[Demiurge]

I agree. I've been living off Python for 20 years and have never needed to know any of these numbers, nor do I need them now, for my work, contrary to the title. I also regularly use profiling for performance optimization and opt for Cython, SWIG, JIT libraries, or other tools as needed. None of these numbers would ever factor into my decision-making.

[AtlasBarfed]

.....

You don't see any value in knowing that numbers?

[Demiurge]

That's what I just said. There is zero value to me knowing these numbers. I assume that all python built in methods are pretty much the same speed. I concentrate on IO being slow, minimizing these operations. I think about CPU intensive loops that process large data, and I try to use libraries like numpy, DuckDB, or other tools to do the processing. If I have a more complicated system, I profile its methods, and optimize tight loops based on PROFILING. I don't care what the numbers in the article are, because I PROFILE, and I optimize the procedures that are the slowest, for example, using cython. Which part of what I am saying does not make sense?

[KeplerBoy]

That makes perfect sense. Especially since those numbers can change with new python versions.

[TuringTest]

As others have pointed out, Python is better used in places where those numbers aren't relevant.

If they start becoming relevant, it's usually a sign that you're using the language in a domain where a duck-typed bytecode scripting-glue language is not well-suited.