Show HN: Socketify.py: Http/Https and WebSockets servers for PyPy3 and Python3

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Re: Show HN: Socketify.py: Http/Https and WebSockets servers for PyPy3 and Python3

#191

Post by okaleniuk » Thu, Jan 19, 2023, 3:49 PM UTC

goatlover wrote: post #29

okaleniuk wrote: post #13

Good point! However, you bring in a common misconception I'm fighting with within my company for a long time. Python is not an interpreted language. There is no such thing as an "interpreted language", a language is just a set or rules and keywords. Everything you can fit into Backus–Naur form is already a language even if it doesn't have any implementation nor compiler neither interpreter. Just as a piece of evidenc…

For all practical purposes, a programming language is defined by it's general real world implementation, and not it's specification. Maybe not so much for computer scientists, but for programmers, Python is interpreted with some JIT alternatives and C++ is compiled.

Numba is a Python compiler for heterogeneous programming. It builds kernels with the same back-end NVCC does. With the equivalent AST, the kernel code it also equivalent.

We adopted it last year, and we don't rewrite code in C++ for GPGPU anymore. We save tons of effort on rewriting and even more on support.

How is this computer science?

Re: Show HN: Socketify.py: Http/Https and WebSockets servers for PyPy3 and Python3

#192

Post by okaleniuk » Thu, Jan 19, 2023, 3:54 PM UTC

messe wrote: post #124

okaleniuk wrote: post #114

Earlier quoted context omitted.

I literally posted the links to the AOT Python compiler and to the C++ interpreter.

The commenter above you said: > general real world implementation By this they mean the real-world-implementation that is in general use, which in this case is interpreted. Yes, Python can be compiled and C++ can be interpreted. 99% of the time, they're not though. When somebody says X language is interpreted, they mean that the most common and widely implementation is an interpreter. That's a useful bit of informati…

Counterexample. Numba is a Python compiler for heterogeneous computing. We adopted it last year and stopped rewriting code in C++ to run it on GPGPU.

On one hand, the conception from the 90s based on the most common Python implementation, on the other - a compiler that saves us tons of money. Which one adds value again?

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