Putting constraints on configuration is a big use case. CUE is much nicer to write than Yaml or JSON, and then you can output those formats for the programs which use the "old" formats. There is a vet command if you want to validate Yaml or JSON before moving to generating them. It has helped me catch errors and I use CUE instead of Helm for a lot of things now. I'm looking into generating Terraform JSON rather than HCL. If there was going to be a language, CUE is preferable to HCL.
Another thing I have been working on is a tool to diff, mask, upsert, and transform config or data files in bulk using CUE. https://github.com/hofstadter-io/cuetuls
I agree that it’s probably nicer than YAML, but that’s a low bar. I’m more interested in whether it’s nicer than something like Starlark (especially a hypothetical statically typed Starlark).
CUE aims to be turing-incomplete, so no programming. This is based on Marcel's experience writing borgcfg and GCL while at Google.
The quote I really like is "wrap code in data, not data in code"
It has a lot to do with readability, maintainability, and being able to write tooling to work with config or data. Think about building a query tool that can find everything in your config using a particular label. With CUE, it is likely to be a one-liner (once the query proposal is implemented)
I agree, but I don't understand the value of the difference.
> CUE aims to be turing-incomplete, so no programming
You could satisfy this property with an imperative language that lacks recursion, unbounded loops, etc; however, I'm not convinced this property is very useful in practice. I've never worked anywhere where this was a real problem.
> Think about building a query tool that can find everything in your config using a particular label.
In an imperative configuration language, I would just `jq` the generated JSON. At least I think that's analogous to your suggestion?
Marcel does a great job of arguing the value of Turing incompleteness. I've collected his talks here: https://cuetorials.com/videos I cannot say it better than he has.
JQ is close to how CUE would solve this. Both are different than an imperative config language, where you would recurse over data. For both JQ and CUE, you would provide a pattern matching "mask" of sorts. With CUE, you can also have a schema built into that mask and ensure that any transformations are still valid. You can also do the same with Yaml, so you get one tool and language to replace jq, yq, and jsonschema.
Cue might actually get bounded recursion, the idea has been thrown around. It ought not invalidate the theory because it can be proved all the way down. You can simulate it today with comprehensions. I've built some structural helpers on the pattern here: https://github.com/hofstadter-io/cuetils
True, though one may turn that around to say Cue's scope is too large while Jsonnet's is more "pure" while still enabling the larger scope.
Schema that describes data is itself just data and Jsonnet can describe both. While the various Jsonnet compilers do not "know" about any specific meta-schema in which to express schema nor of course any way to apply that schema to data for validation, one can create such systems with Jsonnet as the language and its compilers as a component.
True, CUE has quite the inspirational scope right in the name. It is actually what draws me to the language. I also like the theoretical foundations in being turing-incomplete. Functions and computation make configuration harder to understand and reason about.
I mostly generate yaml and json now that I've been using CUE. The cool thing about CUE is that it's really doing both at the same time. Types and values are just points along a spectrum of specificity, going from types to constraints to concrete values.
I found CUE because I needed something better than Yaml for generating code, or declarative application code. (https://github.com/hofstadter-io/hof). It was similar to when I found Go and replaced a bunch of C++. I gained way more functionality in my application while shedding more than 50% of my LOC.
Another thing I have been working on is a tool to diff, mask, upsert, and transform config or data files in bulk using CUE. https://github.com/hofstadter-io/cuetuls