Comment by HenriTEL

The goal of the article is not to know the exact numbers by heart, duh!

Care about orders of magnitude instead, in combination with the speed of hardware https://gist.github.com/jboner/2841832 you'll have a good understanding of how much overhead is due to the language and the constructs to favor for speed improvements.

Just reading the code should give you a sense of its speed and where it will spend most time. Combined with general timing metrics you can also have a sense of the overhead of 3rd party libraries (pydantic I'm looking at you).

So yeah, I find that list quite useful during the code design, likely reduce time profiling slow code in prod.