I agree with those who say "software engineering" is not "engineering." We as a field are more comfortable with our beliefs, supported by anecdotal evidence, than with empirical results.

That said, the few and limited empirical results which do exist, like Prechelt's empirical work from 20 years ago, support the author's premise.

As another example, Boehm's work across a range of projects (<100KLoc) shows that code size has the biggest impact on development effort, and slightly non-linear scaling in KLoC (KLoC^~1.1 in COCOMO); and various publications show Python generally requires fewer lines of code.

(As one example picked semi-arbitrarily from a Google Scholar search, http://jucs.org/jucs_19_3/a_comparison_of_five/jucs_19_03_04... on a small project has Python at the smallest effective LOC, smallest effective byte size, and nearly the smallest (after Java) eByte/eLOC size.)

Modern C++ is a much more compact (and complicated!) language than 20 years ago, so of course all of these previous results must be reviewed and reconsidered.

As a field, we have not provided that funding for solid empirical research!

> At no point does the author acknowledge that there may be other reasons to pass over python than performance.

Shrug. Okay. And from that you conclude the author is saying that Python should be used in all cases? "I'm going to talk about why you should eat more vegetables" doesn't mean "you should only ever eat vegetables." Similarly, "I'm going to talk about why you shouldn't reject Python from the get-go for a project you think is performance intensive" doesn't mean "you should only ever use Python."

The author even talks about Rust in an earlier blog entry, from August of this year, at https://snarky.ca/introducing-the-python-launcher-for-unix/ saying "And so over 3 years ago I set out to re-implement the Python Launcher for Unix in Rust. On July 24, 2021, I launched 1.0.0 of the Python Launcher for Unix".

So the evidence is that Cannon does not believe that Python is the best language for all projects.

> Sometimes, your performance is your users' time

Cannon's essay is about the case where people select a programming language based strongly on expected computational cost, and forget other factors in the cost model. Here's the relevant quote:

] I think the jump to selecting a programming language based on potential performance needs often comes from a place where people think their computation costs are more important to optimize for than their developer time. I don't think that always holds, though, as software developers are expensive.

In your model, people are choosing a language based in part of the cost of users' time, which means they they are not primarily focused on computation costs, and so are outside the scope of this essay. That doesn't contradict the essay, only show that it's incomplete. Which we know already from the text itself.

> Sometimes, if you don't reach a given threshold, your code simply doesn't work.

And sometimes you can reach a given threshold with an off-the-shelf use of Pandas, rather than build your own analysis routine. If you start off thinking "Python must be slow" and don't even know what your thresholds or performance characteristics are, then selecting (say) assembly over Python is probably premature optimization.

Cannon didn't even argue that if you aren't building data centers then you must use Python. Your [2] trims the full paragraph I quoted earlier. You left out: a) the "please consider", which makes this a request, and not a rejection of any alternatives; b) the request to also consider developer costs, because essay argues people should consider more than computational costs; and c) the "you don't even know if that perceived efficiency is even necessary", which ties the essay back to Knuth's "premature optimization is the root of all evil" quote.