Node, pnpm, Monorepo Cache, and Deterministic Install CI reproduces the repository using the committed lockfile. pnpm install --frozen-lockfile should fail if package manifests and the lockfile disagree. Setup-node can cache pnpm package downloads, but the lockfile remains the dependency truth. Cache speeds installation; it must never replace correctness.
Same Lockfile → pnpm cache → Frozen install → dependency graph
What this changes in TaskFlow • Node 24.21.0 course lock
• pnpm 12.3.4 course lock
• pnpm-lock.yaml committed
• Cache dependency path points at the lockfile
Deterministic setup uses: pnpm/action-setup@v6 with: version: 12.3.4
uses: actions/setup-node@v7
with:
node-version: 24.21.0
cache: pnpmrun: pnpm install --frozen-lockfileactions/setup-node v7 can cache pnpm dependencies; the committed lockfile remains the reproducibility anchor.
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 “Node pnpm Monorepo Cache and Deterministic Install” 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: .github/workflows/ci.yml plus release/deploy workflows that build once, tag by commit SHA, and gate promotion.. 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 “Node pnpm Monorepo Cache and Deterministic Install” to a different TaskFlow resource or input. Write the acceptance criteria first, implement it, and provide the evidence that each criterion is satisfied.
Run lint/typecheck/tests/build as separate clear steps or jobs with understandable failure ownership.
Use the smallest change that demonstrates this lesson. Stop after it works and capture evidence.Rebuilding different artifacts in each environment
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.