The Story of DataGoblin

The story starts with me sitting at my desk, working on my mod, RubyMod, and being very bored. I was working on implementing JSON asset generation (AKA datagen) for my mod's loot tables, and I thought - "There must be a better way to do this."

I remembered a talk by Hadi Hariri I watched about Kotlin DSLs, and how you can create "mini-languages" in Kotlin using 3 language features:

  • Extension Functions
  • Lambdas with Receivers
  • Trailing Lambdas

TL;DR of those 3 features, respectively:

  • Extension functions allow you to add a function to class as if it was a regular member.
  • Lambdas with receivers use their receiver type as the type of this, scoped inside the lambda.
  • If the last parameter of a function is a lambda, it can be moved outside the parenthesis, for a conciser syntax.

What does DataGoblin actually do?

DataGoblin isn't a project on its own, but a collection of Kotlin DSLs (all of which can be installed separately) made to create idiomatic Kotlin code for MinecraftForge datagen.

As for the time of writing (will be updated in the future), DataGoblin has 2 DSLs: LootGoblin and ModelGoblin.


LootGoblin was the first DSL I created, and it (as the name suggests) creates loot tables. Loot tables were the perfect candidate to make a Kotlin DSL for - the internal system used to create them normally is already very similar to their JSON counterparts, and a Kotlin DSL would help bridge that gap even further.

I got to work, and finished with this:

lootTable(LootParameterSets.BLOCK) {
    // optional parameter - defaults to 1
    pool(rolls = 2) {
        itemEntry(Items.STICK) {
            function { explosionDecay() }

        function {
            // this is a shortened form of setCount(constantCount(2))

A beautiful version of loot tables, all type-safe, made in pure Kotlin code.


ModelGoblin came around about the same way as LootGoblin - only this time I was. I've "borrowed" my old code, and was ready to create another rendition of Kotlin DSLs for Minecraft data generation.

After about a week of work, I've learned some lessons:

  • Models are way more complex than loot tables.
  • Taking my old code was a huge time-saver.
  • I should make more of these.

So what's next?

I'll probably get around to making DSLs for all kinds of data gen:

  • Tags
  • Recipes
  • Item Models
  • World Generation (Dimensions, Dimension types, Biomes, etc.)
  • Entity Models, using @SizableShrimp's EntityModelJson library
  • etc…

But for now, this is not too bad.