bcl VS cue

Another take on replacing HCL with something more sensible:

BCL https://github.com/wkhere/bcl

I agree with you that HCL sucks when it comes to variables.

Other thing that is funny: no user-defined functions, being unable to use function calls in string interpolations, but allowing variables... so it is like saying: we have this parser and at some points it allows expressions, at some other point not. This seems wrong.

At the same time I agree or at least understand original author's intent to squeeze HCL to maxinum. There is something appealing in HCL visual form, at least when defining resources. Maybe it's just (almost) simplest form of defining such structures that can exists.

This is why I started to work on my own format for configuration, visually similar but with different model of evaluation.

Here is the first attempt: https://github.com/wkhere/bcl

Disclaimer: I named it BCL, 'B' stands for Basic, to somehow relate to HCL and make it easily pronounced. But later I discovered that another BCL is used as Google to configure the Borg platform and seems to be massively hated ;) So I look for the better name..

I am crafting BCL, own configuration language.

https://github.com/wkhere/bcl

I started this when I was unable to squeeze certain usage patterns from HCL, like: variables living in the same scope as the file, evaluating variables in one pass with parsing, easily using external (environment) variables; plus, a simplified syntax.

The implementation is mostly done: you can defined blocks holding key-value pairs and use numerical, string and bool expressions in them. I will add lists and nested blocks.

At this very moment I am rewriting a parser from yacc-based to a Pratt top-down parser with vm, heavily inspired by the excellent book "Crafting Interpreters".

https://github.com/wkhere/bcl

Will not immediately help for all of YAML usages, but at least for defining resources in a Terraform-like style. In fact, it's already it's already helpful as a replacement for HCL in one internal project, that was a final motivation to hack it.

In a bigger picture, I have no idea how to help with YAML omnipresence in Kubernetes. More than a half of my problems in a $daily_job is how crude is consolidating a final Helm chart from different sources. I am not saying that Helm would be inherently a bad tool or my company has chosen pretty bad way of using it - I guess everyone is doing their best considering the ciscumstances. But manipulating textual templates is just too error prone, and the detection of errors happens too late. I dare to say - Kubernetes would do much better with custom format based on a C-like syntax, instead if trying to prove how cool YAML is, especially when it isn't.

Related:

just few days ago I crafted together some ideas i had couple of years already for a configuration language, syntactically like HCL but without HashiCorps idiosyncrasies.

Here it goes, BCL (_Basic_ Configuration Language, for a lack of better name yet), Go prototype, I can code Python port and possibly several other as well..

https://github.com/wkhere/bcl

If you are in a situation where you have a backend and you want to expose an API and then you would eventually want a client, you would need format specs as the starting point where server and clients are generated from that one source.

At the moment, OpenAPI with YAML is the only way to go but you can't easily split the spec into separate files as you would do any program with packages, modules and what not.

There are third party tools[0] which are archived and the libraries they depend upon are up for adoption.

In that space, either you can use something like cue language 1] or something like TypeSpec which is purpose built for this so yet, this seems like a great tool although I have not tried it yet myself.

[0]. https://github.com/APIDevTools/swagger-cli

[1]. https://cuelang.org/

EDIT: formating

Where `kube.cue` sets reasonable defaults (e.g. image is /). The "cluster" runs on a mini PC in my basement, and I have a small Digital Ocean VM with a static IP acting as an ingress (networking via Tailscale). Backups to cloud storage with restic, alerting/monitoring with Prometheus/Grafana, Caddy/Tailscale for local ingress.

[1] https://www.talos.dev/

[2] https://cuelang.org/

I've been somewhat surprised that CUE bills itself as "tooling friendly" and doesn't yet have a language server- the number one bit of tooling most devs use for a particular language.

I'm assuming it's becaus CUE is still unstable?

Anyway, if others are interested in CUE's LSP work, I think https://github.com/cue-lang/cue/issues/142 is the issue to subscribe to

This is where I usually pitch in with "Have your heard of CUELang, our lord and savior?": https://cuelang.org/

- Not turing complete

CUE: The core problem CUE solves is "type checking", which is mainly used in configuration constraint verification scenarios and simple cloud native configuration scenarios.

If you really want executable configurations please consider a newer language like https://dascript.org or https://cuelang.org which provide better type safety.

1- https://news.ycombinator.com/item?id=38030778

Markdown and XML are nice, but what about more advanced documentation formats like OpenAPI? For one recent project, I set up automatic generation of the OpenAPI docs from (much more compact and flexible) CUE definitions (https://cuelang.org/) - which has the bonus of also being able to test the API against the definitions. JetBrains has a CUE plugin, but it's really barebones (doesn't even support jumping from the usage of a schema to its definition). Of course the possibilities when generating docs are endless (just think of the various syntaxes for doc comments, embedding examples/tests in source code etc.)...

It doesn't include validators for TOML and INI, but if you're doing JSON and YAML, I would take a look at using or building upon CUE (https://cuelang.org/). It is a different take on schema definition (plus more), and is surprising terse and powerful model.