Python 3.11 vs 3.10 performance

These speedups are awesome, but of course one wonders why they haven't been a low-hanging fruit over the past 25 years.

Having read about some of the changes [1], it seems like the python core committers preferred clean over fast implementations and have deviated from this mantra with 3.11.

Now let's get a sane concurrency story (no multiprocessing / queue / pickle hacks) and suddenly it's a completely different language!

[1] Here are the python docs on what precisely gave the speedups: https://docs.python.org/3.11/whatsnew/3.11.html#faster-cpyth...

[edit] A bit of explanation what I meant by low-hanging fruit: One of the changes is "Subscripting container types such as list, tuple and dict directly index the underlying data structures." Surely that seems like a straight-forward idea in retrospect. In fact, many python (/c) libraries try to do zero-copy work with data structures already, such as numpy.

> Now let's get a sane concurrency story

This is in very active development[1]! And seems like the Core Team is not totally against the idea[2].

[1] https://github.com/colesbury/nogil

[2] https://pyfound.blogspot.com/2022/05/the-2022-python-languag...

Python has actually had concurrency since about 2019: https://docs.python.org/3/library/asyncio.html. Having used it a few times, it seems fairly sane, but tbf my experience with concurrency in other languages is fairly limited.

edit: ray https://github.com/ray-project/ray is also pretty easy to use and powerful for actual parallelism

Cool improvement but changes very little when Python is x100 times slower than other GC languages.

I don't wonder. For me it seems pretty clear.

I believe the reason is that python does not need any low-hanging fruits to have people use it, which is why they're a priority for so many other projects out there. Low-hanging fruits attract people who can't reach higher than that.

When talking about low-hanging fruits, it's important to consider who they're for. The intended target audience. It's important to ask ones self who grabs for low-hanging fruits and why they need to be prioritized.

And with that in mind, I think the answer is actually obvious: Python never required the speed, because it's just so good.

The language is so popular, people search for and find ways around its limitations, which most likely actually even increases its popularity, because it gives people a lot of space to tinker in.