting that a function took 80% of the run time when it actually took 25%”
The source says “In the worst case, one such profiler reports a function takes 80% of execution time while in fact it only consumes 25%”
Source cited by the article: arxiv.org/abs/2212.07597
Couldn’t checkBenchmark result
Austin 4.1's repeated stack detection raised the maximum wall-time sampling rate from 121,000 to 166,000 samples/s (+37%) on Linux x86_64 with Python 3.13.
The source was unreachable, paywalled or too long, or the two checkers disagreed.
The article says “121,000 → 166,000 samples/s (+37%”
The source says No passage could be compared.
Source cited by the article: github.com/P403n1x87/austin/pull/402
Also covered by
No other coverage was clustered with this story.
Elsewhere
Elsewhere: HN 2 pts, not on front page
Recorded for context only, checked 4 Nov 2026, 05:47 UTC. It played no part in the ranking.