recursion-schemes
jsonnet
recursion-schemes | jsonnet | |
---|---|---|
20 | 48 | |
335 | 6,763 | |
0.3% | 0.5% | |
4.3 | 8.4 | |
22 days ago | 11 days ago | |
Haskell | Jsonnet | |
BSD 2-clause "Simplified" License | Apache License 2.0 |
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recursion-schemes
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-❄️- 2023 Day 4 Solutions -❄️-
Reasonably proud of my part 2 solution, although would like to try using a recursion scheme rather than unstructured recursion:
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Interactive animations
Yeah, that project is pretty much at the bottom of my list, unfortunately. My top projects these days are mgmt, klister, recursion-schemes, and hint... And that's already too much!
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Science of Recursion
In a programming context, recursion schemes can be used to write recursive (or corecursive) functions, by automating/abstracting away the common boilerplate part of actually doing the recursion. They take the form of polymorphic higher-order functions, which can be imported from a library like this classic one.
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Is there a way to avoid call overhead?
Maybe I didn't link the best post. It is unfortunately the only one I know that uses Rust. If you are able to read Haskell, the documentation for the recursion-schemes package might be a better resource?
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Ah yes I love arrays with a length of infinity!!!
Writing something as a type of fold over an infinite sequence is nicer than using recursion directly in my opinion. See: https://hackage.haskell.org/package/recursion-schemes
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Tips on mastering recursion and trees and shit?
Consider recursion schemes! It let's you separate the logic of how your recursion is structured on your data, and the logic of what you're doing on each recursion stage. So e.g. you can write the core logic of a recursive linked list summation as just fun x accum -> x + accum, and then you just find the appropriate recursion scheme to pipe the list values into x and handle recursing to build accum (a catamorphism in this case)
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So you come across an undocumented library…
It's a pretty complicated bug, documented in details at https://github.com/recursion-schemes/recursion-schemes/issues/50
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Beautiful ideas in programming: generators and continuations
It’s also trivial and easy in Haskell — you just need an instance of `Foldable` or `Traversable` on your collection, and then you can fold or traverse it in a configurable way. Or for recursive structures, use https://hackage.haskell.org/package/recursion-schemes. Or even just pass a traversal function as an argument for maximum flexibility.
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fromMaybe is Just a fold
https://hackage.haskell.org/package/recursion-schemes is the "normal" library for this type of generalized folding. It even contains Base instances for Maybe and Either.
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Annotation via anamorphism?
I've been working on a system which uses recursion-schemes to annotate a recursive type. The annotated tree itself is pretty simple; at each level, we pair the annotation with the base functor, or
jsonnet
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A Reasonable Configuration Language
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/
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Pkl, a Programming Language for Configuration
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)
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Introduction to Jsonnet: The YAML/JSON templating language
jsonnet cli: link
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10 Ways for Kubernetes Declarative Configuration Management
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.
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-❄️- 2023 Day 4 Solutions -❄️-
[Language: Jsonnet] (on GitHub)
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What Is Wrong with TOML?
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
- Show HN: Keep – GitHub Actions for your monitoring tools
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That people produce HTML with string templates is telling us something
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.
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TOML: Tom's Obvious Minimal Language
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/
- Jsonnet – The Data Templating Language
What are some alternatives?
distributed-process-platform - DEPRECATED (Cloud Haskell Platform) in favor of distributed-process-extras, distributed-process-async, distributed-process-client-server, distributed-process-registry, distributed-process-supervisor, distributed-process-task and distributed-process-execution
kube-libsonnet - Bitnami's jsonnet library for building Kubernetes manifests
record - Anonymous records
dhall-lang - Maintainable configuration files
unliftio - The MonadUnliftIO typeclass for unlifting monads to IO
cue - CUE has moved to https://github.com/cue-lang/cue
machines - Networks of composable stream transducers
cue - The home of the CUE language! Validate and define text-based and dynamic configuration
chr-core - Constraint Handling Rules
json5 - JSON5 — JSON for Humans
pipes-core - Compositional pipelines
cdk8s - Define Kubernetes native apps and abstractions using object-oriented programming