It is hard to recommend Python in production

Idk why such noob stuff is upvoted on HN.

The only thing this tells you that you should try to avoid a billon nested loop iterations in python. In case you didnt know.

On the other hand I would also see python as a bit questionable for bigger procejts, just because at some point a type system does more help than harm. But I have never really worked with pythons type extension so nowadays even this might be good enough.

> The only thing this tells you that you should try to avoid a billon nested loop iterations in python. In case you didnt know.

Where does the article talk about the billion nested loop at all? It uses that as an illustration.

I mentioned the problems related to speed and performance of a simple web server as well as code maintainability issues.

> But I have never really worked with pythons type extension so nowadays even this might be good enough.

I have used Python type system extensively, it is unfortunately, still an honor-code based system. So, you have to catch it during code reviews.

... Adding a step in CICD that catches this is extremely trivial though.

Which tools would you recommend for that?

I'd argue it's noob to use Python for anything other than where it has actual strengths like data science. Even AI can't help Python performance issues, you're stuck. AI can help verify C code, for example, is memory safe. There's just nothing you can do to fix Python's biggest problems. Wrong tool for the job.

Most people seem to agree with my "hot" takes. Why should I invest so much time for a random comment? I just clarified what are the limits of my opinion.

On the other hand it doesn't seem you read the article? It is mostly focused on performance, which often shouldnt be the main focus when selecting the language. And even if you need performance (e.g. data science) it can be very fast if you source out the billion iterations to a library.

The article did talk about maintainability issues with Python as well.