> The computationally expensive parts of “Python” are done in libraries like numpy, tensorflow, etc. Python makes it really handy to play with low level abstrac

> The computationally expensive parts of “Python” are done in libraries like numpy, tensorflow, etc. Python makes it really handy to play with low level abstractions in a higher level language. > So yeah I’ve never stressed much about the GIL as a long time pythons dev You almost always have to use python objects at some point or another, even with very high perf libraries. Unless you are using python as nothing else than glue code, and loading and preprocessing the data entirely outside of your python code. At some point (and I'm not talking about extreme scales here, just feeding a single datqaloader can be enough) you hit a very hard performance bottleneck. Sure you can just use more external code at that point but I think the intention is to make python at least more suitable for the non compute intensive stuff. Like, it is already suitable right now but it's not getting better, while everything around it is (I'm not talking about other languages, what I mean is that the tools and libraries are getting better so without improvement to the language the bottleneck will just get worse)