joi VS zod

Code in Docusaurus This module validates and processes frontmatter objects by using Joi library for the data validation.

Once you've leaped into thinking as a serverless problem solver, it makes a lot of sense to standardize some tooling and frameworks. The old adage right tool for the job is what I like about this layer of the pyramid. For instance, if a problem requires flexibility in data and your team enjoys validating schema with Joi then you might use TypeScript with a Node.js runtime with your lambdas. If you prefer the developer experience and small footprint and simplicity of Go then use the Go 1.x runtime. You might find you don't need "compute" at all, so using intrinsic functions in State Machines might be plenty.

Validation: request data validation using Joi

I'm using Joi on my server to validate form input, do you think I still need honeypot fields? It sounds like it might be worth looking into IP rate limiting as well, I don't think Joi can help with that.

What does your library provide that others don't? For example: https://github.com/colinhacks/zodhttps://github.com/hapijs/joihttps://github.com/jquense/yuphttps://github.com/gcanti/io-tshttps://github.com/pelotom/runtypeshttps://github.com/sindresorhus/ow

Yup's API is heavily inspired by Joi, but leaner and built with client-side validation as its primary use-case. Yup separates the parsing and validating functions into separate steps. cast() transforms data while validate checks that the input is the correct shape. Each can be performed together (such as HTML form validation) or seperately (such as deserializing trusted data from APIs).

Yup is a Javascript object schema validator: it lets you define a schema to describe how a valid object should look like, and allows you to validate an object using this schema. If you know Joi, Yup is heavily inspired by it, except it relies on client-side validation as its primary use-case.

Again a widely used open source validation library like Joi can help you easily create schemas and transform the data into safe objects.

[Zod Documentation](https://zod.dev/) [Zod Error Handling](https://zod.dev/ERROR_HANDLING?id=error-handling-in-zod) [React-Hook-Form Documentation](https://react-hook-form.com/get-started) [Hookform Resolvers](https://www.npmjs.com/package/@hookform/resolvers)

This is a very fair comment, and you seem open to understanding why types are useful.

"problems that are due to typing" is a very difficult thing to unpack because types can mean _so_ many things.

Static types are absolutely useless (and, really, a net negative) if you're not using them well.

Types don't help if you don't spend the time modeling with the type system. You can use the type system to your advantage to prevent invalid states from being represented _at all_.

As an example, consider a music player that keeps track of the current song and the current position in the song.

If you model this naively you might do something like: https://gist.github.com/shepherdjerred/d0f57c99bfd69cf9eada4...

In the example above you _are_ using types. It might not be obvious that some of these issues can be solved with stronger types, that is, you might say that "You rarely see problems that are due to typing".

Here's an example where the type system can give you a lot more safety: https://gist.github.com/shepherdjerred/0976bc9d86f0a19a75757...

You'll notice that this kind of safety is pretty limited. If you're going to write a music app, you'll probably need API calls, local storage, URL routes, etc.

TypeScript's typechecking ends at the "boundaries" of the type system, e.g. it cannot automatically typecheck your fetch or localStorage calls return the correct types. If you're casting, you're bypassing the type systems and making it worthless. Runtime type checking libraries like Zod [0] can take care of this for you and are able to typecheck at the boundaries of your app so that the type system can work _extremely_ well.

[0]: https://zod.dev/ note: I mentioned Zod because I like it. There are _many_ similar libraries.

Zod is an open-source schema declaration and validation library that emphasizes TypeScript. It can refer to any data type, from simple to complex. Zod eliminates duplicative type declarations by inferring static TypeScript types and allows easy composition of complex data structures from simpler ones. It has no dependencies, is compatible with Node.js and modern browsers, and has a concise, chainable interface. Zod is lightweight (8kb when zipped), immutable, with methods returning new instances. It encourages parsing over validation and is not limited to TypeScript but works well with JavaScript as well.

Zod is a TypeScript-first schema declaration and validation library. It helps create schemas for any data type and is very developer-friendly. Zod has the functional approach of "parse, don't validate." It supports coercion in all primitive types.

Link: https://zod.dev/

You can check out their documentation here.

You can learn more about Zod on their website here.

In JS, it's a good idea anyway to use some JSON parsing library instead of JSON.parse.

With Zod, you can use z.bigint() parser. If you take the "parse any JSON" snippet https://zod.dev/?id=json-type and change z.number() to z.bigint(), it should do what you are looking for.

We will validate our input using client-side zod. Zod handles TypeScript-first schema validation with static type inference. This means that it will not only validate your fields, it will also set types on validated fields.