ffd3030352464b26243b0321a9e337c1ddfecb8b
12
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
|
|
0e30ddbcb6 |
fix(notify): no "gauge feed stale" for RID's nightly pause on a quiet river
ping-status sent "gauge feed stale" around midnight and "feed recovered" around 07:00 on each of the last three nights (ntfy and, since phase 3, the Matrix room). RID publishes no hourly report overnight: the 21:00 reading is the last until the 22:00..06:00 hours arrive together (06:35, 06:55, 07:22 on 2026-10-17/18/19). The ThaiWater overlay was meant to bridge that, but ThaiWater's copies of the RID gauges come from the same feed with the same delay (P.1's mirror still has no value for 22:00-00:00 this morning), so it does not. Between 21:00 and FEED_NIGHT_UNTIL_HOUR (default 9, 0 = off) the feed of a quiet river is no longer reported stale; one still without new readings at 09:00 is. While a station is at warning/danger or the P.1 outlook is on, the 3 h rule holds all night. A feed already stale stays stale through the night (no false "recovered"), and a real recovery is announced at any hour. The replay of the Python notifier runs with the window off. Docs no longer claim that ThaiWater keeps the feed current at night. |
||
|
|
7e642555b4 |
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. |
||
|
|
779728e38b |
feat(web): the website and API in ping-collector; Matrix gets the ntfy transitions
Phase 3 of docs/RUST_REWRITE.md: rust/collector/src/web (axum) serves what
the FastAPI app (src/web_api.py) served, so one process collects, forecasts,
notifies and serves. With WEB_LISTEN=0.0.0.0:8000 it runs inside
`ping-collector run`; `ping-collector serve` runs it alone.
Same routes, parameters, JSON fields and field order, status codes,
{"detail": ...} errors and pydantic-style 422 lists, Cache-Control, gzip
(>500 B), CORS, Umami API tracking, the dashboard and static files, and the
stale-while-revalidate response caches (now with byte budgets: a history
response can be 10 MB). /docs is the same Swagger UI (+ /redoc); its OpenAPI
document is built from the route table, whose per-route parameter
declarations also validate the requests, so docs and behaviour cannot drift.
Python output conventions are kept: isoformat(), round(), numpy's pairwise
sums (catchment means), Python's summation order (skill metrics).
scripts/api_parity.py compares the two servers route by route on one
database (53 cases incl. errors, admin and static files; query values vary
per run so FastAPI's caches answer fresh). Locally: 53 identical; the
station CRUD writes byte-identical stations.json files; the skill/trend
logic matches on 9 station/horizon pairs with synthetic model versions.
Intended differences: /health counts the ThaiWater telemetry of the same
gauges while RID lags (as the notifier); /scraping/status adds the collector
version and last forecast run; an old stored forecast is served marked
X-Data-Stale instead of recomputed; /sensors/thaiwater is cached a minute;
.geojson is served as application/geo+json. Load (local, 16 clients): the
dashboard's routes 1375 vs 552 req/s, uncached history 714 vs 53 req/s;
25 MB resident when serving only.
Matrix (MATRIX_*): the notifier sends the room the transitions ntfy gets
(per station, outlook, feed; not ntfy's per-topic summaries), each once,
with its own matrix: keys in notification_state, seeded from ntfy's on first
use so nothing already announced repeats. Checked against a fake homeserver.
It replaces the `run.py --alert-check` cron job (repeated alerts every 15
min), which install_collector.sh now comments out (crontab backup kept).
install_collector.sh: --check-api (ping-collector serve on :8001 next to
FastAPI, api_parity.py), --cutover-api (refuses on a difference; sets
WEB_LISTEN, stops and disables water-monitor.service), --rollback-api;
--rollback-forecast and --rollback bring the Python app back as server.
ping-collector.service: MemoryMax 512M. Config::from_vars for tests; route
tests against a throwaway schema.
|
||
|
|
6ae67dec63 |
feat(collector): forecast and ntfy in ping-collector; ThaiWater keeps alerts current at night
CI / Format & lint (push) Successful in 22s
CI / Test suite (push) Successful in 59s
Docs / Validate documentation (push) Successful in 25s
Rust / fmt, clippy, test, build (push) Successful in 10m2s
Security / Dependency vulnerabilities (push) Successful in 2m11s
Security / Static analysis (push) Successful in 22s
Security / License report (push) Successful in 1m37s
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). |
||
|
|
4e619aa2ae |
feat(rust): ping-collector, phase 1 of the Rust rewrite
CI / Format & lint (push) Successful in 19s
CI / Test suite (push) Successful in 47s
Docs / Validate documentation (push) Successful in 19s
Rust / fmt, clippy, test, build (push) Successful in 7m35s
Security / Dependency vulnerabilities (push) Successful in 1m37s
Security / Static analysis (push) Successful in 17s
Security / License report (push) Successful in 1m30s
rust/collector replaces the collection half of the Python web app: RID hourly gauges (with the late-report semantics: store everything, retry every 10 min while RID is behind, re-fetch yesterday's holes, startup gap fill), HII rain + water level, RID dams (today + yesterday) and Open-Meteo rain. Same tables and upsert semantics, one UNNEST statement per table, Bangkok wall-clock time regardless of the server time zone. Python side: COLLECTION_ENABLED=false makes the API leader stop collecting and instead re-forecast + notify when the newest RID reading in the database advances (polled every FORECAST_POLL_SECONDS) and once per clock hour; /scraping/status then serves the collector's status file; /scrape/trigger answers 409. Verified: 20 Rust tests (parsers, gap/schedule logic, database tests against PostgreSQL); live parity run of both collectors into two empty databases: all 9 tables row-for-row identical (scripts/collector_parity.py); the Python API served health, measurements, stats, status and model forecasts from a database filled only by ping-collector. 177 Python tests pass. reqwest uses native-tls: app.rid.go.th offers only TLS 1.2 CBC suites, which rustls refuses. Deploy/cutover/rollback: scripts/install_collector.sh, scripts/ping-collector.service; CI: .gitea/workflows/rust.yml (fmt, clippy, tests with a PostgreSQL service, release artifact). |
||
|
|
04ebdaa931 |
fix: RID collector keeps late readings instead of losing every evening
CI / Format & lint (push) Successful in 29s
CI / Test suite (push) Successful in 50s
Docs / Validate documentation (push) Successful in 23s
Security / Dependency vulnerabilities (push) Successful in 1m34s
Security / Static analysis (push) Successful in 17s
Security / License report (push) Successful in 1m27s
RID's hourly report often lags 1-2 h in the evening. The cycle discarded the whole report unless it already held the current hour, the web-API loop then slept a full hour, and after 01:00 only today's report was fetched. Result: the 19:00-24:00 readings were dropped most nights (P.1 lost 00:00 on 23 of the last 60 days, 13 evening hours this week), the feed went stale from ~21:00 until morning and ntfy ping-status sent a stale/recovered pair daily. - run_scraping_cycle() upserts every reading the report has; "current hour present" now only decides the retry cadence (returned as before). - Yesterday's report is re-fetched while the store has holes in it (hours 22-24 are only reachable through that day's report). - Leader loop polls at :05 (RID_POLL_OFFSET_MINUTES) and retries every RID_RETRY_MINUTES (10) while RID is behind; HII/dams/rain once per clock hour; forecast precompute + ntfy when newer readings arrive or hourly. - Startup re-fetches holes from the last GAP_FILL_DAYS_ON_START (14) days. - /scraping/status: the leader shares its stats via a JSON file, so any worker reports them (was always 0 runs); adds feed_current, latest_reading, readings_saved. |
||
|
|
f4d42c90f4 |
fix: ntfy listens on the Tailscale address; monitor publishes to it directly
Security / Dependency vulnerabilities (push) Successful in 44s
Security / Static analysis (push) Successful in 9s
CI / Format & lint (push) Successful in 10s
CI / Test suite (push) Successful in 26s
Security / License report (push) Successful in 50s
Docs / Validate documentation (push) Successful in 16s
The reverse proxy is a separate VPS on the tailnet, so a loopback-only ntfy was unreachable from it. install_ntfy.sh now binds the host's Tailscale IP (NTFY_LISTEN overrides). New NTFY_PUBLISH_URL: where the monitor POSTs, separate from the public NTFY_SERVER subscribers see, so an alert never waits on DNS or the proxy (first cycle logged 502s from Cloudflare while the domain was not yet proxied). |
||
|
|
777b230baf |
feat: public flood notifications over self-hosted ntfy
CI / Format & lint (push) Successful in 11s
Security / Static analysis (push) Successful in 12s
CI / Test suite (push) Successful in 18s
Docs / Validate documentation (push) Successful in 11s
Security / Dependency vulnerabilities (push) Successful in 1m30s
Security / License report (push) Successful in 47s
Anyone can now get push alerts on their phone without an account: the monitor publishes to an ntfy server (one Go binary, ~30 MB RSS) and subscribers pick topics in the free iOS/Android/web app. Semantics are transitions, never state. One message when a gauge crosses its warning or danger threshold, one all-clear when it drops back (0.10 m hysteresis), nothing while it sits above. A three-day flood is two messages; a quiet season is zero. Topics: ping-warning / ping-danger (basin digest), ping-<station>-warning / -danger, ping-p1-outlook (opt-in: model P(warning within 24 h) at P.1 rises through 50 %, clears below 25 %, message says it is experimental), ping-status (feed stale >= 3 h / recovered). Priority 5 on danger so it rings through Do Not Disturb. src/notify.py runs once per collection cycle in the API process (leader only, after the forecast precompute, same data the dashboard shows). Last-sent state lives in a notification_state table so a restart never re-sends; a failed publish leaves state untouched so the crossing is retried next cycle instead of lost. Off unless NTFY_SERVER is set. Dashboard: a "Get alerts" button (only when configured) opens a panel with the server, per-topic cards, ntfy:// deep links and web links, app store links and a disclaimer. EN + TH. GET /api/notifications feeds it. scripts/install_ntfy.sh: .deb install, server.yml (loopback listen, anonymous read, token-only write scoped to ping-*, 72 h cache, signup/ login/metrics off, tight visitor limits), systemd, user + token, .env. Verified against ntfy 2.28.0: anon publish 403, token publish 200, token on foreign topic 403, anon read 200, and a seeded crossing through the real _notify_transitions path arrived in the topic with priority, tags, click and action button. docs/NOTIFICATIONS.md has the deployment and reverse-proxy notes. Tests: 10 for the state machine (159 total). |
||
|
|
ae5d0a13d7 |
[verified] feat: add live river dashboard
Add mapped river and ThaiWater sensor layers, PostgreSQL history charts, API endpoints, and dashboard tests. |
||
|
|
ca730e484b |
Add comprehensive Matrix alerting system with Grafana integration
- Implement custom Python alerting system (src/alerting.py) with water level monitoring, data freshness checks, and Matrix notifications - Add complete Grafana Matrix alerting setup guide (docs/GRAFANA_MATRIX_SETUP.md) with webhook configuration, alert rules, and notification policies - Create Matrix quick start guide (docs/MATRIX_QUICK_START.md) for rapid deployment - Integrate alerting commands into main application (--alert-check, --alert-test) - Add Matrix configuration to environment variables (.env.example) - Update Makefile with alerting targets (alert-check, alert-test) - Enhance status command to show Matrix notification status - Support station-specific water level thresholds and escalation rules - Provide dual alerting approach: native Grafana alerts and custom Python system 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> |
||
|
|
6c7c128b4d |
Major refactor: Migrate to uv, add PostgreSQL support, and comprehensive tooling
- **Migration to uv package manager**: Replace pip/requirements with modern pyproject.toml - Add pyproject.toml with complete dependency management - Update all scripts and Makefile to use uv commands - Maintain backward compatibility with existing workflows - **PostgreSQL integration and migration tools**: - Enhanced config.py with automatic password URL encoding - Complete PostgreSQL setup scripts and documentation - High-performance SQLite to PostgreSQL migration tool (91x speed improvement) - Support for both connection strings and individual components - **Executable distribution system**: - PyInstaller integration for standalone .exe creation - Automated build scripts with batch file generation - Complete packaging system for end-user distribution - **Enhanced data management**: - Fix --fill-gaps command with proper method implementation - Add gap detection and historical data backfill capabilities - Implement data update functionality for existing records - Add comprehensive database adapter methods - **Developer experience improvements**: - Password encoding tools for special characters - Interactive setup wizards for PostgreSQL configuration - Comprehensive documentation and migration guides - Automated testing and validation tools 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> |
||
|
|
af62cfef0b |
Initial commit: Northern Thailand Ping River Monitor v3.1.0
Security & Dependency Updates / Dependency Security Scan (push) Successful in 29s
Security & Dependency Updates / Docker Security Scan (push) Failing after 53s
Security & Dependency Updates / License Compliance (push) Successful in 13s
Security & Dependency Updates / Check for Dependency Updates (push) Successful in 19s
Security & Dependency Updates / Code Quality Metrics (push) Successful in 11s
Security & Dependency Updates / Security Summary (push) Successful in 7s
Features: - Real-time water level monitoring for Ping River Basin (16 stations) - Coverage from Chiang Dao to Nakhon Sawan in Northern Thailand - FastAPI web interface with interactive dashboard and station management - Multi-database support (SQLite, MySQL, PostgreSQL, InfluxDB, VictoriaMetrics) - Comprehensive monitoring with health checks and metrics collection - Docker deployment with Grafana integration - Production-ready architecture with enterprise-grade observability CI/CD & Automation: - Complete Gitea Actions workflows for CI/CD, security, and releases - Multi-Python version testing (3.9-3.12) - Multi-architecture Docker builds (amd64, arm64) - Daily security scanning and dependency monitoring - Automated documentation generation - Performance testing and validation Production Ready: - Type safety with Pydantic models and comprehensive type hints - Data validation layer with range checking and error handling - Rate limiting and request tracking for API protection - Enhanced logging with rotation, colors, and performance metrics - Station management API for dynamic CRUD operations - Comprehensive documentation and deployment guides Technical Stack: - Python 3.9+ with FastAPI and Pydantic - Multi-database architecture with adapter pattern - Docker containerization with multi-stage builds - Grafana dashboards for visualization - Gitea Actions for CI/CD automation - Enterprise monitoring and alerting Ready for deployment to B4L infrastructure! |