Alby96andClaude Opus 5
3fcbb9f1c4
Sets up the Nuvolari monorepo layout (app/, backend/, docs/, tool/) with the groundwork that does not depend on the Flutter toolchain: gitignore covering Flutter, Python and every secret file shape; env.example.json as the template for --dart-define-from-file; a verification script that skips stages whose target does not exist yet so it is runnable from day one; and a CI workflow in GitHub Actions syntax so it runs unchanged on Gitea or GitHub. The documentation records facts verified against the live services rather than restated from the brief. Two of them change the design: - DPC VMI rasters are 1200x1400 Float32 on a 1 km grid in a custom projection centred on Italy, not EPSG:4326 or EPSG:3857, and their GeoKeys are internally inconsistent. Reprojection is mandatory and the source CRS must be read from each file rather than hardcoded. - The ARPA CAP feed carries six level values, not four: BIANCO for the avalanche scale out of season and "-" for no data. Collapsing either into VERDE would report "no alert" where the bulletin reports "not assessed". Also documents why the frames we publish inherit CC BY-SA from the DPC source, and why rain notifications subscribe to cell topics from the device so no user location ever reaches a server. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
4.9 KiB
Stack decisions
Each entry records what was chosen, what it was chosen over, and why. Revisit an entry only with a reason that invalidates its rationale.
Flutter, single codebase
Android ships first, iOS follows on the same code. Platform-specific work stays behind
interfaces (core/platform/) so the iOS port is additive rather than a rewrite.
Toolchain pinned during setup: Flutter 3.47.3 stable / Dart 3.13.3,
compileSdk/targetSdk 36, minSdk 21 (the floor imposed by maplibre_gl),
JDK 21.
State management — Riverpod without code generation
flutter_riverpod with hand-written Notifier / AsyncNotifier classes.
Chosen over: Bloc (more ceremony than this app's state needs), plain setState
(the radar timeline, the frame cache and the consent flow all share state across
screens), Riverpod with riverpod_generator.
Dropping code generation keeps build_runner out of CI and out of every edit-run
cycle. The generator's benefit — less boilerplate on providers — is small at this
size, and its cost is paid on every build. Reconsider if provider count passes ~40.
Networking — Dio
dio with interceptors for: the mandatory MET Norway User-Agent, retry with
exponential backoff, and timeouts.
Chosen over http, which has no interceptor model — the User-Agent obligation is a
licensing requirement, so it belongs in one enforced place rather than at each call
site where it can be forgotten.
The DPC origin header lives only in the Python worker. The app never talks to
DPC directly.
Models — hand-written fromJson
Chosen over freezed + json_serializable. The model set is small (radar manifest and
frames, forecast series, CAP alerts, region config) and the parsers are covered by
tests against real fixtures. Same rationale as Riverpod: no build_runner.
The tests, not the generator, are what guarantee the parsing is right — fixtures captured from the real endpoints catch schema drift that codegen would not.
Map — MapLibre GL
maplibre_gl 0.27.0 (Flutter 3.29+, Android API 21+, iOS 13+).
Chosen over flutter_map, which renders tiles in Dart. Radar animation redraws a
full-viewport image several times a second; a GPU-composited native renderer holds
frame rate where a Dart canvas does not.
The base map style URL comes from MAP_STYLE_URL. With no key configured the app
loads a minimal local style — flat background plus the Piedmont boundary from a
bundled GeoJSON — so development, tests and the demo mode all work offline.
Radar frame rendering — image source, double buffered
The worker publishes each frame already cropped to the region bounding box and
reprojected to EPSG:3857, so the four corners of a MapLibre LatLngQuad are exact and
no client-side warping is needed.
Animation uses two image sources, A and B: while one is visible the next frame is decoded into the other, then visibility swaps.
Chosen over: adding all ~20 frames as layers with opacity 0 (constant GPU memory matters more than the saved swap — 20 frames at 1024×1024 RGBA is ~80 MB resident), and over updating a single source in place (visible flicker during decode).
Frame cache — custom LRU
FrameCache over path_provider: an on-disk LRU with a configurable byte cap, plus a
small in-memory LRU of PNG bytes.
Chosen over flutter_cache_manager, which does not expose the eviction control the
scrubber needs. Prefetch must prioritise frames adjacent to the playhead and evict by
distance from it, not by age.
Region configuration
Everything region-specific lives in app/assets/regions/<id>.json: bounding box, map
centre and zoom limits, alert zones, active data sources, attribution strings. Adding
a region is a new JSON file plus its assets — no Dart changes.
Piedmont bounding box, padded: [6.55, 43.95, 9.30, 46.55] (W, S, E, N).
To be refined against the ISTAT geometry once that dataset is confirmed.
Backend — Python worker on a VPS
GDAL and HDF5 cannot run on Supabase Edge Functions (Deno), so the worker runs as a scheduled process on a VPS or Cloud Run.
rasterio 1.5.1 publishes Windows wheels for Python 3.14, so the worker also runs
natively on the development machine — no Docker or WSL needed to iterate.
Trigger: the DPC WebSocket push channel wss://radar-wss.protezionecivile.it, with a
5-minute cron as fallback. Polling DPC on a timer is the fallback, never the norm.
Output goes through a Publisher interface: LocalPublisher writes to backend/out/
for development, S3Publisher targets R2 or Supabase Storage once credentials exist.
Rain notifications — client-side topic subscription
The worker computes rain per geographic cell and publishes per-cell state. The app subscribes to FCM topics named after cells, from the device.
The server therefore never learns any user's position — not precisely, not even by cell. There is no user table to leak, and Data safety can honestly declare that no location is transmitted or stored.