Filtering Database Query with Multiple Checkboxes
You can use multiple checkboxes in order to filter your database queries. In our example we already created a server action with database query which shows the
Filter Query with Multiple Checkboxes
Section titled “Filter Query with Multiple Checkboxes”Use checkbox-driven filtering when users need multi-select narrowing without losing track of which conditions are active.
Introduction
Section titled “Introduction”Checkbox-driven filtering is useful when users need to combine several conditions at once without building complex search syntax in their head. In Wappler, the challenge is keeping the selected conditions readable, making the filtered result understandable, and avoiding stale checkbox state when the rest of the view changes.
Keep multi-select filters understandable
Section titled “Keep multi-select filters understandable”The more active filters a page allows, the more important clarity becomes.
Show active filter state
Section titled “Show active filter state”Users should be able to tell which boxes are shaping the result without scanning the whole panel repeatedly. Active state needs to stay obvious.
Design for combinations, not isolated toggles
Section titled “Design for combinations, not isolated toggles”Each checkbox may seem simple on its own, but the real behavior appears when users select several at once. Make sure the combined result still feels explainable.
Make clearing and recovery easy
Section titled “Make clearing and recovery easy”Multi-select filters should be easy to undo. A user who over-filters should be able to back out quickly instead of unpicking a maze of state.
Next steps
Section titled “Next steps”Checkbox filters pair naturally with dynamic checkbox state, sortable tables, and explicit no-results messaging.
Core components
Section titled “Core components”Data-oriented building blocks: data components and common data sources.
Core components
Section titled “Core components”Choose a Core components tour to start. These tours cover App Connect’s foundational data pieces—Variables/Arrays/Toggles, and common sources like Data Stores and derived datasets.