flambeau VS PyOxidizer

In particular for deep learning as bobsyourunkl already mentioned there is arraymancer on the one hand and also flambeau on the other. The latter is a Nim wrapper around libtorch (i.e. the PyTorch C++ backend). It is missing things (to be wrapped by adding a few lines) and has some rough edges, but if one needs to get stuff done, it's possible.

That’s one thing I like about Nim. It can compile to C++ and so can directly wrap C++ code. While Nim’s ecosystem is small it’s easy enough to wrap most any C/C++ library. It’s great for OpenCV. Some folks have been updating direct PyTorch C++ api (1)!

1: https://github.com/SciNim/flambeau

Bundling Python isn't too bad if you find the right tools for it.

I really like https://github.com/indygreg/python-build-standalone and https://github.com/indygreg/PyOxidizer

A bundled, built standalone Python can be 16 to 32MB (including the full standard library, which you can strip down to just the bits you use to save size). Not tiny, but probably not worth switching programming languages over.

But really, I would suggest thinking about what you want to build before "how" or "with which tool" - one of the signs of a person becoming a good engineer is having an array of tools at their disposal and being able to choose a correct tool for the correct task. Rust also excels in integrating with other languages - with JS via WebAssembly (a bit of self-promotion, for example), with Elixir via Rustler, with Python via PyO3 and PyOxidizer, etc. So you absolutely can start writing a frontend app with JS, or a distributed system with Elixir, or a data processing/ML app with Python and use Rust to speed up critical parts of those. Or, in reverse, you can start with Rust & add new capabilities to whatever you're building, that being a frontend, a resilient chat interface, or an ML model.

Thank you, although this is not exactly on topic. I'd not heard of PyOxidizer, but it appears to have the same goal as PyInstaller, py2exe, and cx_Freeze -- as the PyOxidizer readme says, it produces

Here is some example Github Action from PyOxidizer as a Kickstarter: https://github.com/indygreg/PyOxidizer/blob/main/.github/workflows/build-exe.yml

A starting point to try out binary modules by the way would be https://github.com/indygreg/PyOxidizer - could already have benefits by rolling in all dependencies of modules (so no more pip/apt/dnf/... installs on target hosts). Setting this up should be relatively straightforward and could probably be automated enough to even manage to build binary modules for all modules in the community ansible distribution eventually.

PyOxidizer might be another option.

XAR signing is effectively just an RFC 5652 CMS signature plus some minimal data structure manipulation. Code at https://github.com/indygreg/PyOxidizer/blob/faa7dfcea5d66bf5....

Mach-O and bundles, by contrast, require a myriad of additional data structures requiring thousands of lines of code to support. To my knowledge, nobody else has implemented signing of these far-more-complicated primitives. (Existing Mach-O signing solutions just do ad-hoc signing and/or don't handle Mach-O in the context of a bundle.)