Python: The Optimization Ladder • Hacker News Board

Re: Python: The Optimization Ladder

#31

Post by repple » Sat, Mar 14, 2026, 4:34 PM UTC

jb_hn wrote: post #24

repple wrote: post #20

Significant AI smell in this write up. As a result, my current reflex is to immediately stop reading. Not judgement on the actual analysis and human effort which went in. It’s just that the other context is missing.

I didn't notice any signs of AI writing until seeing this comment and re-reading (though I did notice it on the second pass). That said, I think this article demonstrates that focusing on whether or not an article used AI might be focusing on the wrong “problem.” I appreciate being sensitive to the "smell" (the number of low-effort, AI posts flying around these days has made me sensitive too), but personally, I found…

Your initial focus is to prioritize which content to consume.

Re: Python: The Optimization Ladder

#32

Post by skeledrew » Sat, Mar 14, 2026, 4:36 PM UTC

I must admit that I'm amused by the people who find the writeup useful but are turned off by the AI "smell". And look forward to the day when all valued content reeks of said "smell"; let's see what detractors-for-no-good-reason do then (yes I'm a bit ticked by the attitude).

Re: Python: The Optimization Ladder

#33

Post by adsharma » Sat, Mar 14, 2026, 4:41 PM UTC

Missing: write static python and transpile to rust pyO3 which is at the top of the ladder.

Some nuance: try transpiling to a garbage collected rust like language with fast compilation until you have millions of users.

Also use a combination of neural and deterministic methods to transpile depending on the complexity.

Re: Python: The Optimization Ladder

#34

Post by FusionX » Sat, Mar 14, 2026, 4:41 PM UTC

repple wrote: post #20

Significant AI smell in this write up. As a result, my current reflex is to immediately stop reading. Not judgement on the actual analysis and human effort which went in. It’s just that the other context is missing.

I don't think it should be conflated with auto generated AI slop. I see a lot of snippets which were clearly manually written. I'm assuming the author used AI in a supervised manner, to smooth out the writing process and improve coherency.

Re: Python: The Optimization Ladder

#35

Post by markisus » Sat, Mar 14, 2026, 4:49 PM UTC

I wish there were more details on this part.

> Missing @cython.cdivision(True) inserts a zero-division check before every floating-point divide in the inner loop. Millions of branches that are never taken.

I thought never taken branches were essentially free. Does this mean something in the loop is messing with the branch predictor?

Re: Python: The Optimization Ladder

#36

Post by markisus » Sat, Mar 14, 2026, 4:53 PM UTC

repple wrote: post #20

Significant AI smell in this write up. As a result, my current reflex is to immediately stop reading. Not judgement on the actual analysis and human effort which went in. It’s just that the other context is missing.

I also seem to be developing an immune response to several slopisms. But the actual content is useful for outlining tradeoffs if you’re needing to make your Python code go faster.

Re: Python: The Optimization Ladder

#37

Post by jaharios » Sat, Mar 14, 2026, 4:54 PM UTC

json.loads is something you don't want to use in a loop if you care for performance at all. Just simple using orjson can give you 3x speed without the need to change anything.

Re: Python: The Optimization Ladder

#38

Post by tda » Sat, Mar 14, 2026, 5:00 PM UTC

adsharma wrote: post #33

Missing: write static python and transpile to rust pyO3 which is at the top of the ladder. Some nuance: try transpiling to a garbage collected rust like language with fast compilation until you have millions of users. Also use a combination of neural and deterministic methods to transpile depending on the complexity.

One thing with python is that usually I will use one of the many c based libraries to get reasonable speed and well thought out abstractions from the start. I architect around numpy, scipy, shapely, pandas/polars or whatever. So my code runs at reasonable speed from the start. But transpiling to rust then effectively means a complete redesign of the code, data structures, algorithms etc. And I have seen the AI tools really struggle to get it right, as my intent gets lost somewhere.

So what I do now (since Claude Code) is write really bare bones (and slow) pure python implementation (like I used to do for numba, pypy or cython ready code), with minimal dependencies. Then I use the REPL, notebooks and nice plotting tools to get a real understanding of the problem space and the intricacies of my algorithm/problem at hand. When done, I let Claude add tests and I ask it to transpile to equivalent Rust and boom! a flawless 1000x speed upgrade in a minutes.

The great thing is I don't need to do the mental gymnastics to vectorize code in a write only mode like I've had to do since my Matlab days. Instead I can write simple to read for loops that follow my intent much better, and result in much more legible code. So refreshing!

And with pyO3 i can still expose the Rust lib to python, and continue to use Python for glue and plotting

Re: Python: The Optimization Ladder

#39

Post by pavpanchekha » Sat, Mar 14, 2026, 5:02 PM UTC

markisus wrote: post #35

I wish there were more details on this part. > Missing @cython.cdivision(True) inserts a zero-division check before every floating-point divide in the inner loop. Millions of branches that are never taken. I thought never taken branches were essentially free. Does this mean something in the loop is messing with the branch predictor?

They're cheap but not free, especially at the front end of the CPU where it's just a lot more instructions to churn through. What the branch predictor gets you is it turns branches, which would normally cause a pipeline bubble, to be executed like straightline code if they're predicted right. It's a bit like a tracing jit. But you will still have a bunch of extra instructions to, like, compute the branch predicate.

Re: Python: The Optimization Ladder

#40

Post by achierius » Sat, Mar 14, 2026, 5:03 PM UTC

skeledrew wrote: post #32

I must admit that I'm amused by the people who find the writeup useful but are turned off by the AI "smell". And look forward to the day when all valued content reeks of said "smell"; let's see what detractors-for-no-good-reason do then (yes I'm a bit ticked by the attitude).

Isn't this a depressing thought? Regardless of AI, to think that everything we read would come in the same literary style, conveying little of the author, giving no window through which to learn about who they are -- that would be a real loss.