data-fetching

Standardize server data fetching by routing all reads through a typed service layer calling lambdaClient.query and driving client fetching with SWR-backed hooks stored in a Zustand store. This enforces consistent patterns for list and detail caching across your application.

Migrate away from useEffect by replacing request logic with useClientDataSWR hooks that fetch through a dedicated service layer. This moves server data caching into SWR and keeps the Zustand store clean by separating read operations from state management.

Implement optimistic updates by routing writes through lambdaClient.mutate and enforcing refreshXxx() patterns that target SWR cache keys. This mutation-safe refresh approach invalidates specific cache entries to ensure the UI reflects the latest server state without full reloads.

Yes, you can centralize all lambdaClient.query and lambdaClient.mutate access behind typed service methods. This keeps components and Zustand stores clean by abstracting API interactions into a dedicated, reusable service layer.

List and detail caching use distinct patterns: array-based caching for list flows and map-based caching for detail entries. Both are managed through useFetchXxx SWR hooks and support targeted refresh helpers after write operations.

SWR-backed hooks provide built-in caching, revalidation, and mutation-safe refresh capabilities that useState cannot. By combining SWR with a Zustand store and service layer, you ensure consistent server data synchronization without manual effect-based request logic.