ts-simple-type VS io-ts

We use an internal validator library that we infer request types from. It’s similar to Zod (but also predates it by a year).

I’ve also spent some time on a Typescript type to X compiler. My first prototype is open source and targets Thrift, Proto3, Python, and JSON schema: https://github.com/justjake/ts-simple-type/tree/main/src/com...

I’m not happy with the design decision in that codebase to try to “simplify” Typescript types before compiling, and probably won’t continue that implementation, but we have a few internal code generators that consume TS types and output test data builders and model clases we use in production.

After some frustration with the TypeScript schema library ecosystem, I've decided that I'd prefer to declare my types using TypeScript's excellent type syntax, so I can take advantage of generics, mapped types, etc. Then, I'll take those TypeScript types and compile them to whatever alternative schema format I need.

There are many libraries that claim to convert your Typescript types to other formats, such as ts-json-schema-generator, ts-to-zod, or typeconv/core-types-ts. These libraries work by interpreting the Typescript AST, essentially re-implementing a bare-bones type system from scratch. Most do not support advanced Typescript features like generic application, mapped types, or string literal types. So, what's the point? To avoid those limitations, I use Typescript's first-party ts.TypeChecker API to analyze types, and an existing library called ts-simple-type (which I've forked) to convert from ts.Type to a more usable intermediate format. Then, I recurse over the intermediate format and emit "AST nodes". It's pretty simple, but seems promising.

So far, I have compilers from TypeScript type to Python 3 and Thrift. But I plan to add OpenAPI/JSONSchema, Protobuf (Proto3), Kotlin, Swift, and maybe Zod and Avro. Each target language is around ~300 LoC so they're pretty easy to put together.

Repo: https://github.com/justjake/ts-simple-type

Compiler input and output: https://github.com/justjake/ts-simple-type/blob/jake--compil...

Thrift compiler: https://github.com/justjake/ts-simple-type/blob/jake--compil...

Python compiler: https://github.com/justjake/ts-simple-type/blob/jake--compil...

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.