[devjab]

You should really add that Python is also a very good tool for people who know more performant languages. I think one of the sides which often gets forgotten is that a lot of software will never actually need to be very performant and often you’re not going to know the bottlenecks beforehand. If you even get to the bottlenecks it means you’ve succeeded enough to get to the bottlenecks. Somewhere you might not have gotten if you over engineered things before you needed it.

What makes Python brilliant is that it’s easy to deliver on business needs. It’s easy to include people who aren’t actually software engineers but can write Python to do their stuff. It’s easy to make that Wild West code sane. Most importantly, however, it’s extremely easy to replace parts of your Python code with something like C (or Zig).

So even if you know performant languages, you can still use Python for most things and then as glue for heavy computation.

Now I may have made it sound like I think Python is brilliant so I’d like to add that I actually think it’s absolute trash. Loveable trash.

[nomel]

> it’s extremely easy to replace parts of your Python code with something like C

I tend to use C++, so use SWIG [1] to make python code to interface with C++ (or C). You can nearly just give it a header file, and a python class pops out, with native types and interfaces. It's really magical.

[1] https://www.swig.org

[lanstin]

I do think not being able to use 32 cores easily is a gap in the current language. In 2017 I rewrote a fairly high performance python dialog to Kafka daemon in Go. The python version require a lot of specialized knowledge to write, using gevent, PyPy, hand optimizing our framework for the hot paths etc, and still was only using a few cores to do work.

The Go was a dead simple my first Go project sort of implementation and used 32 cores and therefore worked much better right out of the gate. (I mean I did have go routine worker pools for each step of the processing, but the division of work into the stages was already in the Python code).

So yeah Python is easy to make less of a mess of for lots of people, until you want to use all your cores (which again means rerunning your things goes from four minutes to 15 seconds on that fancy laptop).