Comment by Demiurge
1 day ago
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.
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You don't see any value in knowing that numbers?
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?
That makes perfect sense. Especially since those numbers can change with new python versions.
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.