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Yea it’s gotten to the point where it’s a sub-domain of expertise in Python being on top of the various performance extensions/runtimes/hacks. Intuitively, num
by maegul 3y ago
Yea it’s gotten to the point where it’s a sub-domain of expertise in Python being on top of the various performance extensions/runtimes/hacks.
Intuitively, numba and cython still feel like the most interesting/relevant.
I recall talk a few years ago about the possibility of writing packages in “numba”. IE, targeting the subset of Python and numpy that numba supports.
Occasionally I check in with numba’s releases and they seem to be slowly but surely supporting more of Python such that surely it will start to make sense to talk about the “numba” language. Has anyone got a tighter grip on whether this than I?
- BiteCode_dev 3y agoI would say the most popular way to speed up a python program today is not through a compiler anymore, but using rust for hot loops and maturin (https://pypi.org/project/maturin/ https://pypi.org/project/maturin/) for seamlessly use it in Python and provide packages. I get the benefit of being able to "just use python" and still gain a speed up though. Plus there are many situations with rust is no possible (no time to learn such a complex language, rust is not approved by the security team).
- tialaramex 3y agoThe other edge is where your heatmap is just all red, and so "speed up hot loops" isn't going to get it done, and at that point somebody needs to bite the bullet and {hire people who know / learn} an AOT language with good performance. or it turns out the reason the heatmap is all red is that you were solving categorically the wrong problem, e.g. you decided to use machine vision to figure out what's in the packaging, while your competitors are just scanning the EAN-13 barcode.