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feat(collector): forecast and ntfy in ping-collector; ThaiWater keeps alerts current at night
Phase 2b/2c of docs/RUST_REWRITE.md. With FORECAST_IN_COLLECTOR=true (shared
.env) ping-collector, after each cycle that brought newer RID or HII readings
and at least hourly: loads the last 336 h (RID + HII mirror fill), fetches the
rain forecast, runs every exported model (rust/forecast), stores
forecast_history and forecast_current, and sends the ntfy notifications.
The Python API then serves forecast_current as /forecast (computing in-process
only when it is older than FORECAST_MAX_AGE_SECONDS) and neither forecasts nor
notifies.

ntfy (collector/src/notify.rs): a port of src/notify.py with the same topics,
texts, hysteresis, capacity guard and notification_state keys, checked word
for word on 751 messages generated by Python (testdata/gen_notify_cases.py).
The change: for stations whose ThaiWater twin is the same sensor, a reading
newer than RID's drives the level alerts (marked as ThaiWater telemetry), and
the feed counts as stale only when neither source has a reading for 3 h. RID
alone lagging is reported once after RID_STALE_ALERT_HOURS (18). This ends the
nightly "gauge feed stale" / "recovered" pairs caused by RID's late reports.

Commands: `forecast [--json] [--save] [--now] [--rain-file]`,
`notify --dry-run`. scripts/forecast_parity.py compares Python and the
collector on the live database (same moment, same rain); locally 48/48 rows
identical. install_collector.sh: models export + that check on every install,
--cutover-forecast (refuses on a failed check) and --rollback-forecast.

Trees are packed into 24-byte nodes: 70 MB peak with all 15 models (was 140).
Forecast values are written to NUMERIC as shortest round-trip text, so they
round as psycopg2's do. DB test schemas get a counter (parallel tests collided
on Windows' coarse clock).
2026-10-18 14:43:39 +07:00

3.3 KiB

CLAUDE.md

Guidance for AI coding agents working in this repository.

What this is

Flood monitoring and forecasting for the Ping River, Chiang Mai. Public dashboard and API at https://water.buildfor.life/ (never publish the server's private/Tailscale IP). Production: one systemd unit on a small VPS, /opt/thailand-water-monitor, user water-monitor, interpreter .venv/bin/python (uv-managed), updated by git pull.

Rules

  • Python 3.11 only. uv sync --python 3.11; run everything as uv run ....
  • make format (black 88 / isort black profile, config in pyproject.toml) before committing; CI fails on formatting. make test must stay green — tests are synthetic-data only, never add one that needs the DB or network.
  • Timestamps everywhere are Asia/Bangkok wall-clock with no offset. The dashboard parses them with parseTs() and renders with timeZone: TZ; keep it that way.
  • Model changes go through the rolling-origin harness (scripts/evaluate_variants.py) and are judged on first-alert LEAD and false alarms, not MAE. Record results, positive or negative, in docs/FLOOD_FORECASTING.md section 5. Do not change what is deployed (rise_rain / hgb-v3) without a harness result that beats it on lead.
  • train_all() must never silently produce a gauge-only (v2) model; the guard that raises RainUnavailableError stays.
  • No git add -A: zero-byte shell-accident files (#, $(wc, ...) have been committed before. Stage files by name.
  • Do not add Co-Authored-By trailers.
  • The dashboard is a single file, src/static/dashboard.html, EN + TH via the t() table: every user-visible string needs both languages.
  • Rust (rust/, see rust/README.md): cargo fmt --all, cargo clippy --all-targets -- -D warnings, cargo test (database tests need TEST_DATABASE_URL). The Rust collector writes the same tables as the Python collectors: a change to a table, upsert or parser on one side must be made on the other until the Python side is retired (check with a live run of both into two databases).
  • The forecast is served by Rust (rust/forecast) from models trained in Python. A change to src/ml/features.py, predict.py, the HII fill or the dam frame must be ported in the same change: regenerate rust/forecast/testdata/gen_forecast_fixtures.py and keep cargo test -p ping-forecast green. Changing thresholds, stages, leads or notify constants: uv run python -m src.ml.export --config (a test fails otherwise) and rebuild the collector. Notify texts: rust/collector/testdata/gen_notify_cases.py.

Where things are

  • src/web_api.py FastAPI app; src/water_scraper_v3.py RID collector; src/hii_collector.py ThaiWater/HII; src/ml/ features/train/evaluate/predict, rain.py (Open-Meteo), dam.py, hii_rain.py.
  • scripts/retrain.sh + water-monitor-retrain.timer: monthly retrain with staged promote. scripts/dev_proxy.py: serve the working-copy dashboard against the live API.
  • rust/collector (ping-collector): Rust data collector; with it deployed the Python app runs COLLECTION_ENABLED=false. With FORECAST_IN_COLLECTOR=true it also forecasts (rust/forecast) and sends ntfy; the API serves its forecast_current. Rewrite plan: docs/RUST_REWRITE.md.
  • docs/FLOOD_FORECASTING.md is the authoritative model write-up; docs/DATA_SOURCES.md the source catalog.