152 lines
8.0 KiB
Markdown
152 lines
8.0 KiB
Markdown
# Rust services
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Rewrite of the Ping River Monitor in Rust, one service at a time. The plan,
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costs and the parity rules are in [docs/RUST_REWRITE.md](../docs/RUST_REWRITE.md).
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| Crate | Replaces | Status |
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| --- | --- | --- |
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| `collector` (`ping-collector`) | RID, HII/ThaiWater, RID dams and Open-Meteo collection in the Python web app | phase 1: in production since 2026-10-17 |
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| `forecast` (`ping-forecast`, library) | the flood forecast (`src/ml` serving path); run by `ping-collector` with ntfy | phase 2: in production since 2026-10-18 |
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## ping-collector
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Collects into the same PostgreSQL tables as the Python app, so the two can be
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swapped (and swapped back) with no data migration. The Python web app keeps
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serving the API, forecasting and sending ntfy alerts with
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`COLLECTION_ENABLED=false`, and re-forecasts whenever the newest RID reading in
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the database advances.
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```text
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ping-collector run # the service: startup gap fill, RID at :05 (+10 min retries
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# while RID is behind), HII/dams/rain once per clock hour;
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# with FORECAST_IN_COLLECTOR=true also forecast + ntfy
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ping-collector once [--dry-run] # one cycle of every source; --dry-run writes nothing
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# and compares the RID fetch with the database
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ping-collector fill-gaps <days|all> # re-fetch RID reports with holes
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ping-collector check-db # connect, create missing tables, row counts
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ping-collector forecast [--json] [--save] [--now T] [--rain-file F]
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# forecast from the database and print it
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ping-collector notify --dry-run # the readings the notifier judges, and what it would send
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```
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Configuration is the Python app's `.env` (read from the working directory, or
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`--env-file`) with python-dotenv's rules, verified on 614 generated inputs
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(`collector/testdata/`): an unparsable line is skipped with a warning giving
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only its line number, never its value. Variables already set (e.g. by systemd's
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`EnvironmentFile=`) win. Used keys:
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`POSTGRES_CONNECTION_STRING` (or `POSTGRES_HOST/PORT/DB/USER/PASSWORD`),
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`RID_POLL_OFFSET_MINUTES` (5), `RID_RETRY_MINUTES` (10),
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`GAP_FILL_DAYS_ON_START` (14), `ENABLE_HII_COLLECTION`,
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`ENABLE_RESERVOIR_COLLECTION`, `ENABLE_RAIN_COLLECTION`, `HII_BASIN_CODE` (6),
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`STATION_CONFIG_PATH` (falls back to the bundled `src/data/stations.json`),
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`SCRAPING_STATUS_FILE` (status JSON served by the API's `/scraping/status`),
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`LOG_LEVEL` / `RUST_LOG`; for phase 2 `FORECAST_IN_COLLECTOR` (false),
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`MODELS_DIR` (`models`), `NTFY_SERVER` / `NTFY_PUBLISH_URL` / `NTFY_TOPIC_PREFIX`
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/ `NTFY_TOKEN` / `PUBLIC_URL` (as the Python app), `RID_STALE_ALERT_HOURS` (18,
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0 = off). All timestamps are Asia/Bangkok wall-clock, whatever the server's
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time zone.
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Not ported: the one-off archive backfills (`scripts/backfill_*.py`), which
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stay in Python.
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### Verified
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- 20 tests: parsers, gap/schedule logic, and database tests against a real
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PostgreSQL (late reports, midnight recovery, upsert revisions, NUMERIC
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rounding, dam metadata preservation).
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- Live parity: the Python collectors and `ping-collector` run back-to-back
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against the real upstream APIs into two empty databases produced identical
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rows in all 9 tables (16 stations, 1,104 RID readings, 103 + 76 HII rows,
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35 dams x 2 days, 168 rain hours). Rerun with
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`scripts/collector_parity.py` after changing a parser, table or upsert on
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either side.
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- The Python API with `COLLECTION_ENABLED=false` served `/health`,
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`/measurements/latest`, `/api/stats`, `/scraping/status` and model
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forecasts from a database filled only by `ping-collector`.
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## Forecast and notifications (phase 2)
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With `FORECAST_IN_COLLECTOR=true` in the shared `.env`, `ping-collector` runs
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the flood forecast after every cycle that brought newer RID or HII readings
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(and at least hourly), stores it in `forecast_history` and `forecast_current`
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(the Python API serves the latter as `/forecast`, falling back to computing
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itself when it is older than `FORECAST_MAX_AGE_SECONDS`), and sends the ntfy
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notifications. The Python app then neither forecasts nor notifies.
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- **Models** stay trained in Python. `src/ml/export.py` writes
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`models/flood_<station>.json.gz` next to each joblib bundle (`train_all()`
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does it, `retrain.sh` promotes it, `python -m src.ml.export` exports
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existing bundles); the collector reloads changed files on its next run.
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- **Shared constants** (thresholds, flood stages, upstream leads, notify
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settings) are compiled in from `forecast/flood_config.json`, generated by
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`uv run python -m src.ml.export --config`. `tests/test_model_export.py`
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fails while it differs from Python, and a change needs a collector rebuild.
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- **Notifications**: same topics, texts, hysteresis and `notification_state`
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keys as `src/notify.py`, so switching sends nothing twice. One change: for
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the stations whose ThaiWater twin is the same sensor, a reading newer than
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RID's (RID's report lags 2-10 h at night) drives the level alerts, marked
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"ThaiWater telemetry; the RID report is not in yet". "Gauge feed stale" now
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means no source has a reading for 3 h; RID alone lagging is reported once
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after `RID_STALE_ALERT_HOURS`.
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- Memory: 70 MB peak with all 15 models loaded (24-byte tree nodes).
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Verified:
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- `forecast/tests/parity.rs` replays fixtures from the Python production path
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(`forecast/testdata/gen_forecast_fixtures.py`: the 2024 flood rising and at
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its peak with RID lagging behind HII, a quiet window with dam data, a
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stale-feed window, moved thresholds). HII fill, every feature and every
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level are bit-identical; with all 15 local models 377 of 384 probabilities
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are bit-identical and the rest within 2 ulp (`exp`). CI checks the P.1 model.
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- `scripts/forecast_parity.py` does the same on the live database: Python and
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`ping-collector forecast --json` at the same moment with the same rain
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series. The install script runs it before `--cutover-forecast`.
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- `collector/testdata/gen_notify_cases.py`: 652 hourly steps through
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`src/notify.py` (thresholds, capacity guard, outlook, feed gaps, ntfy
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outages); the Rust notifier sends the same 751 messages word for word.
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### Develop
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```bash
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cd rust
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cargo fmt --all && cargo clippy --all-targets -- -D warnings
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docker run -d --name ping-pg -e POSTGRES_PASSWORD=ping -e POSTGRES_DB=ping -p 55432:5432 postgres:16
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TEST_DATABASE_URL=postgres://postgres:ping@localhost:55432/ping cargo test
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```
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Without `TEST_DATABASE_URL` the database tests skip. CI
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(`.gitea/workflows/rust.yml`) runs them against a PostgreSQL service and
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uploads the Linux binary as the `ping-collector-linux-x86_64` artifact.
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HTTP uses native-tls (OpenSSL on Linux), not rustls: app.rid.go.th (dams)
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only offers TLS 1.2 CBC cipher suites, which rustls refuses. Building on
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Linux needs `pkg-config` and `libssl-dev`.
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### Deploy
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Needs Rust >= 1.88. Distro `cargo` packages are older (`resolver 3 is not
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valid` / `edition 2024` errors), so install the toolchain once with rustup:
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```bash
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apt-get install -y build-essential pkg-config libssl-dev curl
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curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --profile minimal
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. "$HOME/.cargo/env" # puts ~/.cargo/bin before /usr/bin/cargo
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cargo --version # >= 1.88
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```
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Then on the server, after `git pull` (the Python side of the switch ships in
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the same commit):
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```bash
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cargo build --release --locked --manifest-path rust/Cargo.toml # or BIN=<CI artifact>
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sudo bash scripts/install_collector.sh # install + checks, nothing switched
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sudo bash scripts/install_collector.sh --cutover # Rust collects from now on
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sudo bash scripts/install_collector.sh --cutover-forecast # Rust also forecasts and notifies
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sudo bash scripts/install_collector.sh --rollback-forecast # forecasts + ntfy back to Python
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sudo bash scripts/install_collector.sh --rollback # Python does everything again
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journalctl -u ping-collector -f
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```
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Every install exports the models and runs `scripts/forecast_parity.py`;
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`--cutover-forecast` refuses to switch if it fails (`FORCE=1` overrides).
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