Commit Graph
9 Commits
Author SHA1 Message Date
grabowski 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).
2026-10-18 14:43:39 +07:00
grabowski 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).
2026-10-17 22:20:02 +07:00
grabowski 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.
2026-10-17 21:45:09 +07:00
grabowski 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).
2026-09-12 00:28:29 +02:00
grabowski 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).
2026-09-12 00:18:38 +02:00
grabowski ae5d0a13d7 [verified] feat: add live river dashboard
Add mapped river and ThaiWater sensor layers, PostgreSQL history charts, API endpoints, and dashboard tests.
2026-08-09 16:59:25 +07:00
grabowskiandClaude 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>
2025-09-26 16:18:02 +07:00
grabowskiandClaude 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>
2025-09-26 15:10:10 +07:00
grabowski 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!
2025-08-12 15:40:24 +07:00