wasp VS dhall-lang

We used Wasp’s built-in auth which makes your auth totally yours and independent of any 3rd party service. Under the hood, it uses Lucia and Arctic to give you email, username and multiple OAuth providers out of the box.

Wasp (https://github.com/wasp-lang/wasp) has actually worked out quite well! It just crossed 10k stars on GitHub and is currently the fastest-growing full-stack framework for React & Node.js. It's being used in both startups and enterprises.

Although Wasp has its own DSL/compiler, the secret to its adoption is probably that it works with the existing stack, like React & Node.js. From the developer's perspective, it feels like a framework; the "compiler" part is just what gives it its superpowers.

Another example of a React framework utilizing Vite to give their users a SPA experience is Wasp - a full-stack framework for React & Node.js that drastically cuts the boilerplate. Despite being a full-stack framework, it focuses on the standardized approach of deploying a client-side React app with a Node.js server to be as portable as possible. With this approach, you can deploy your app pretty much anywhere, as well as self-host it, which is also a thing that we mentioned before in this article.

As before, you will be redirected to the application's login page. Click to link to sign up to create a new account. After authenticating, you will be able to access the todo list functionality as before. ## Conclusion In this guide, we demonstrated how to build and deploy a Wasp application to Koyeb. We started with one of Wasp's templates to create a working, full-stack web application backed by a database. We migrated the application's configuration from a local SQLite database to an external PostgreSQL database to prepare for deployment. Afterwards, we created a multi-stage `Dockerfile` to build and configure our various application layers. Finally, we deployed the backend and web app to Koyeb by targeting different stages in the `Dockerfile`. This tutorial covers the basics of how to manage a Wasp project and deploy to a production environment. As you continue to develop your projects, be sure to check out the [Wasp documentation](https://wasp-lang.dev/docs) to learn how to integrate new features, work with the data model, and leverage the development framework to make your life easier.

First off, Wasp is a full-stack React, NodeJS, and Prisma framework with superpowers. It just crossed 10,000 stars on GitHub, and it has been used to create over 50,000 projects.

When building AI Blog Articles, I decided to get started as fast as possible. So I looked for a free boilerplate and stumbled upon Open SaaS, which used YC-backed Wasp. It is a full-stack React + NodeJS + Prisma that takes 8 hours to get started with.

Exactly. Wasp, https://wasp-lang.dev, is the only framework in the React/Node/Prisma space that's taking this opinionated approach to full-stack development.

For example, you get full-stack auth by just adding this to your config file:

`auth.methods: { email: {}, google: {} }`

Then you on-the-fly Auth UI components and all the necessary hooks

If you already have some sort of foundation in programming, use AI and some great abstractions/frameworks to get things done even faster. For example, instead of creating everything from the ground up (and probably suffering on little things along the way) you can skip repeating yourself a ton of times by using Wasp, which is a great React/Node full-stack framework that takes care of managing the boilerplate side of programming for you. 🤯

Aider is one of my favorite AI agents, especially because it can work with existing codebases. We've seen a lot of good results from folks who used it with Wasp (https://github.com/wasp-lang/wasp) - a full-stack web framework I'm working on.

A "marketingy" demo video: https://www.youtube.com/watch?v=DXunbNBpgZg&ab_channel=Wasp

Fail to see how this is any different than Dhall (https://dhall-lang.org/) other than it produces plists too.

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)

There are underpowered languages / tools, that can only solve a problem for which they are intended poorly. But not all limited tools are like that.

Say, eBPF is prominently not Turing-complete, which allows to guarantee that a eBPF program terminates, and even how soon. Still eBPF is hugely useful in its area.

Or, say, regular expressions are limited to regular languages; in particular, they famously [1] cannot process recursive structures, like trees. Still tools like grep / ag / rg are mightily useful.

Yes, I agree that YAML is underpowered for proper k8s configuration! But it's also too powerful for its own good in other aspects [2]. I wish Google used Dhall [3] or their own purely functional config language (FCL? I already forgot the name) instead of YAML; sadly, they did not.

[1]: https://stackoverflow.com/a/1732454/223424

[2]: https://ruudvanasseldonk.com/2023/01/11/the-yaml-document-fr...

[3]: https://dhall-lang.org/

Dhall: Dhall is a programmable configuration language that combines features like JSON, functions, types, and import capabilities. Its style leans towards functional programming, so if you're familiar with functional-style languages such as Haskell, you might find Dhall to be quite intuitive.

I've been thinking along these lines but more 'strongly validated' than statically typed in the sense that you'd be better off being able to load the entire config and then produce a list of problems (and should be able to offer good editor support if done correctly).

Though https://dhall-lang.org/ demonstrates that you can statically type quite a lot of configuration to great advantage, which appears to be programmatically embeddable in multiple languages per https://docs.dhall-lang.org/howtos/How-to-integrate-Dhall.ht...

> Where practical is in the sense of an engineer (or in their terms, a CS practitioner),

Configuration processing. E.g. I'd like my yamls to be decidable, though I'd settle for guaranteed to halt[1].

[1] https://dhall-lang.org/

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

And to checkout Dhall: https://dhall-lang.org/