Build Your Own DSL in Six Steps with Langium

About fifteen years ago the author first touched compiler construction, and now revisits the challenge with modern tools. Using the ZModel DSL (a superset of Prisma Schema Language) as a concrete example, the article shows how to define a language, compile a sample model, and progressively refine it.

Step 1 – From Text to AST

Lexical analysis splits source text into tokens (ID, STRING) and a parser builds an abstract syntax tree (AST). Langium, a TypeScript‑based language engineering framework, combines these steps.

model User {
  id Int
  name String
  posts Post[]
}

model Post {
  id Int
  title String
  author User
  published Boolean
  @@allow('read', published == true)
}

Step 2 – From AST to Linked Tree

After parsing, a linking pass resolves cross‑references (e.g., posts referencing Post) turning the tree into a graph. Langium automatically builds scopes and resolves names, but custom linking logic can be added when needed.

// Example of a custom linking service (simplified)</nexport function registerLinking(services: ZModelServices) {
  const linker = services.linker;
  // custom logic here
}

Step 3 – Semantic Validation

Syntax errors stop compilation, but semantic errors require explicit checks. Langium lets you register validation hooks that examine nodes and report problems.

export function registerValidationChecks(services: ZModelServices) {
  const registry = services.validation.ValidationRegistry;
  const validator = services.validation.ZModelValidator;
  const checks: ValidationChecks<ZModelAstType> = {
    SimpleExpression: validator.checkExpression,
  };
  registry.register(checks, validator);
}

export class ZModelValidator {
  checkExpression(expr: SimpleExpression, accept: ValidationAcceptor) {
    if (isFieldReference(expr) && expr.target?.type !== 'Boolean') {
      accept('error', 'Only boolean fields are allowed in conditions', { node: expr });
    }
  }
}

Step 4 – Improving Developer Experience

Good IDE support (syntax highlighting, auto‑completion, error reporting) is achieved because Langium generates a Language Server Protocol (LSP) implementation that works with VS Code and JetBrains IDEs. Custom LSP extensions can further enhance the experience.

Step 5 – Making the Language Useful

After a clean, error‑free AST you can either expose the tree, translate it to another language (e.g., Prisma schema), implement a plug‑in conversion mechanism, or build a runtime interpreter to execute the model directly.

Step 6 – Adoption

Finally, the article encourages sharing the language with others, noting that the hardest part is convincing users to adopt it.

Author: Cao Yiming, founder of ZenStack and senior architect.