all programs are single threaded unless otherwise specified.
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Oooooh this is really cool, thanks for sharing. How could I install it on Linux (Ubuntu)? I assume I would have to compile CPython. Also, would the source of the programs I run need any modifications?
In this case, it's a feature of the language that enables developers to implement greater amounts of parallelism. So, the developers of the Python-based application will need to refactor to take advantage of it.
From memory I can only answer one of those: The way I understand it (and I could be wrong), your programs theoretically should only need modifications if they have a concurrency related bug. The global interlock is designed to take a sledgehammer at "fixing" a concurrency data race. If you have a bug that the GIL fixed, you'll need to solve that data race using a different control structure once free threading is enabled.
I know it's kind of a vague answer, but every program that supports true concurrency will do it slightly differently. Your average script with just a few libraries may not benefit, unless a library itself uses threads. Some libraries that use native compiled components may already be able to utilize the full power of you computer even on standard Python builds because threads spawned directly in the native code are less beholden to the GIL (depending on how often they'd need to communicate with native python code)
Oh wow, a programming language that is not supposed to be used for every single software in the world. Unlike Javascript for example which should absolutely be used for making everything (horrible). Nodejs was a mistake.
don't worry it'll use all the RAM anyway
let's be honest here, he actually means 0.01 core performance
Do you mean Synapse the Matrix server? In my experience, Conduit is much more efficient.
i wish they would switch the reference implementation to conduit
there is core components on the client side in rust so maybe that's the way for the future
Yep, I mean as in matrix. There is currently no was to migrate to conduit/conduwuit. Btw from what I've seen conduwuit is more full-featured.
I tough this was about excel and was like yeah haha!
But is about Python, so I'm officially offended.
I prefer this default. Im sick of having to rein in Numba cores or OpenBlas threads or other out of control software that immediately tries to bottleneck my stack.
CGroups (Docker/LXC) is the obvious solution, but it shouldn't have to be
I'll be honest, this only matters when running single services that are very expensive. it's fine if your program can't be pararlelized if the OS does its job and spreads the love around the cpus
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