data-fetching

Manage data fetching by centralizing API interactions in a service layer, binding SWR hooks to a Zustand store, and triggering SWR cache invalidation after mutations to ensure UI consistency. This pattern reliably synchronizes remote data across list and detail views.

The best way to structure a service layer for data fetching is to encapsulate all API calls within typed, reusable service methods. This isolates network logic from the UI, allowing Zustand and SWR to handle state and caching predictably without scattering fetch logic across components.

Yes, you can apply optimistic updates to list and detail UIs by mutating the local Zustand state immediately and leveraging SWR's cache invalidation. This approach provides instant UI feedback while safely synchronizing the remote data upon successful API resolution.

You need a dedicated store pattern for remote data fetching when building data-heavy UIs like dashboards or admin interfaces. These applications require predictable caching, safe mutations across lists and details, and consistent state management that a combined Zustand and SWR architecture provides.

Combining Zustand and SWR improves API calling reliability by enforcing a central service layer for network requests. SWR handles caching and revalidation, while Zustand manages predictable state, ensuring safe mutations and consistent data rendering across complex admin interfaces.

Handle cache invalidation after mutations by calling SWR's mutation or revalidation functions directly from your Zustand store actions. This ensures the local cache refreshes immediately after the service layer confirms a successful remote update, keeping list and detail views synchronized.