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https://github.com/jpawlowski/hass.tibber_prices.git
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189d3ba84d
Add comprehensive data_lifecycle_status sensor showing real-time cache vs fresh API data status with 6 states and 13+ detailed attributes. Key features: - 6 lifecycle states: cached, fresh, refreshing, searching_tomorrow, turnover_pending, error - Push-update system for instant state changes (refreshing→fresh→error) - Quarter-hour polling for turnover_pending detection at 23:45 - Accurate next_api_poll prediction using Timer #1 offset tracking - Tomorrow prediction with actual timer schedule (not fixed 13:00) - 13+ formatted attributes: cache_age, data_completeness, api_calls_today, next_api_poll, etc. Implementation: - sensor/calculators/lifecycle.py: New calculator with state logic - sensor/attributes/lifecycle.py: Attribute builders with formatting - coordinator/core.py: Lifecycle tracking + callback system (+16 lines) - sensor/core.py: Push callback registration (+3 lines) - coordinator/constants.py: Added to TIME_SENSITIVE_ENTITY_KEYS - Translations: All 5 languages (de, en, nb, nl, sv) Timing optimization: - Extended turnover warning: 5min → 15min (catches 23:45 quarter boundary) - No minute-timer needed: quarter-hour updates + push = optimal - Push-updates: <1sec latency for refreshing/fresh/error states - Timer offset tracking: Accurate tomorrow predictions Removed obsolete sensors: - data_timestamp (replaced by lifecycle attributes) - price_forecast (never implemented, removed from definitions) Impact: Users can monitor data freshness, API call patterns, cache age, and understand integration behavior. Perfect for troubleshooting and visibility into when data updates occur. |
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| .. | ||
| __init__.py | ||
| base.py | ||
| daily_stat.py | ||
| interval.py | ||
| lifecycle.py | ||
| metadata.py | ||
| rolling_hour.py | ||
| timing.py | ||
| trend.py | ||
| volatility.py | ||
| window_24h.py | ||