MacOS and docker is asking for trouble. It requires all kinds of hacks and awareness of where things are being built or mounted, which architecture is being emulated because it runs in a VM, memory limits, swapping, and so on. It's no surprise build times are a problem.

I imagine your build pipeline is for aarch64, you have made modifications to numpy itself (build flags or something), you're using a special distro in the pipelines, or the rebuild is unnecessary. For me numpy has always been a simple "pip install numpy" or "poetry install" when not on nixOS.

My guess is that if you used non-emulated Linux, your local build issues would be reduced and also sped up. But I can't say that with any certainty because I don't have nor require nvidia in my Linux rig, nor do I know your setup very well.

You do however fall quite nicely into the criteria I shared. Were you outside of that, python would probably be much much easier (aka no non-pytjon deps).

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[–] BatmanAoD@programming.dev 0 points 4 months ago (2 children)

MacOS and docker is asking for trouble.

That's a real problem! MacOS and Docker are extremely common for development, and a scripting language like Python should just work with them, not just at the language level (which is good enough) but in the ecosystem and tooling. The latter is what Astral is trying to improve.

[–] onlinepersona@programming.dev 1 points 4 months ago* (last edited 4 months ago) (1 children)

I'm not talking specifically Python. Just macOS and docker. That combination has proven time and time again to be a massive timesink in every place I've seen it used. Devs can spend days (not joking, I've seen this happen multiple times) getting it setup for whichever purpose.

It went from all kinds of fancy wrappers around QEMU to claims that Rosetta and Intel docker would work, to Apple's VMs, docker's proprietary VM (after they dropped qemu), Ubuntu's Multi-pass, and that's where I stopped following the news. Every single one of these solutions claimed to be the best and they all ran into such massive problems that they needed hacks and workarounds and "novel" solutions.

And these weren't even for niche or hardware related stuff. Simply mounting the repository's folder or mounting a node_module folder absolutely killed performance on Macs because it wasn't direct hardware access or filesystem access but everything had to go through a socket or some sort from the VM to Mac. Anything with many files or file access completely tanked: java, Kotlin, C/C++, Rust, anything compilation, JavaScript and it's modules, Perl too.

One would expect the logical conclusion to be "Mac isn't the best development platform for Linux deployables" but instead a few glossy, rounded corners later and people cling on to it and then blame the tools for not adapting to Mac hacks.

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[–] BatmanAoD@programming.dev 1 points 4 months ago

Well, that's fair; first-class support for running an actual Linux kernel, with the containerization support that implies, is one of the reasons I prefer Windows with WSL as a dev environment when using Docker (at least, in companies where the IT team won't just let you run native Linux).

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