nestedtextto VS jsonnet

I used the official reference implementation to make a CLI converter between NestedText and TOML, JSON, and YAML. When generating one of these formats, you can use yamlpath queries to concisely but explicitly apply supported types to data elements.

I'm a huge fan of NestedText, especially as there is no escaping needed ever.

If you ever want to use it as a pre-format to generate either TOML, JSON, or YAML, I used the official reference implementation to make a CLI converter between them and NestedText.

When generating one of these formats, you can use yamlpath queries to concisely but explicitly apply supported types to data elements.

- My CLI converter: https://github.com/AndydeCleyre/nestedtextto

- yamlpath info: https://github.com/wwkimball/yamlpath/wiki/Search-Expression...

In case you're interested and haven't seen it, I've become a big fan of NestedText, which is similar to YAML but without the complicated parts, and without types (just strings, lists, and dicts). The idea is that any meaningful validation and coercion belongs in code anyway. An extra cool part is that nothing ever needs to be escaped, so the content is super clean and unambiguous.

If you want to play around with it, I made NestedTextTo (nt2 on PyPI), for CLI conversion between NestedText and YAML, TOML, or JSON, with a pretty cool (IMO) way to cast value types along the way.

https://nestedtext.org/en/stable/ (not my project)

https://github.com/AndydeCleyre/nestedtextto (my project)

I recently fell in love with the NestedText format, and whipped up a CLI for conversions between it and YAML (and JSON and TOML), so now whenever manually viewing those other formats I pipe it through into readable NestedText. In this example, the result is identical to format A.

So I made nt2 (NestedTextTo) (install from PyPI as nt2[toml] for TOML support).

jsonnet[1] and kapitan[2] are the tools I currently use. Their learning curve is not optimal (and I tried to contribute to smoothen it with a jsonnet course[3] and a 'get started wit kapitan' blog post[4]), but once used to it it's hard to do without, and their combination makes them even more useful (esp. if you deploy K8s).

In Ruud's case, Jsonnet might have been worth looking at as Hashicorp tools can be configured with json in addition to HCL. But that would have been less fun I guess ;-)

I hope for Ruud it finds its niche, there's quite some competition in this field!

1: https://jsonnet.org/

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)

jsonnet cli: link

Jsonnet: A data template language implemented in C++, suitable for application and tool developers, can generate configuration data and organize, simplify and manage large configurations without side effects.

[Language: Jsonnet] (on GitHub)

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

Apologies for the lack of context, and for missing this comment until today.

Both are tools for defining kubernetes manifests (which are YAML) in a reusable manner.

Jsonnet is a formally specified extension of JSON. It’s essentially a functional programming language (w/some object oriented features) that generates config files in JSON/YAML/etc, so it’s straightforward to determine whether an input file is valid, and to throw an error that points to an exact line if it’s not. It has a high learning curve, especially for people whose only experience is with imperative languages.

https://jsonnet.org/

Helm charts also generate YAML/JSON config files, but they use Go templating. This is easier and faster to understand, since it’s mostly string substitution and not much logic (there’s conditionals, iterators, and very basic helper functions). Unfortunately a simple typo or mistake can cause errors that are difficult to diagnose (the message may indicate a problem far away in code from the actual mistake). It can also generate output that’s valid according to the string templating rules, but not what was intended, which can be very confusing to debug.

Despite these shortcomings, the vast majority of kubernetes applications are distributed as helm charts. I understand why things ended up this way, but I still wish it were more common for people to invest the upfront effort to learn the superior tool, so it could be more widespread.

I like Google's Jsonnet [1], which has all of this except for 4.

Jsonnet is quite mature, with fairly wide language adoption, and has the benefit of supporting expressions, including conditionals, arithmetic, as well as being able to define reusable blocks inside function definitions or external files.

It's not suitable as a serialization format, but great for config. It's popular in some circles, but I'm sad that it has not reached wider adoption.

[1] https://jsonnet.org/