class-validator VS typebox

You can learn more from the documentation here.

This is the request body when creating a new task. The IsString decorator provided by class-validator rejects all types other than strings, including undefined or null. The task name value object does not consider the possibility of values other than strings.

In this class, we are using the famous class-validator to decorate our request parameters. This way it is more clear how we are going to use our request object and everything.

We add validation using https://github.com/typestack/class-validator.

I will make sure we get this documented.

Also OP can check out class-transformer + class-validator if he want to properly instantiate objects and validate them with precise and verbose output of potential format errors. OP can even go the god tier way by setting up a custom RxJS operator that does that for him easily.

Start by installing the class-transformer and class-validator packages for dto validation (see more in the docs), sharp for image optimization, and the S3 client packages.

The description of the request body model in NestJS is similar to the description of Ditsmod models, but NestJS uses decorators provided by the utility class-validator. In NestJS, it is customary to name the request body model with the ending *Dto (this is an abbreviation of Data transfer object):

You could use Zod or Superstruct to validate the types of values, or use typestack/class-validator if it makes sense.

Also, title of before article was I made 1,000x faster TypeScript validator library, but today's benchmark is showing that typescript-json is maximum 6,500x times faster. It's just because I added a new library class-validator in the benchmark and it is much slower than previous zod. Of course, I've continuously tuned the performance, but it just improved the performance about 2x times only.

The documentation can be found here.

So far I like the commonly used approach in the Typescript community best:

1. Create your Schema using https://zod.dev or https://github.com/sinclairzx81/typebox

2. Generate your Types from the schema. It's very simple to create partial or composite types, e.g. UpdateModel, InsertModels, Arrays of them, etc.

3. Most modern Frameworks have first class support for validation, like is a great example Fastify (with typebox). Just reuse your schema definition.

That is very easy, obvious and effective.

There's a ton of schema validators out there and most devs have their personal favorite. Mine was zod and is now typebox + ajv.

If you're willing to document your API with an OpenAPI schema, then it should be possible to generate TypeScript types based on the OpenAPI schema with something like openapi-typescript. Also, Typebox can generate JSON schemas, maybe it can be used to generate something that the front-end can also use?

Well, I do provide extensibility for those bullet points you've listed to varying degrees (both schema and type representation), as well as offering a reference implementation for expressing a entirely different schema specification under the type system (specifically RFC8927 / JSON Type Definition). Reference implementation here. As for JSDoc, It's supported in code hints.

In setting out to build this service, we wanted to use gRPC for its APIs. We’ve been reaching for REST when building APIs so far, primarily out of necessity, i.e., our public APIs needed auto-generated client SDKs and docs for developers working with them. We built those APIs with Fastify and Typebox but felt burned by a code-first approach to generating an OpenAPI spec. I’ll spare you the details and save that experience/learning for another article. Suffice it to say we love gRPC’s schema-first approach. This blog post summarizes our feelings well