github-desktop
rules_jsonnet
github-desktop | rules_jsonnet | |
---|---|---|
1 | 1 | |
1 | 64 | |
- | - | |
0.0 | 6.7 | |
6 months ago | 24 days ago | |
TypeScript | Starlark | |
MIT License | Apache License 2.0 |
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github-desktop
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Jsonnet – The Data Templating Language
Yes that's a common problem with config languages. They're torn between competing priorities:
1. Fast to parse with a small engine, good error messages, safe to evaluate.
2. Powerful, can express config with arbitrary logic.
In Conveyor we try an alternative approach. The config is HOCON, which is a superset of JSON syntax designed for human readability/writability/convenience first and foremost, so it's got a very nice and clean feel to it. You can see an example here:
https://github.com/hydraulic-software/github-desktop/blob/co...
It can be parsed with a normal-sized config library and the errors you get are reasonable.
But then what if you hit the limits of what it can express? We added support for "hashbang includes":
include "#!script.js"
rules_jsonnet
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Jsonnet – The Data Templating Language
I can definitely sympathize here - in every context, just straight JSON/YAML configuration seems never expressive enough, but the tooling created in response always seems to come with sharp edges.
Here are some of the things I appreciate about Jsonnet:
- It evals to JSON, so even though the semantics of the language are confusing, it is reasonably easy to eval and iterate on some Jsonnet until it emits what one is expecting - and after that, it's easy to create some validation tests so that regressions don't occur.
- It takes advantage of the fact that JSON is a lowest-common-denominator for many data serialization formats. YAML is technically a superset of JSON, so valid JSON is also valid YAML. Proto3 messages have a canonical JSON representation, so JSON can also adhere to protobuf schemas. This covers most "serialized data structure" use-cases I typically encounter (TOML and HCL are outliers, but many tools that accept those also accept equivalent JSON). This means that with a little bit of build-tool duct-taping, Jsonnet can be used to generate configurations for a wide variety of tooling.
- Jsonnet is itself a superset of JSON - so those more willing to write verbose JSON than learn Jsonnet can still write JSON that someone else can import/use elsewhere. Using Jsonnet does not preclude falling back to JSON.
- The tooling works well - installing the Jsonnet VSCode plugin brings in a code formatter that does an excellent job, and rules_jsonnet[0] provides good bazel integration, if that's your thing.
I'm excited about Jsonnet because now as long as other tool authors decide to consume JSON, I can more easily abstract away their verbosity without writing a purpose-built tool (looking at you, Kubernetes) without resorting to text templating (ahem Helm). Jsonnet might just be my "one JSON-generation language to rule them all"!
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Though if Starlark is your thing, do checkout out skycfg[1]
[0] - https://github.com/bazelbuild/rules_jsonnet
[1] - https://github.com/stripe/skycfg
What are some alternatives?
kubectl-neat-diff - De-clutter your kubectl diff output using kubectl-neat
skycfg - Skycfg is an extension library for the Starlark language that adds support for constructing Protocol Buffer messages.
kubecfg - A tool for managing complex enterprise Kubernetes environments as code.
isopod - An expressive DSL and framework for Kubernetes configuration without YAML
sprig - Useful template functions for Go templates.
ursonnet - experimental ur-cause tracer for jsonnet
hof - Framework that joins data models, schemas, code generation, and a task engine. Language and technology agnostic.
aperture - Rate limiting, caching, and request prioritization for modern workloads
nickel - Better configuration for less
cue - The home of the CUE language! Validate and define text-based and dynamic configuration
jsonnet - Jsonnet - The data templating language