class-validator VS apollo-server

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.

Another interesting point is that executing fetches on the server can allow developers to more easily leverage caching. Next.js already handles caching out-of-the-box and I’m curious to see if the wider adoption of RSC reduces the need to combine React with solutions like Apollo Server and Apollo Client. While there are other benefits to these tools, RSC could provide similar caching behavior without the need to invest in a GraphQL solution.

There are several GraphQL server implementations, however, for this tutorial, we'll utilize Apollo GraphQL's Apollo Server, a lightweight and flexible JavaScript server that makes it easy to build GraphQL APIs.

As I mentioned, their main GraphQL server package is[1], so that's where the confusion came from. Thanks.

[1] https://github.com/apollographql/apollo-server/blob/9817bc47...

While working on this blog post, I learned that Apollo Server, the most popular GraphQL server for typescript, uses a similar method for adding error codes to GraphQL. It even lets you add custom errors. Hopefully, someday other GraphQL server projects will follow them. Until then, we’ve got a strong indication we took the right approach.

GraphQL is just a schema, there are many different implementations of a GraphQL server, AppSync being one of them. I mentioned Apollo server in this series as well.

After some head-scratching, I opened an issue on Apollo Server’s GitHub repository. There, Apollo Server contributor @​glasser shared a helpful suggestion: why not invoke our AuthPlugin from Apollo Server’s context function? Throwing from context would ensure we can control the HTTP status response without having to introduce more methods and error checks to our AuthPlugin (like unexpectedErrorProcessingRequest). With that suggestion in mind, we rewrote our AuthPlugin as follows:

Apollo as a middleware in Express.js, actually.

Apollo Server 3 Cookie Issue #5775

Lastly, instead of writing our API core ourselves, we'll be using the star of this episode --- Apollo Server (a.k.a. GraphQL server). It has detailed documentation available here.