I spent a decade optimizing Python data science projects for a Fortune 100. I agree with the other sentiments that you can't really optimize Python itself becau

I spent a decade optimizing Python data science projects for a Fortune 100. I agree with the other sentiments that you can't really optimize Python itself because of these weird behaviors that seem to change the more you look at them... Mostly all of my optimization work was generic computer science stuff across the entire system and, in the data science world, this usually meant optimizing the database queries or the io throughput, or the overall shape of the kind of work that they were doing in order to parallelize it, or figure out how to simply do way less, etc. If someone actually came up to me with an actual problem with a Python code and it was the Python code that was not performing correctly, I would pretty immediately say let's use something else. I think the efforts to make a more efficient Python are really great, but I think the extreme utility of Python as a light glue to pull together lots of other things that are performing well in other computer languages is a widely recognized strength of the Python ecosystem.