procedural-gl-js VS io-ts

Nice writeup, I always like it when the shaders are highlighted like this. I got started in a similar way 7 years ago and have been making 3D terrains with THREE.js & WebGL since.

The real fun begins when you need to implement some sort of Level-of-Detail system and streaming in data to give the illusion of high detail everywhere without sacrificing performance.

Last year I released an open-source framework (https://github.com/felixpalmer/procedural-gl-js) for creating 3D terrains for web applications, you can see Uluru here: https://www.procedural.eu/map/?longitude=131.036&latitude=-2... (unfortunately the aerial imagery from our default provider isn't as high resolution as other places in Europe)

Great visualization and approach with compressing the tile data. Do you have a comparison of how much smaller the payload ends up being compared to simply sending PNG files?

I use PNGs to encode elevation data in my 3D mapping library (https://github.com/felixpalmer/procedural-gl-js/) and this does a pretty good job of compressing the data, for example in the ocean the PNG files are also very small as the image is mostly black. Different use case I now as your data is much more sparse, but I wonder how close the PNG compression would be compared to your approach.

Yeah, the React parts of this are very minimal. I'm not really sure what using it gets you, since it just manages a single div.

The _actual_ library that does all the work is here: https://github.com/felixpalmer/procedural-gl-js

- Tiny filesize means library is parsed fast. Package size is less than THREE.js thanks to code stripping

Check it out on Github: https://github.com/felixpalmer/procedural-gl-js/

The imagery comes from the Orthofoto dataset on https://www.basemap.at/ - the actual texturing is done by the Procedural GL JS library https://github.com/felixpalmer/procedural-gl-js

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.