cargo-ebuild VS pyflow

In Gentoo, Rust crates are just normal files to be downloaded in order to build a given package. The package pins (and checks the hashes of) the crate deps, and builds using cargo --offline. There is no serde/clap/etc packages, just ripgrep/librsvg/etc packages. There is no need to patch all packages to use the same serde crate version. Packaging a Rust program in gentoo is pretty much automatic.

Then, I went through like 3 different pages on gentoo and learned how to make my own rebuild using this... But after setting up my custom repo and making sure it had the right permissions, manifest, etc. the ebuild failed on account of not being able to find the Config.yoml file it needed, which exists in the directory I built the ebuild from. I think I am just SOL on this, and will have to probably find a different approach

FWIW it's worth for portage (Gentoo) there is g-sorcery[0], which can create ebuilds for Emacs (m/elpa) and python packages automatically. Similarly there is also cargo-ebuild[1] which can create ebuilds for rust programs/libraries, including a list of all dependencies with hashes.

I've successfully used cargo-ebuild in the past to create ebuilds automatically, it's a breeze. I'd be surprised if similar tools didn't exist for deb/rpm based distros.

[0]:https://github.com/jauhien/g-sorcery

[1]: https://github.com/cardoe/cargo-ebuild

I'm working on a custom repository where I intend to write ebuild files for packages that's not supported by Gentoo's repository. Right now, I'm trying to write an ebuild file for xplr, which is a Rust project that uses the Cargo build system. Initially, I used the cargo-ebuild tool, which generated the file xplr-0.14.3.ebuild.

Maybe you already know, but specifically for making Rust ebuilds and filling the CRATES variable there's a tool cargo-ebuild to automatically extract that from Cargo.toml.

I have zero issues with Gentoo's Rust and Rust-using packages. I use rustup's Rust and cargo install for development, and maintain a gentoo package using cargo ebuild.

Very cool! Of note, I made something along these lines a few years ago, although with a slightly broader scope to also include managing and installing python versions. I abandoned it due to lack of free time, and edge cases breaking things. The major challenge is that Python packages that aren't wheels can do surprising things due to setup.py running arbitrary code. (https://github.com/David-OConnor/pyflow)

Pyflow

Pyflow takes care of the use when you need pyenv to isolate different python versions, pipx to isolate some global python-based tools, and isolated, reproducible builds per project with on tool. I highly recommend people to give it go.

https://github.com/David-OConnor/pyflow#a-thoroughly-biased-...

Pyflow is a similar implementation of PEP582. NGL I wonder if it's better because of how good Rust stuff is. Probably a lot faster. Looks like you can install it via Pypi. I should've tested it before moving to PDM. Though it seems dev is a bit slow. Hmmm.

I’m personally complaining that pip is so much behind cargo. I have some hope with Pyflow though.

I literally stumbled into this issue again today. Has anyone leveraged Pyflow before? It looks pretty slick for keeping things organized. I don't do heavy dev work, just need something to keep things generally tidy. Was curious if anyone had used it and their opinion on it.

PDM is pretty new so it’s not entirely clear how it’ll play out but if you’re interested in PEP 582 then it’s really that or pyflow.

It's a good safeguard, and it's going in the direction of the other initiatives to make python package management default behavior saner.

PEP 852 is the another one to follow up: https://www.python.org/dev/peps/pep-0582/

It basically uses the concept of node_modules, making python interpreters local any local __pypackages__ directory. There are 2 differences though:

- unlike JS, python can only have one version of one lib

- but since having several versions of python often matters, you may have several __pypackages__/X.Y sub dirs to catter to each of them

It does also force you to use "-m" to use commands, which is the best practice anyway. I hope it will make jupyter fix "-m" on windows for them because that's a blocker for beginners.

If you are not already using "-m", start now. It solves a lot of different problems with running python cli programs.

E.G: instead of running "black" or "pylint", do "python -m black" or "python -m pylint". Or course you may want to chose a specific version of python, so "python3.8 -m black" for unix, or "py -3.8 -m black" on windows.

To test out __pypackages__, give a try to the pdm project: https://github.com/pdm-project/pdm

At last, some other tools that I wish people knew more about that solves packaging issues:

- pyflow (https://github.com/David-OConnor/pyflow): it's a package manager like poetry, but it also install whatever python you want like pyenv. Except it provides the binary, no need to compile anything. It's a young project, but I wish it succeeds because it's really a great concept.

- shiv (shiv.readthedocs.io/): it leverage the concept of zipapp, meaning the ability that python has to execute python inside a zip file. It's a successor to pex. Basically it lets you bundle your code + all deps from virtualenv inside a zip, like a Java .war file. You can then run the resulting zip, a .pyz file, like if it was a regular .py file. It will unzip on the first run automatically. It makes deployment almost as easy as with golang.

- nuitka (shiv.readthedocs.io/): take your code and all dependancies, turn them into C, and compiles it. Although it does require a bit of setup, since it needs headers and a compiler, it results reliably in a standalone compiled executable that will run on the same architecture with no need for anything else. Also it will speed up your Python program, up to 4 times.