Authenticated Task Queries End to End Connect query functions to the real protected NestJS API
Phase 22 - TanStack Query Volume 06 - Professional Frontend
Build an authenticated Task API client TanStack Query does not perform HTTP requests itself. The query function calls TaskFlow's existing authenticated API client. This keeps authentication, error parsing and HTTP semantics outside React components.
export async function fetchTasks(query: TaskListQuery) { const params = new URLSearchParams(); params.set("page", String(query.page)); params.set("pageSize", String(query.pageSize)); if (query.search) params.set("search", query.search); if (query.status) params.set("status", query.status); if (query.priority) params.set("priority", query.priority);
return authenticatedFetch<TaskPage>( `/tasks?${params.toString()}`, ); }
Client component reads cached server state "use client";
export function TasksScreen({ query }: { query: TaskListQuery }) {
const result = useQuery(taskListOptions(query));if (result.isPending) return <TaskListSkeleton />; if (result.isError) return <TaskListError error={result.error} />; if (result.data.data.length === 0) return <EmptyState />;
return (
<>
{result.isFetching ? <span>Refreshing...</span> : null}
<TaskTable tasks={result.data.data} />
</>
);
}Keep the response shape typed export type TaskPage = { data: Task[]; meta: { page: number; pageSize: number; totalItems: number; totalPages: number; hasPreviousPage: boolean; hasNextPage: boolean; }; };
Server Components, TanStack Query hooks and form mutations should reuse the same transport contract where practical. Do not create a new fetch wrapper inside every component.
Preserve the Phase 13 error contract The API client should throw the structured ApiClientError created earlier, including status, stable error code and requestId when available. TanStack Query stores that error as query state; it should not flatten every failure into a generic fetch string.
Transport boundary checklist Concern Owner
TanStack Query is a server-state synchronization system, not merely a fetch helper. Cache identity, freshness, invalidation, and mutation semantics are the core model.
Restate the goal of “Authenticated Task Queries End to End” as one observable behavior. Write the success signal before touching code.
Trace the boundary map: component → query key → cache state → fetch/mutation → reconciliation. Mark the one boundary this lesson changes.
Inspect the current repository state and record the exact files, route, table, or runtime involved. Avoid creating an abstraction before you can name the existing owner.
Implement the smallest vertical slice. Add one coherent change, run the narrowest verification command, and read the output before continuing.
Connect the slice to TaskFlow’s phase artifact: TaskFlow query/mutation layer with stable keys, list/detail caching, invalidation, filters, and debugging via devtools/logs.. Verify behavior from the outside as a user or API client would.
Create one controlled failure that is safe to reproduce. Predict the symptom first, capture evidence, locate the earliest broken boundary, then fix only that cause.
Close the reference and rebuild or explain the core change from memory. Record what you would monitor or test before trusting the same change in production.
export const taskKeys = {
all: ["tasks"] as const,
list: (filters: TaskFilters) => ["tasks", "list", filters] as const,
detail: (id: string) => ["tasks", "detail", id] as const,
};Do not copy this as a finished answer. Predict what each boundary does, type the smallest useful slice, run it, then compare the result with your prediction.
Return to the nearest observable boundary: input, network, process log, database, or rendered UI. Compare actual evidence with the predicted path.
Change one variable at a time and reproduce the original failure after the fix; otherwise you have correlation, not diagnosis.
Without copying the final source, create a second small scenario that applies “Authenticated Task Queries End to End” to a different TaskFlow resource or input. Write the acceptance criteria first, implement it, and provide the evidence that each criterion is satisfied.
Implement create/update mutations and choose between invalidation and direct cache updates deliberately.
Use the smallest change that demonstrates this lesson. Stop after it works and capture evidence.Random query-key arrays scattered through components
Predict the symptom before causing the failure. Then locate the earliest boundary where reality diverges from expectation.Why does this responsibility live here, what input does it trust, what output proves success, and what would go wrong if another layer owned it?
If your explanation is vague, repeat the boundary trace before moving on.Close the reference. Reproduce the core idea from memory or explain the exact request/data flow aloud. Then check your diff or notes for accidental shortcuts that bypass validation, authorization, error handling, or verification earned in earlier phases.