reflow VS dhall-lang

Reflow [1] is a similar attempt at a slightly different domain: bioinformatics and ETL pipelines. Reflow exposes a data model and programming model that reclaims programmability in these systems, and, by leaning on these abstractions, gives the runtime much more leeway to do interesting things. It unties the hands of the implementer.

[1] https://github.com/grailbio/reflow

https://github.com/grailbio/reflow is the closest that I know, as it has a design that resembles the Bazel build system.

It seems Reflow falls in this category:

https://github.com/grailbio/reflow

> Reflow thus allows scientists and engineers to write straightforward programs and then have them transparently executed in a cloud environment. Programs are automatically parallelized and distributed across multiple machines, and redundant computations (even across runs and users) are eliminated by its memoization cache. Reflow evaluates its programs incrementally: whenever the input data or program changes, only those outputs that depend on the changed data or code are recomputed.

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/