chore: remove the Python service; Python is the training stack only

Phase 4 of docs/RUST_REWRITE.md. Since 2026-10-18 ping-collector (rust/)
collects, forecasts, notifies (ntfy + Matrix) and serves the website/API;
nothing in production ran the Python service code any more.

Removed (~17k lines): the FastAPI app (web_api, schemas, health_check,
metrics, postgres_history, forecast_history, thaiwater), the Python RID
collector and CLI (water_scraper_v3, main, run.py), the notifier and Matrix
alerting (notify, alerting), the multi-backend adapters (SQLite, MySQL,
InfluxDB, VictoriaMetrics) with demo databases, models/validators/exceptions/
logging/rate limiter, ml/skill.py (served by Rust now), the migration tooling
(api_parity, collector_parity, e2e_notify, install_collector.sh,
gen_notify_cases.py, spikes/rust-forecast), Docker/compose/Grafana files,
sql/, the release workflow and the docs for all of that. Their tests went
with them.

Kept in Python: src/ml (training, evaluation harness, export; predict.py as
the reference the Rust forecaster is tested against), the HII and RID-dam
clients/stores for the archive backfills (their live collectors removed),
the backfill scripts, retrain.sh + timer, forecast_parity.py.

- PostgreSQL only: src/config.py is database_url() from POSTGRES_* / .env;
  the stores lost their sqlite/mysql branches (and the 2026-08 column
  migration). The database tests run against a throwaway schema from
  TEST_DATABASE_URL (tests/conftest.py pg_url, skipped without it), as the
  Rust tests do; CI gets a PostgreSQL service. 100 tests (66 without a DB).
- The notifier settings moved from src/notify.py into src/ml/export.py;
  flood_config.json regenerates byte-identical.
- tests/test_dashboard.py checks every path the dashboard fetches against
  ping-collector's router.
- Dependencies: fastapi, uvicorn, pydantic, influxdb, pymysql, psutil,
  schedule, sphinx, pyinstaller, mypy, pytest-asyncio dropped; python-dotenv
  1.1.1 explicit (it came in through uvicorn[standard]).
- Formatting contract extended to scripts/ and tests/ (reformatted once).
- scripts/install.sh is the one installer (fresh host or update, in place in
  a checkout without touching its ownership): binary, units, uv sync, .env
  defaults, removes the retired water-monitor.service and any old
  --alert-check cron job, dry run + forecast check, restart, readiness wait.
- Docs, CLAUDE.md, CONTRIBUTING.md, .env.example, Makefile, unit comments
  and Rust doc comments updated to the Rust service.

scripts/retrain.sh

@@ -5,15 +5,15 @@
 #
 # Why a script rather than ExecStart=train_flood_model.py:
 #   * train.py writes each station's bundle straight into models/ over ~12 min,
-#     and the API's hourly precompute reloads bundles by mtime. Training into
-#     a staging dir and mv-ing (atomic on one filesystem) means the API never
-#     sees a half-written joblib file or a mixed old/new set.
+#     and ping-collector reloads bundles by mtime on every forecast run.
+#     Training into a staging dir and mv-ing (atomic on one filesystem) means
+#     it never sees a half-written bundle or a mixed old/new set.
 #   * A run that produced gauge-only (v2) bundles, or trained too few stations,
 #     must NOT replace the deployed models. train.py already aborts on a
 #     missing rain series; this script re-checks the written metrics anyway.
-#   * No restart is needed: predict.py (Python) and ping-collector (Rust,
-#     FORECAST_IN_COLLECTOR=true) reload changed bundles on their next
-#     forecast run, so the new models are live within an hour.
+#   * No restart is needed: ping-collector reloads changed bundles
+#     (models/flood_*.json.gz, written by train.py next to each .joblib) on
+#     its next forecast run, so the new models are live within an hour.
 #
 # Exit codes: 0 ok, 2 training refused (see log), 3 verification failed.
 set -euo pipefail
@@ -88,4 +88,4 @@ for f in "${STAGE_DIR}"/flood_*.joblib "${STAGE_DIR}"/flood_*.json.gz "${STAGE_D
     mv -f "${f}" "${MODELS_DIR}/${name}"
 done
 rm -rf "${STAGE_DIR}"
-log "deployed ${VERSION} (${TRAINED} stations); previous generation in models/.previous. The API picks it up on its next hourly precompute."
+log "deployed ${VERSION} (${TRAINED} stations); previous generation in models/.previous. ping-collector loads it on its next forecast run."