jpawlowski/hass.tibber_prices
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refactor: Store trend attributes in a sensor-specific dictionary for better organization

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Julian Pawlowski 2025-11-08 15:30:55 +00:00
parent f9f4908748
commit 5ba0633d15
1 changed files with 13 additions and 18 deletions
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31
custom_components/tibber_prices/sensor.py
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@ -521,6 +521,7 @@ class TibberPricesSensor(TibberPricesEntity, SensorEntity):
self._attr_has_entity_name = True self._attr_has_entity_name = True
self._value_getter: Callable | None = self._get_value_getter() self._value_getter: Callable | None = self._get_value_getter()
self._time_sensitive_remove_listener: Callable | None = None self._time_sensitive_remove_listener: Callable | None = None
self._trend_attributes: dict[str, Any] = {} # Sensor-specific trend attributes
async def async_added_to_hass(self) -> None: async def async_added_to_hass(self) -> None:
"""When entity is added to hass.""" """When entity is added to hass."""
@ -1225,27 +1226,25 @@ class TibberPricesSensor(TibberPricesEntity, SensorEntity):
# Calculate trend with 5% threshold # Calculate trend with 5% threshold
trend_state, diff_pct = calculate_price_trend(current_price, future_avg, threshold_pct=5.0) trend_state, diff_pct = calculate_price_trend(current_price, future_avg, threshold_pct=5.0)
# Store attributes for extra_state_attributes # Store attributes in sensor-specific dictionary (not shared _attr_extra_state_attributes)
if not hasattr(self, "_attr_extra_state_attributes") or self._attr_extra_state_attributes is None: self._trend_attributes = {
self._attr_extra_state_attributes = {} "timestamp": next_interval_start.isoformat(),
f"trend_{hours}h_%": round(diff_pct, 1),
# Core attributes f"future_avg_{hours}h": round(future_avg * 100, 2),
self._attr_extra_state_attributes["timestamp"] = next_interval_start.isoformat() "intervals_analyzed": hours * 4,
self._attr_extra_state_attributes[f"trend_{hours}h_%"] = round(diff_pct, 1) }
self._attr_extra_state_attributes[f"future_avg_{hours}h"] = round(future_avg * 100, 2)
self._attr_extra_state_attributes["intervals_analyzed"] = hours * 4
# Calculate additional attributes for better granularity # Calculate additional attributes for better granularity
if hours > MIN_HOURS_FOR_LATER_HALF: if hours > MIN_HOURS_FOR_LATER_HALF:
# Get second half average for longer periods # Get second half average for longer periods
later_half_avg = self._calculate_later_half_average(hours, next_interval_start) later_half_avg = self._calculate_later_half_average(hours, next_interval_start)
if later_half_avg is not None: if later_half_avg is not None:
self._attr_extra_state_attributes[f"later_half_avg_{hours}h"] = round(later_half_avg * 100, 2) self._trend_attributes[f"later_half_avg_{hours}h"] = round(later_half_avg * 100, 2)
# Calculate incremental change: how much does the later half differ from current? # Calculate incremental change: how much does the later half differ from current?
if current_price > 0: if current_price > 0:
incremental_diff = ((later_half_avg - current_price) / current_price) * 100 incremental_diff = ((later_half_avg - current_price) / current_price) * 100
self._attr_extra_state_attributes["incremental_change"] = round(incremental_diff, 1) self._trend_attributes["incremental_change"] = round(incremental_diff, 1)
return trend_state return trend_state
@ -1589,13 +1588,9 @@ class TibberPricesSensor(TibberPricesEntity, SensorEntity):
key = self.entity_description.key key = self.entity_description.key
attributes = {} attributes = {}
# For trend sensors, merge _attr_extra_state_attributes first # For trend sensors, merge _trend_attributes (sensor-specific)
if ( if key.startswith("price_trend_") and hasattr(self, "_trend_attributes") and self._trend_attributes:
key.startswith("price_trend_") attributes.update(self._trend_attributes)
and hasattr(self, "_attr_extra_state_attributes")
and self._attr_extra_state_attributes
):
attributes.update(self._attr_extra_state_attributes)
# Group sensors by type and delegate to specific handlers # Group sensors by type and delegate to specific handlers
if key in [ if key in [