assert-combinators VS io-ts

We use in prod variant of no 1. [0]. Why? Because:

* it's extremely lightweight (built on pure, functional combinators)

* it allows us to use more complex patterns ie. convention where every json field ends with Json which is automatically parsed; which, unlike datatype alone, allows us to create composable query to fetch arbitrarily nested graphs and promoting single [$] key ie. to return list of emails as `string[]` not `{ email: string }[]` with `select email as [$] from Users` etc.

* has convenience combinators for things like constructing where clauses from monodb like queries

* all usual queries like CRUD, exists etc. and some more complex ie. insertIgnore, merge1n etc has convenient api

We resort to runtime type assertions [1] which works well for this and all other i/o; runtime type assertions are necessary for cases when your running service is incorrectly attached to old or future remote schema (there are other protections against it but still happens).

[0] https://github.com/appliedblockchain/tsql

[1] https://github.com/appliedblockchain/assert-combinators

We use not so much frameworks but combination of lightweight libraries:

- runtime assertions [0] - to map unknown values at i/o boundary into statically typed code (rpc input parameters, sql results etc)

- template based sql combinators to sanitize sql/generate sql [1]

- jsonrpc over websockets - for bidirectional comms between f/e and b/e

[0] https://github.com/appliedblockchain/assert-combinators

[1] https://github.com/appliedblockchain/tsql

Types can be asserted at runtime (parsed) at IO boundaries (reading http request or response, websocket message, parsing json file etc). Once they enter statically type system they don't need to be asserted again.

The difference it makes is illusion of type-safety vs type-safety this article touches on.

You can try to bind service with client somehow but in many cases this will fail in production as you can't guarantee paired versioning, due to normal situations by design of your architecture or temporary mid-deployment state or other team doing something they were not suppose to do etc. It's hard to avoid runtime parsing in general.

Functional combinators [0] or faster [1] with predicate/assert semantics work very well with typescript, which is very pleasant language to work with.

[0] https://github.com/appliedblockchain/assert-combinators

[1] https://github.com/preludejs/refute

Once i/o boundaries are parsing unknown types into static types, your type safety is guaranteed.

[0] https://github.com/appliedblockchain/assert-combinators

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.