jpawlowski/hass.tibber_prices
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fix

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Julian Pawlowski 2025-11-02 23:45:05 +00:00
parent 097c3c63c0
commit 54d0359be8
1 changed files with 32 additions and 5 deletions
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37
custom_components/tibber_prices/sensor.py
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@ -378,8 +378,8 @@ class TibberPricesSensor(TibberPricesEntity, SensorEntity):
local_midnight = dt_util.as_local(dt_util.start_of_local_day(dt_util.now())) local_midnight = dt_util.as_local(dt_util.start_of_local_day(dt_util.now()))
local_midnight_tomorrow = local_midnight + timedelta(days=1) local_midnight_tomorrow = local_midnight + timedelta(days=1)
# Collect all prices from both today and tomorrow data that fall within local today # Collect all prices and their intervals from both today and tomorrow data that fall within local today
prices = [] price_intervals = []
for day_key in ["today", "tomorrow"]: for day_key in ["today", "tomorrow"]:
for price_data in price_info.get(day_key, []): for price_data in price_info.get(day_key, []):
starts_at_str = price_data.get("startsAt") starts_at_str = price_data.get("startsAt")
@ -397,12 +397,26 @@ class TibberPricesSensor(TibberPricesEntity, SensorEntity):
if local_midnight <= starts_at < local_midnight_tomorrow: if local_midnight <= starts_at < local_midnight_tomorrow:
total_price = price_data.get("total") total_price = price_data.get("total")
if total_price is not None: if total_price is not None:
prices.append(float(total_price)) price_intervals.append(
{
"price": float(total_price),
"interval": price_data,
}
)
if not prices: if not price_intervals:
return None return None
# Find the extreme value and store its interval for later use in attributes
prices = [pi["price"] for pi in price_intervals]
value = stat_func(prices) value = stat_func(prices)
# Store the interval with the extreme price for use in attributes
for pi in price_intervals:
if pi["price"] == value:
self._last_extreme_interval = pi["interval"]
break
result = self._get_price_value(value, in_euro=in_euro) result = self._get_price_value(value, in_euro=in_euro)
if decimals is not None: if decimals is not None:
@ -748,7 +762,13 @@ class TibberPricesSensor(TibberPricesEntity, SensorEntity):
attributes = {} attributes = {}
# Group sensors by type and delegate to specific handlers # Group sensors by type and delegate to specific handlers
if key in ["current_price", "current_price_eur", "price_level"]: if key in [
"current_price",
"current_price_eur",
"price_level",
"next_interval_price",
"next_interval_price_eur",
]:
self._add_current_price_attributes(attributes) self._add_current_price_attributes(attributes)
elif any(pattern in key for pattern in ["_price_today", "rating", "data_timestamp"]): elif any(pattern in key for pattern in ["_price_today", "rating", "data_timestamp"]):
self._add_statistics_attributes(attributes) self._add_statistics_attributes(attributes)
@ -825,6 +845,13 @@ class TibberPricesSensor(TibberPricesEntity, SensorEntity):
if hasattr(self, "_last_rating_level") and self._last_rating_level is not None: if hasattr(self, "_last_rating_level") and self._last_rating_level is not None:
attributes["level_id"] = self._last_rating_level attributes["level_id"] = self._last_rating_level
attributes["level_value"] = PRICE_RATING_MAPPING.get(self._last_rating_level, self._last_rating_level) attributes["level_value"] = PRICE_RATING_MAPPING.get(self._last_rating_level, self._last_rating_level)
elif key in ["lowest_price_today", "lowest_price_today_eur", "highest_price_today", "highest_price_today_eur"]:
# Use the timestamp from the interval that has the extreme price (already stored during value calculation)
if hasattr(self, "_last_extreme_interval") and self._last_extreme_interval:
attributes["timestamp"] = self._last_extreme_interval.get("startsAt")
else:
# Fallback: use the first timestamp of today
attributes["timestamp"] = price_info.get("today", [{}])[0].get("startsAt")
else: else:
# Fallback: use the first timestamp of today # Fallback: use the first timestamp of today
first_timestamp = price_info.get("today", [{}])[0].get("startsAt") first_timestamp = price_info.get("today", [{}])[0].get("startsAt")