hadolint VS dhall-lang

To skip the "move your scripts to standalone files" step some devs don't like, consider something like https://github.com/hadolint/hadolint which runs Shellcheck over inline scripts within Containerfiles.

This is neat :)

I love going and making containers smaller and faster to build.

I don't know if it's useful for alpine, but adding a --mount=type=cache argument to the RUN command that `apk add`s might shave a few seconds off rebuilds. Probably not worth it, in your case, unless you're invalidating the cached layer often (adding or removing deps, intentionally building without layer caching to ensure you have the latest packages).

Hadolint is another tool worth checking out if you like spending time messing with Dockerfiles: https://github.com/hadolint/hadolint

With Depot, we make use of two Dockerfile linters, hadolint and a set of Dockerfile linter rules that Semgrep has written to make a bit of a smarter Dockerfile linter.

# Download hadolint wget https://github.com/hadolint/hadolint/releases/download/v2.12.0/hadolint-Linux-x86_64 # Download SHA256 checksum wget https://github.com/hadolint/hadolint/releases/download/v2.12.0/hadolint-Linux-x86_64.sha256 # Validate the checksum sha256sum -c hadolint-Linux-x86_64.sha256 # Make the file executable chmod + ./hadolint-Linux-x86_64 # Rename the file mv hadolint-Linux-x86_64 hadolint

The most common linter I've seen and used it Hadolint, which does: https://github.com/hadolint/hadolint/wiki/DL3002 I didn't bother checking to see if alternatives also support this as well though.

Some discussion on that here:

https://github.com/koalaman/shellcheck/issues/58

The hadolint project does shell checking for Dockerfiles and it uses shellcheck:

https://github.com/hadolint/hadolint

So the approach is definitely feasible, but you do need a new project and probably it needs to be written in Haskell.

how does this compare to something like hadolint?

Also, have you run across Hadolint for linting? https://github.com/hadolint/hadolint

Fail to see how this is any different than Dhall (https://dhall-lang.org/) other than it produces plists too.

Kubernetes config is a decent example. I had ChatGPT generate a representative silly example -- the content doesn't matter so much as the structure:

https://gist.github.com/cstrahan/528b00cd5c3a22e3d8f057bb1a7...

Now consider 100s (if not 1000s) of such files.

I haven't given Pkl an in depth look yet, but I can say that the Industry Standard™ of "simple YAML" + string substitution (with delicate, error prone indentation -- since YAML is indentation sensitive) is easily beat by any of:

- https://jsonnet.org/

- https://nickel-lang.org/

- https://nixos.org/manual/nix/stable/language/index.html

- https://dhall-lang.org/

- (insert many more here, probably including Pkl)

There are underpowered languages / tools, that can only solve a problem for which they are intended poorly. But not all limited tools are like that.

Say, eBPF is prominently not Turing-complete, which allows to guarantee that a eBPF program terminates, and even how soon. Still eBPF is hugely useful in its area.

Or, say, regular expressions are limited to regular languages; in particular, they famously [1] cannot process recursive structures, like trees. Still tools like grep / ag / rg are mightily useful.

Yes, I agree that YAML is underpowered for proper k8s configuration! But it's also too powerful for its own good in other aspects [2]. I wish Google used Dhall [3] or their own purely functional config language (FCL? I already forgot the name) instead of YAML; sadly, they did not.

[1]: https://stackoverflow.com/a/1732454/223424

[2]: https://ruudvanasseldonk.com/2023/01/11/the-yaml-document-fr...

[3]: https://dhall-lang.org/

Dhall: Dhall is a programmable configuration language that combines features like JSON, functions, types, and import capabilities. Its style leans towards functional programming, so if you're familiar with functional-style languages such as Haskell, you might find Dhall to be quite intuitive.

I've been thinking along these lines but more 'strongly validated' than statically typed in the sense that you'd be better off being able to load the entire config and then produce a list of problems (and should be able to offer good editor support if done correctly).

Though https://dhall-lang.org/ demonstrates that you can statically type quite a lot of configuration to great advantage, which appears to be programmatically embeddable in multiple languages per https://docs.dhall-lang.org/howtos/How-to-integrate-Dhall.ht...

> Where practical is in the sense of an engineer (or in their terms, a CS practitioner),

Configuration processing. E.g. I'd like my yamls to be decidable, though I'd settle for guaranteed to halt[1].

[1] https://dhall-lang.org/

Maybe you'd like jsonnet: https://jsonnet.org/

I find it particularly useful for configurations that often have repeated boilerplate, like ansible playbooks or deploying a bunch of "similar-but" services to kubernetes (with https://tanka.dev).

Dhall is also quite interesting, with some tradeoffs: https://dhall-lang.org/

A few years ago I did a small comparison by re-implementing one of my simpler ansible playbooks: https://github.com/retzkek/ansible-dhall-jsonnet

And to checkout Dhall: https://dhall-lang.org/