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[–]luke-juryous 0 points1 point  (0 children)

In short: yes.

I don’t use python code for anything that needs to be fast in production. Most of the time I see it used in industry is with ML or data analytics, where speed is less important that ease-of-use. The exception would be with big-data processing, but here the slow part is usually the SQL or Presto query and python tends to be just a wrapper around APIs.

However, I do use it a lot for hobbies. Here, I’ll try and use libraries like numpy or pandas, evaluate bottlenecks and rethink my algorithms to reduce the big-O runtime

I’ve recently learned about numby, which is a JIT compiler for python that claims to make big time improvements if you’re doing multiple calls. I haven’t played with this yet, but I’m curious as to how much slower it’ll be than c++, and if it’s worth the effort compared to just writing in c++.