My point was that if this was the case, your Python code is probably suboptimal.
Sure, you are comparing against naive implementation as well, but if performance is a concern, don't do naive Python :)
> I gave the example earlier of a web service that was struggling to complete requests in even 60s (despite using Numpy under the hood where possible) while a naive Go implementation completed in hundreds of ms.
Yes, it's easy and sometimes even idiomatic to write non-performant Python code. Getting the most out of pure Python is hard and it means avoiding some common patterns.
Eg. simply using sqlalchemy ORM (to construct rich dynamic ORM objects) instead of sqlalchemy core (tuples) to get 100k+ rows from DB is 20x slower, and that's still 2x slower from pure psycopg (also tuples using basic types). There are plenty of examples like this in Python, unfortunately.