Define Bufdir Payload Schema and TypeScript Interfaces
epic-bufdir-report-export-core-backend-task-001 — Define the canonical Bufdir JSON payload TypeScript interfaces and Dart models that represent the intermediate representation consumed by all output channels (CSV, PDF, future API). This includes activity record structure, peer mentor grouping envelope, org hierarchy roll-up fields, and duplicate flag metadata. These types are the contract shared by the aggregation service, serializer, and generation services.
Acceptance Criteria
Technical Requirements
Implementation Notes
Place all Bufdir domain models in a dedicated folder (`lib/domain/models/bufdir/`) to make the contract boundary explicit and easy to locate. If the project already uses `freezed` for immutable models and union types, use it here for consistency — it auto-generates copyWith, ==, hashCode, and toJson. If not using code generation, implement these manually and note the decision in a comment so future developers don't add a second pattern. The `ScopeLevel` enum should use lowercase string values for JSON (`chapter`, `region`, `national`) matching what Supabase Edge Functions will produce.
Avoid importing Flutter widgets or platform channels in this file — it must be pure Dart so it is usable in both Flutter mobile and any future server-side Dart context. This file is the single source of truth: any time the Bufdir specification changes, update these models first and let the compiler surface all required downstream changes.
Testing Requirements
Unit tests in `test/domain/models/bufdir/bufdir_payload_test.dart` covering: (1) round-trip serialization — construct a model, call toJson, then fromJson, and assert equality; (2) null/empty list defaults — confirm duplicate_warnings defaults to [] when absent from JSON; (3) enum parsing — confirm fromJson correctly maps all scope_level string values and throws or returns null for unknown values; (4) boundary values — period_start equal to period_end (single-day report) is accepted; negative session counts should either be prevented by constructor assertion or rejected by fromJson with a descriptive error. All tests use flutter_test.
Supabase Edge Functions have a default execution timeout. For large national-scope exports aggregating tens of thousands of activities across 1,400 chapters, the edge function may time out before completing, leaving coordinators with a failed export and no partial output.
Mitigation & Contingency
Mitigation: Optimise the aggregation SQL using pre-materialised aggregation views or RPC functions that run inside the database rather than iterating records in Deno. Profile query execution time against realistic production data volumes early. Request an elevated timeout limit from Supabase if needed. Implement progress checkpointing so the export can be resumed from the last completed aggregation batch.
Contingency: For organisations exceeding a configurable threshold (e.g. >5,000 activities), switch to an asynchronous export pattern: the edge function writes a 'pending' audit record and enqueues the job; the client polls for completion and is notified via Supabase Realtime when the file is ready.
Server-side PDF generation in a Deno Edge Function environment restricts library choices. Many popular PDF libraries require Node.js APIs not available in Deno, or produce large bundle sizes that exceed edge function limits. Choosing the wrong library could block the entire PDF generation path.
Mitigation & Contingency
Mitigation: Spike PDF library selection as the first task of this epic, evaluating at least two Deno-compatible options (e.g. pdf-lib, jsPDF with Deno compatibility shim). Test bundle size and basic rendering before committing to an implementation. Document the chosen library's constraints.
Contingency: If no suitable Deno-native PDF library is found, generate a well-structured HTML report from the edge function and use a headless Chromium service (e.g. Browserless, Gotenberg) for HTML-to-PDF conversion, or temporarily ship CSV-only export while the PDF path is resolved.
Peer mentors affiliated with multiple chapters (a documented NHF scenario) must not be double-counted in participant totals. Incorrect deduplication logic would overreport participation figures to Bufdir, which could be discovered during audit and damage organisational credibility.
Mitigation & Contingency
Mitigation: Define and document the deduplication contract explicitly before coding: deduplication is per-person per-period, not per-activity. Build dedicated unit tests with fixtures containing the exact multi-chapter membership patterns described in NHF's documentation. Have a NHF representative validate test fixture outputs against known-good manual counts.
Contingency: If deduplication logic produces results that cannot be verified against manual counts before launch, surface a deduplication warning in the export preview listing the affected peer mentor IDs, and require explicit coordinator acknowledgement before finalising the export.