Our team wants to explore using Lombok annotations (like @14766979, @1889392, @Builder) in Sling Models that we export via Sling Model Exporter in AEM. What are the consequences, best practices, and advantages of using Lombok in this context?
Hi @priyankakh4,
Using Lombok in Sling Models exported through Sling Model Exporter can bring benefits but also has considerations. Here’s a breakdown:
Less Boilerplate: Lombok drastically reduces boilerplate code by auto-generating getters, setters, constructors, builders, and more, making your Sling Models cleaner and easier to maintain.
Consistency: Generates consistent, standard Java bean getters and setters that Sling Model Exporter relies on for JSON serialization.
Improved Readability: Cleaner code helps teams focus on business logic rather than repetitive method definitions.
Supports Jackson Annotations: Lombok works well with Jackson annotations (e.g., @JsonIgnore, @JsonProperty), so you can customize JSON output easily.
Compile-Time Dependency: Lombok generates code only at compile time, so your build process must include Lombok. IDEs need Lombok plugins to avoid showing errors.
Injection Annotations Still Needed: You still need Sling’s @Inject annotations for dependency injection; Lombok doesn’t replace AEM injection.
No-Arg Constructor Requirement: Sling Models require a no-argument constructor. Using Lombok’s @Builder or other constructors must not break this requirement.
Debugging Complexity: Debugging issues can be slightly harder since Lombok-generated code isn’t visible in source, though IDEs typically handle this well.
Team Familiarity: Teams unfamiliar with Lombok may face a learning curve.
Continue using Sling’s injection annotations (@Inject) on fields or constructors.
Avoid removing no-arg constructors if using Lombok builders or all-args constructors.
Annotate either fields or generated getters with Jackson annotations for JSON customization.
Ensure your build system and IDE are configured for Lombok support.
Use Lombok to reduce boilerplate but avoid overusing advanced features that might conflict with Sling’s model adaptation.
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