infernu VS io-ts

Or maybe a sound type system can only be achieved either by limiting JavaScript or with a different language that compiles to JavaScript?

Very constrained. Since "constraints liberate, liberties constrain", as Bjarnason said. Inspired by Golang's minimalism, and Elm's guardrails. For learnability and maintainability. Since discipline doesn't scale (obligatory xkcd: with too much power, and the wrong nudges, all it takes is a moment of laziness/crunch-time to corrupt a strong foundation), and a complex language affords nerd-sniping kinds of puzzles, and bikeshedding and idiomatic analysis-paralysis. Counter-inspired by Haskell. The virtue of functional programming is that it subtracts features that are too-powerful/footguns (compared to OOP), namely: mutation & side-effects. The language designers should take care of and standardize all the idiomacy (natural modes of expression in the language). "Inside every big ugly language there is a small beautiful language trying to come out." -- sinelaw. The language should assume the developer is an unexperienced, lazy, (immediately) forgetful, and habitual creature. As long as software development is done by mere humans. This assumption sets the bar (the worst case), and is a good principle for DX, as well as UX. The constrained nature of the language should allow for quick learning and proficiency. Complexity should lie in the system and domain, not the language. When the language restricts what can be done, it's easier to understand what was done (a smaller space of possibilities reduces ambiguity and increases predictability, which gives speed for everyone, at a small initial learning cost). The language should avoid Pit of Despair programming, and leave the programmer in the Pit of Success: where its rules encourage you to write correct code in the first place. Inspired by Eric Lippert, but also by Rust.

Qué rico. Si tenés chance meté un proceso de code review fuerte, y para el tema de I/O probá a usar https://github.com/Effect-TS/schema ó https://github.com/gcanti/io-ts que les da una solución obvia al tema de "tipos para lo que devuelva el backend", aunque es en realidad mucho más capaz que eso.

My fave is still io-ts (https://github.com/gcanti/io-ts/blob/master/docs/index.md) as I find it more flexible than zod at the ingress. The author is also working on the Effect ecosystem which also looks interesting.

I’ve been using io-ts for this and been very happy with it. [1] It’s similar to Swift’s Coding protocol in case you’re familiar.

[1] https://gcanti.github.io/io-ts/

Yeah, there are a few new concepts and it's not the easiest to pick up right away. The best introduction is here on the main documentation page.

We use https://github.com/gcanti/io-ts/blob/master/Decoder.md which has a very similar interface. It can even be used to mutate the data using https://github.com/gcanti/io-ts/blob/master/Decoder.md#the-parse-combinator.

A good way to significantly improve the reliability of your app is via improving type-safety by moving away from using any to unknown. One relevant example could be when you type your backend responses and when stringifying JSON to using unknown combined with some sort of runtime type checking. It can be done either by using built-in functionality like type guards or using an external library like io-ts, zod or yup.

Usage of TypeBox is similar with io-ts and zod, but it is much powerful and faster than them. Also, TypeBox can generate JSON schema very easily. Therefore, if you're looking for a validator library for new project and not suffering from legacy codes, I think TypeBox would be much better choice than io-ts and zod. TypeBox can totally replace them.

This check can be done with different libraries like: io-ts, typebox, or zod. These libraries allow you to create objects that represent your typescript definitions. Then, these objects can be used at runtime to validate the received data, in addition, you can also convert this object to a Typescript definition to have all the benefits of using typescript. These objects can be called schema validations because they are responsible for the data validation.