python-build-standalone VS asdf

It also replaces "just" as a task manager for me which is very pleasant.

The fact that the python plugin uses precompiled Python binaries by default instead of building them from source remove common issues I had with the asdf's python plugin at work with missing dependencies.

Just so you know, I encountered two little quirks that needed a fix:

- [Backspace Key Doesn't work in Python REPL](https://github.com/indygreg/python-build-standalone/blob/mai...)

These builds are an alternative: https://github.com/indygreg/python-build-standalone

Those are what Rye and hatch use.

Drawbacks: late availability of patch versions, various quirks from how they are built (missing readline, missing some build info that self-compiled C python modules might need.)

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.

I'm trying to build a "portable" Python package based on those available from https://github.com/indygreg/python-build-standalone/releases.

I'm a huge fan of https://github.com/indygreg/python-build-standalone which provides Python builds that CAN be moved around and work independently of any other Python installation.

I used that for my own Python+Electron app, which I wrote about here: https://til.simonwillison.net/electron/python-inside-electro...

I used to build my own Pythons that are the same everywhere, now I use indygreg's Python builds. Rye will automatically download and manage Python builds from there. No compiling, no divergence.

One interesting tidbit is that it completely ignores your system Python installations, and instead uses precompiled installations of Python by indygreg from PyOxidizer. This means you don't have to deal with installing Python. It just auto downloads the right builds.

wget https://github.com/indygreg/python-build-standalone/releases/download/20220630/cpython-3.10.5+20220630-x86_64_v3-unknown-linux-gnu-install_only.tar.gz -O - | tar -xz && mv python PortablePython

The lack of Ruby support instantly rings an alarm for me because CPython (on POSIX) also is not relocatable, but is listed as support. Turns pit Hermit is actually using a third-party build script[1] instead of the official one. While the python-build-standalone project is quite awesome and indeed is useful for a lot of things, it has enough quirks I would recommend against any generic package distributor to advertise as Python for general use. This in turn makes me lose most confidence on Hermit, unfortunately.

Be careful if you’re also interested in Hermit. These kinds of things bit you up way down the road when you least expect them to.

[1] https://github.com/indygreg/python-build-standalone

If you really want to be sure, you can download an install_only standalone Python build from https://github.com/indygreg/python-build-standalone/releases and install the libraries with the included pip. Then just tar it again to archive it, and use the included python to run your project. The downloaded wheel you get with pip wheel may depend on the Python version so you just save the wheels you must make sure the Python point version is exactly the same.

The main issue most people have with asdf is that it’s annoyingly slow. Not unusably so, but just enough that it’s irritating.

I identified [0] the source for much of it (sub-shells and pipes) and began a PR [1], but became bogged down with BATS testing, and then found mise / rtx, so kind of lost interest. Sorry. You can always implement these if you’d like.

[0]: https://github.com/asdf-vm/asdf/issues/290#issuecomment-1383...

[1]: https://github.com/asdf-vm/asdf/pull/1441

Or if you need to manage more than just node, asdf has been around for over a decade and works great. You can use a .tool-versions to change runtimes for each project you have, in addition to managing your global runtime versions

https://asdf-vm.com/

Why not just use a tool like asdf (https://asdf-vm.com/) or mise (https://mise.jdx.dev/)?

These tools have the advantage of not being multi-taskers and can manage version for all your tools. You wouldn’t need pyenv and npm and rvm and…

We’ve even started committing the .mise.toml files for projects to our repos. That way, since we work on multiple projects that may need multiple versions of the same tool, it’s handled and documented.

The purpose of a version manager is to help you navigate or install any tools for development easily. Version Manager can be one tool for each dependency (e.g. NVM, g) or One tool for all dependencies (e.g. asdf, mise).

(asdf)[https://asdf-vm.com/] fully supports Python and almost any other language. I've been using it for Ruby, Python, Elixir, and other languages for years and never looked back.

Secondly, our development environments must not drift, because then code may behave differently and a change could pass on our machine but fail in production. There are many tools for locking down environments, e.g nix, pkgx, asdf, containers, etc., and they all share the common goal of being able to lock down dependencies for an environment accurately and deterministically. And that needs to be enforced in our local workflow so we don't have to rely on CI environments for correctness. All developers must have environments that are effectively identical to what runs in CI (which itself should be representative of the production environment).

There are many ways this can be done (e.g nix, pkgx, asdf, containers, etc.), and we won’t get into which specific tools to use, because we'll instead cover the essential essence of preventing environment drift:

I've really been enjoying asdf, which is a program that allows you to install specified versions of dev utilities as well as dynamically manage them via shims and .tool-versions files.