[coldtea]

>Like I can use Node, Go, C#, and Java at scale without being concerned about the low-level details, however, that's not the case for Python.

Well, if you chose not be concerned about the low-level details with these languages, then you can chose not to be concerned about the low-level details with Python. There's nothing inherent in Python or those other languages that makes it otherwise.

Or you mean "but Python is slow"? That's mostly irrelevant for many use cases, which either don't need the speed (web, administration, glue, controllers, etc), or depend on Python packages written in C/Fortran and plenty fast (which is the case for AI / ML / DS and such).

>it doesn't seem to offer any benefits compared to Node, Go, C# or even Java

Ease of use, less ceremony, huge package ecosystem including several de-facto standards for many use cases/industries, suitable for glue work, are benefits.

[itsmefaz]

> Ease of use, less ceremony, huge package ecosystem including several de-facto standards for many use cases/industries, suitable for glue work, are benefits.

Sure, these are operational advantages. But purely from an computational perspective (GPUs, multi-core, concurrency, etc) does it offer anything natively without interfacing with C/C++ that validates it to be called a general purpose language.

[coldtea]

>But purely from an computational perspective (GPUs, multi-core, concurrency, etc)

Most of the stuff people do with Python isn't hampered by the "computational perspective". For the things that are, we usually don't need to interface with C/C++, because somebody else has already written the library that does it.

[smoldesu]

> does it offer anything natively without interfacing with C/C++ that validates it to be called a general purpose language.

In fairness, a huge amount of C/C++ functionality is managed by the kernel anyways. I'd bet most of the stuff C is used for in this situation could be replaced with Python code, but isn't for maintainability and performance purposes.