grabowski
764764e07e
train_all() now raises RainUnavailableError when use_rain=True and the
Open-Meteo history cannot be loaded, instead of logging a warning and
writing gauge-only (v2) bundles over the deployed v3 set -- which is what
the 2026-09-01 server retrain did unnoticed. --no-rain remains the explicit
way to get v2. CLI exits 2 with a one-line error. Three tests cover the
guard, the opt-out, and the v3 happy path.
scripts/retrain.sh trains into models/.staging, refuses to promote unless
metrics.json shows hgb-v3+ and >=14 trained stations, then renames bundles
into place (previous generation kept in models/.previous). No API restart:
predict.py reloads by mtime on the hourly precompute.
water-monitor-retrain.{service,timer}: 1st of each month 03:30, Persistent,
OMP_NUM_THREADS=4, Nice=15, same sandbox as the API unit. install.sh now
does `uv sync` into .venv (one env rule; removes a stale venv/) and enables
the timer. water-monitor.service in the repo matched neither the deployed
unit nor the uv env; it now does (run.py --web-api, .venv, EnvironmentFile).
176 lines
2.4 KiB
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176 lines
2.4 KiB
Plaintext
# Python
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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PIPFILE.lock
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# Virtual environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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*~
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# Kiro IDE (keep local only)
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.kiro/
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# Logs
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*.log
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logs/
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water_monitor.log
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water_monitor_performance.log
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# Database files
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*.db
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*.sqlite
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*.sqlite3
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water_levels.db
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demo_water_sqlite.db
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# Configuration files with secrets
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.env.local
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.env.production
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config.local.py
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# Docker
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.dockerignore
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# OS
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.DS_Store
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.DS_Store?
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._*
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.Spotlight-V100
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.Trashes
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ehthumbs.db
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Thumbs.db
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# Temporary files
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*.tmp
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*.temp
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temp/
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tmp/
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# Coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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# Jupyter Notebook
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.ipynb_checkpoints
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# pyenv
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.python-version
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# pipenv
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Pipfile.lock
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# PEP 582
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__pypackages__/
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# Celery
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.env.local
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.env.development.local
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.env.test.local
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.env.production.local
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# Docker volumes
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vm_data/
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grafana_data/
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# Runtime station config (persisted CRUD); bundled default lives in src/data/
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/stations.json
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# Ruflo local secrets and runtime data
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.env.*.local
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.claude-flow/data/
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.claude-flow/logs/
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.claude-flow/sessions/
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# Trained flood-forecast model artifacts (produced on the server, ~100 MB; see docs/FLOOD_FORECASTING.md)
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models/*.joblib
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models/cache/
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models/metrics.json
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# scripts/retrain.sh working dirs (staging + one rollback generation)
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models/.staging/
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models/.previous/
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# Playwright MCP browser artifacts (screenshots/snapshots from agent sessions)
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.playwright-mcp/
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# Agent tooling state (whole dirs; the entries above only covered subpaths)
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.claude/
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.claude-flow/
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.swarm/
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# local MCP server wiring, not project config
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.mcp.json
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# CLAUDE.md is intentionally NOT ignored — track it if you want the agent
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# conventions shared with collaborators; it is untracked today.
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# Model evaluation output (regenerate with scripts/evaluate_variants.py)
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models/eval_*.json
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# Editor/merge leftovers and stray shell-redirect artifacts. The repo root once
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# collected 56 zero-byte files named after fragments of shell commands.
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*.orig
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*.rej
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*.bak
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*~
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