Get spark DataFrame inferred schema with schema.json(), then use this to convert it to scala source (StructType, etc.)

sparkJsonSchemaToStructTypeSource.js

// https://github.com/apache/spark/blob/0494dc90af48ce7da0625485a4dc6917a244d580/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataType.scala#L200

function sparkJsonSchemaToStructTypeSource(json) {
  const types = ["string", "long", "double", "float", "boolean"];

  if (typeof json === "string")
    return `${json[0].toUpperCase()}${json.slice(1)}Type`;

  switch (json.type) {
    case "array":
      return `ArrayType(${sparkJsonSchemaToStructTypeSource(
        json.elementType
      )}, containsNull = ${json.containsNull})`;

    case "struct":
      return `StructType(Array(${json.fields
        .map(
          (f) =>
            `StructField("${f.name}", ${sparkJsonSchemaToStructTypeSource(
              f.type
            )}, nullable = ${f.nullable})`
        )
        .join(", ")}))`;

    case "map":
      return `MapType(${sparkJsonSchemaToStructTypeSource(
        json.keyType
      )}, ${sparkJsonSchemaToStructTypeSource(
        json.valueType
      )}, valueContainsNull = ${json.valueContainsNull})`;

    default:
      console.error(json);
      throw new Error("Unknown type " + json.type);
  }
}