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Generated APIs for domain-driven development

· 2 min read
TeaQL Code Gen
TeaQL Code Gen
Core Contributor

Domain-driven development breaks down when the domain language disappears from the code path.

That happens easily in data-heavy systems. The model may be discussed in design sessions, but implementation code becomes SQL strings, mapper files, repository methods, DTOs, and service glue.

TeaQL uses generated APIs to keep the domain model visible.

Model First​

TeaQL starts from a domain model:

  • entities;
  • scalar fields;
  • object relations;
  • child lists;
  • constants;
  • validation expectations;
  • data-service targets.

The generator turns that model into APIs. Application code then works with the generated vocabulary instead of reconstructing it by hand.

Queries as Domain Language​

Generated query methods make intent explicit:

Q.orders()
    .filterByMerchant(ctx.getMerchant())
    .selectCustomer(Q.customers().selectName())
    .selectLineItemList(Q.lineItems().selectSku().selectQuantity())
    .countLineItems()
    .executeForList(ctx);

The code names the domain structure:

  • orders;
  • merchant;
  • customer;
  • line items;
  • SKU;
  • quantity.

That is more reviewable than a service method that hides several mapper calls and response transformations.

Relations Matter​

DDD systems are rarely flat. Relations carry meaning:

  • an order has line items;
  • a merchant belongs to a platform;
  • an employee belongs to a department;
  • a ticket has comments and assignments.

TeaQL relation loading APIs give those relationships a generated shape. The runtime can still decide how to execute the load efficiently.

Graph Writes​

Domain changes often arrive as object graphs:

  • create an order with lines;
  • update a parent and merge children;
  • remove a child row;
  • attach an existing reference;
  • keep missing children for a relation that should not delete absent rows.

TeaQL Rust models this through graph nodes, graph operation state, mutation planning, and transaction boundaries. Java TeaQL carries the same high-level idea through entity save and graph-oriented runtime behavior.

Validation and Runtime Policy​

Domain logic is not only data shape. It also includes:

  • required fields;
  • status transitions;
  • tenant rules;
  • permission policy;
  • audit metadata;
  • language-aware validation messages.

TeaQL keeps those concerns near runtime context and generated model hooks instead of scattering them across controllers.

Why Generate?​

Handwritten domain APIs are possible. The problem is consistency.

Generation gives every entity the same baseline:

  • field selectors;
  • filters;
  • relation selectors;
  • aggregate helpers;
  • request builders;
  • checker hooks;
  • behavior hooks;
  • runtime registration.

Teams can then focus on the parts of the domain that are actually special.

The Short Version​

Generated APIs are not a shortcut around domain modeling.

They are a way to make the domain model executable, reviewable, and reusable across application code, runtime providers, and AI coding tools.