Fixed inconsistency between "Current Electricity Price" and "Current Electricity Price
(Energy Dashboard)" sensors that were showing different prices and icons.
Changes:
- Add current_interval_price_base to TIME_SENSITIVE_ENTITY_KEYS so it updates at
quarter-hour boundaries instead of only on API polls. This ensures both sensors
update synchronously when a new 15-minute interval starts.
- Use interval_data["startsAt"] as timestamp for current interval price sensors
(both variants) instead of rounded calculation time. This prevents timestamp
divergence when sensors update at slightly different times.
- Include current_interval_price_base in icon color attribute mapping so both
sensors display the same dynamic cash icon based on current price level.
- Include current_interval_price_base in dynamic icon function so it gets the
correct icon based on current price level (VERY_CHEAP/CHEAP/NORMAL/EXPENSIVE).
Impact: Both sensors now show identical prices, timestamps, and icons as intended.
They update synchronously at interval boundaries (00, 15, 30, 45 minutes) and
correctly represent the Energy Dashboard compatible variant without lag or
inconsistencies.
- Introduced `get_intervals_for_day_offsets` helper to streamline access to price intervals for yesterday, today, and tomorrow.
- Updated various components to replace direct access to `priceInfo` with the new helper, ensuring a flat structure for price intervals.
- Adjusted calculations and data processing methods to accommodate the new data structure.
- Enhanced documentation to reflect changes in caching strategy and data structure.
Introduce TimeService as single source of truth for all datetime operations,
replacing direct dt_util calls throughout the codebase. This establishes
consistent time context across update cycles and enables future time-travel
testing capability.
Core changes:
- NEW: coordinator/time_service.py with timezone-aware datetime API
- Coordinator now creates TimeService per update cycle, passes to calculators
- Timer callbacks (#2, #3) inject TimeService into entity update flow
- All sensor calculators receive TimeService via coordinator reference
- Attribute builders accept time parameter for timestamp calculations
Key patterns replaced:
- dt_util.now() → time.now() (single reference time per cycle)
- dt_util.parse_datetime() + as_local() → time.get_interval_time()
- Manual interval arithmetic → time.get_interval_offset_time()
- Manual day boundaries → time.get_day_boundaries()
- round_to_nearest_quarter_hour() → time.round_to_nearest_quarter()
Import cleanup:
- Removed dt_util imports from ~30 files (calculators, attributes, utils)
- Restricted dt_util to 3 modules: time_service.py (operations), api/client.py
(rate limiting), entity_utils/icons.py (cosmetic updates)
- datetime/timedelta only for TYPE_CHECKING (type hints) or duration arithmetic
Interval resolution abstraction:
- Removed hardcoded MINUTES_PER_INTERVAL constant from 10+ files
- New methods: time.minutes_to_intervals(), time.get_interval_duration()
- Supports future 60-minute resolution (legacy data) via TimeService config
Timezone correctness:
- API timestamps (startsAt) already localized by data transformation
- TimeService operations preserve HA user timezone throughout
- DST transitions handled via get_expected_intervals_for_day() (future use)
Timestamp ordering preserved:
- Attribute builders generate default timestamp (rounded quarter)
- Sensors override when needed (next interval, daily midnight, etc.)
- Platform ensures timestamp stays FIRST in attribute dict
Timer integration:
- Timer #2 (quarter-hour): Creates TimeService, calls _handle_time_sensitive_update(time)
- Timer #3 (30-second): Creates TimeService, calls _handle_minute_update(time)
- Consistent time reference for all entities in same update batch
Time-travel readiness:
- TimeService.with_reference_time() enables time injection (not yet used)
- All calculations use time.now() → easy to simulate past/future states
- Foundation for debugging period calculations with historical data
Impact: Eliminates timestamp drift within update cycles (previously 60+ independent
dt_util.now() calls could differ by milliseconds). Establishes architecture for
time-based testing and debugging features.
Created entity_utils/helpers.py with platform-agnostic utility functions:
- get_price_value(): Price unit conversion (major/minor currency)
- translate_level(): Price level translation
- translate_rating_level(): Rating level translation
- find_rolling_hour_center_index(): Rolling hour window calculations
These functions moved from sensor/helpers.py as they are used by both
sensor and binary_sensor platforms. Remaining sensor/helpers.py now
contains only sensor-specific helpers (aggregate_price_data, etc.).
Updated imports:
- sensor/core.py: Import from entity_utils instead of sensor.helpers
- entity_utils/icons.py: Fixed find_rolling_hour_center_index import
- binary_sensor platforms: Can now use shared helpers
Added clear docstrings explaining:
- entity_utils/helpers.py: Platform-agnostic utilities
- sensor/helpers.py: Sensor-specific aggregation functions
Impact: Better code reuse, clearer responsibility boundaries between
platform-specific and shared utilities.
Added 10 new timing sensors (5 for best_price, 5 for peak_price) to track
period timing and progress:
Timestamp sensors (quarter-hour updates):
- best_price_end_time / peak_price_end_time
Shows when current/next period ends (always useful reference time)
- best_price_next_start_time / peak_price_next_start_time
Shows when next period starts (even during active periods)
Countdown sensors (minute updates):
- best_price_remaining_minutes / peak_price_remaining_minutes
Minutes left in current period (0 when inactive)
- best_price_next_in_minutes / peak_price_next_in_minutes
Minutes until next period starts
- best_price_progress / peak_price_progress
Progress percentage through current period (0-100%)
Smart fallback behavior:
- Sensors always show useful values (no 'Unknown' during normal operation)
- Timestamp sensors show current OR next period end/start times
- Countdown sensors return 0 when no period is active
- Grace period: Progress stays at 100% for 60 seconds after period ends
Dynamic visual feedback:
- Progress icons differentiate 3 states at 0%:
* No data: mdi:help-circle-outline (gray)
* Waiting for next period: mdi:timer-pause-outline
* Period just started: mdi:circle-outline
- Progress 1-99%: mdi:circle-slice-1 to mdi:circle-slice-8 (pie chart)
- Timer icons based on urgency (alert/timer/timer-sand/timer-outline)
- Dynamic colors: green (best_price), orange/red (peak_price), gray (disabled)
- icon_color attribute for UI styling
Implementation details:
- Dual update mechanism: quarter-hour (timestamps) + minute (countdowns)
- Period state callbacks: Check if period is currently active
- IconContext dataclass: Reduced function parameters from 6 to 3
- Unit constants: UnitOfTime.MINUTES, PERCENTAGE from homeassistant.const
- Complete translations for 5 languages (de, en, nb, nl, sv)
Impact: Users can now build sophisticated automations based on period timing
('start dishwasher if remaining_minutes > 60'), display countdowns in
dashboards, and get clear visual feedback about period states. All sensors
provide meaningful values at all times, making automation logic simpler.
Added timestamp attributes to all sensors and enhanced the dynamic icon
system for comprehensive price sensor coverage with rolling hour support.
TIMESTAMP ATTRIBUTES:
Core Changes:
- sensor/attributes.py:
* Enhanced add_average_price_attributes() to track extreme intervals
for min/max sensors and add appropriate timestamps
* Added _update_extreme_interval() helper to reduce complexity
* Extended add_volatility_type_attributes() with timestamp logic for
all 4 volatility types (today/tomorrow/today_tomorrow/next_24h)
* Fixed current_interval_price timestamp assignment (use interval_data)
Timestamp Logic:
- Interval-based sensors: Use startsAt of specific 15-minute interval
- Min/Max sensors: Use startsAt of interval with extreme price
- Average sensors: Use startsAt of first interval in window
- Volatility sensors: Use midnight (00:00) for calendar day sensors,
current time for rolling 24h window
- Daily sensors: Already used fallback to midnight (verified)
ICON SYSTEM ENHANCEMENTS:
Major Extensions:
- entity_utils/icons.py:
* Created get_rolling_hour_price_level_for_icon() implementing
5-interval window aggregation matching sensor calculation logic
* Extended get_price_sensor_icon() coverage from 1 to 4 sensors:
- current_interval_price (existing)
- next_interval_price (NEW - dynamic instead of static)
- current_hour_average_price (NEW - uses rolling hour aggregation)
- next_hour_average_price (NEW - uses rolling hour aggregation)
* Added imports for aggregate_level_data and find_rolling_hour_center_index
Documentation:
- sensor/definitions.py:
* Updated 30+ sensor descriptions with detailed icon behavior comments
* Changed next_interval_price from static to dynamic icon
* Documented dynamic vs static icons for all sensor types
* Added clear icon mapping source documentation
SENSOR KEY RENAMING:
Renamed for clarity (current_hour_average → current_hour_average_price):
- sensor/core.py: Updated value getters and cached data lookup
- sensor/definitions.py: Updated entity descriptions
- sensor/attributes.py: Updated key references in attribute builders
- coordinator.py: Updated TIME_SENSITIVE_ENTITY_KEYS set
- const.py: Updated comment documentation
Translation Updates:
- custom_translations/*.json (5 files): Updated sensor keys
- translations/*.json (5 files): Updated sensor keys
Impact:
- All sensors now have timestamp attribute showing applicable time/interval
- Icon system provides richer visual feedback for more sensor types
- Consistent sensor naming improves code readability
- Users get temporal context for all sensor values
- Dynamic icons adapt to price conditions across more sensors
Added 6 new sensors for yesterday/today/tomorrow aggregated price
levels and ratings, following the same calculation logic as existing
current/next interval sensors.
New sensors:
- yesterday_price_level, today_price_level, tomorrow_price_level
- yesterday_price_rating, today_price_rating, tomorrow_price_rating
Implementation details:
- Added DAILY_LEVEL_SENSORS and DAILY_RATING_SENSORS in sensor/definitions.py
- Implemented _get_daily_aggregated_value() in sensor/core.py using
existing aggregate_level_data() and aggregate_rating_data() helpers
- Extended icon support in entity_utils/icons.py for dynamic icons
- Added icon_color attributes in sensor/attributes.py with helper
functions _get_day_key_from_sensor_key() and _add_fallback_timestamp()
- Complete translations in all 5 languages (de, en, nb, nl, sv):
* Standard translations: sensor names
* Custom translations: description, long_description, usage_tips
Impact: Users can now see aggregated daily price levels and ratings
for yesterday, today, and tomorrow at a glance, making it easier to
compare overall price situations across days and plan energy consumption
accordingly. Sensors use same aggregation logic as hourly sensors for
consistency.
