Update sensor.py
This commit is contained in:
balgerion
@ -8,11 +8,21 @@ from homeassistant.components.sensor import SensorEntity, SensorStateClass
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from homeassistant.helpers.update_coordinator import CoordinatorEntity
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from homeassistant.util import dt as dt_util
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from .update_coordinator import PstrykDataUpdateCoordinator
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from .const import DOMAIN
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from .const import (
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DOMAIN,
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CONF_MQTT_48H_MODE,
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CONF_RETRY_ATTEMPTS,
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CONF_RETRY_DELAY,
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DEFAULT_RETRY_ATTEMPTS,
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DEFAULT_RETRY_DELAY
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)
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from homeassistant.helpers.translation import async_get_translations
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_LOGGER = logging.getLogger(__name__)
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# Store translations globally to avoid reloading for each sensor
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_TRANSLATIONS_CACHE = {}
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async def async_setup_entry(
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hass: HomeAssistant,
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entry: ConfigEntry,
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@ -24,9 +34,23 @@ async def async_setup_entry(
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sell_top = entry.options.get("sell_top", entry.data.get("sell_top", 5))
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buy_worst = entry.options.get("buy_worst", entry.data.get("buy_worst", 5))
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sell_worst = entry.options.get("sell_worst", entry.data.get("sell_worst", 5))
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mqtt_48h_mode = entry.options.get(CONF_MQTT_48H_MODE, False)
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retry_attempts = entry.options.get(CONF_RETRY_ATTEMPTS, DEFAULT_RETRY_ATTEMPTS)
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retry_delay = entry.options.get(CONF_RETRY_DELAY, DEFAULT_RETRY_DELAY)
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_LOGGER.debug("Setting up Pstryk sensors with buy_top=%d, sell_top=%d, buy_worst=%d, sell_worst=%d",
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buy_top, sell_top, buy_worst, sell_worst)
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_LOGGER.debug("Setting up Pstryk sensors with buy_top=%d, sell_top=%d, buy_worst=%d, sell_worst=%d, mqtt_48h_mode=%s, retry_attempts=%d, retry_delay=%ds",
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buy_top, sell_top, buy_worst, sell_worst, mqtt_48h_mode, retry_attempts, retry_delay)
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# Load translations once for all sensors
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global _TRANSLATIONS_CACHE
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if not _TRANSLATIONS_CACHE:
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try:
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_TRANSLATIONS_CACHE = await async_get_translations(
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hass, hass.config.language, DOMAIN, ["entity", "debug"]
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)
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except Exception as ex:
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_LOGGER.warning("Failed to load translations: %s", ex)
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_TRANSLATIONS_CACHE = {}
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# Cleanup old coordinators if they exist
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for price_type in ("buy", "sell"):
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@ -39,6 +63,8 @@ async def async_setup_entry(
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coordinator._unsub_hourly()
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if hasattr(coordinator, '_unsub_midnight') and coordinator._unsub_midnight:
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coordinator._unsub_midnight()
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if hasattr(coordinator, '_unsub_afternoon') and coordinator._unsub_afternoon:
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coordinator._unsub_afternoon()
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# Remove from hass data
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hass.data[DOMAIN].pop(key, None)
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@ -48,7 +74,14 @@ async def async_setup_entry(
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# Create coordinators first
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for price_type in ("buy", "sell"):
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key = f"{entry.entry_id}_{price_type}"
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coordinator = PstrykDataUpdateCoordinator(hass, api_key, price_type)
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coordinator = PstrykDataUpdateCoordinator(
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hass,
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api_key,
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price_type,
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mqtt_48h_mode,
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retry_attempts,
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retry_delay
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)
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coordinators.append((coordinator, price_type, key))
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# Initialize coordinators in parallel to save time
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@ -84,12 +117,17 @@ async def async_setup_entry(
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# Schedule updates
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coordinator.schedule_hourly_update()
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coordinator.schedule_midnight_update()
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# Schedule afternoon update if 48h mode is enabled
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if mqtt_48h_mode:
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coordinator.schedule_afternoon_update()
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hass.data[DOMAIN][key] = coordinator
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# Create only one sensor per price type that combines both current price and table data
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top = buy_top if price_type == "buy" else sell_top
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worst = buy_worst if price_type == "buy" else sell_worst
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entities.append(PstrykPriceSensor(coordinator, price_type, top, worst))
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entities.append(PstrykPriceSensor(coordinator, price_type, top, worst, entry.entry_id))
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async_add_entities(entities, True)
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@ -98,32 +136,20 @@ class PstrykPriceSensor(CoordinatorEntity, SensorEntity):
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"""Combined price sensor with table data attributes."""
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_attr_state_class = SensorStateClass.MEASUREMENT
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def __init__(self, coordinator: PstrykDataUpdateCoordinator, price_type: str, top_count: int, worst_count: int):
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def __init__(self, coordinator: PstrykDataUpdateCoordinator, price_type: str, top_count: int, worst_count: int, entry_id: str):
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super().__init__(coordinator)
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self.price_type = price_type
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self.top_count = top_count
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self.worst_count = worst_count
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self.entry_id = entry_id
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self._attr_device_class = "monetary"
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self._translations = {}
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self._cached_sorted_prices = None
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self._last_data_hash = None
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async def async_added_to_hass(self):
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"""When entity is added to Home Assistant."""
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await super().async_added_to_hass()
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# Load translations
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self._translations = await self._load_translations()
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async def _load_translations(self):
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"""Load translations for the current language."""
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translations = {}
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try:
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translations = await async_get_translations(
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self.hass, self.hass.config.language, DOMAIN, ["entity", "debug"]
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)
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except Exception as ex:
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_LOGGER.warning("Failed to load translations: %s", ex)
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return translations
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@property
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def name(self) -> str:
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return f"Pstryk Current {self.price_type.title()} Price"
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@ -132,11 +158,56 @@ class PstrykPriceSensor(CoordinatorEntity, SensorEntity):
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def unique_id(self) -> str:
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return f"{DOMAIN}_{self.price_type}_price"
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@property
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def device_info(self):
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"""Return device information."""
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return {
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"identifiers": {(DOMAIN, "pstryk_energy")},
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"name": "Pstryk Energy",
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"manufacturer": "Pstryk",
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"model": "Energy Price Monitor",
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"sw_version": "1.6.2",
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}
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def _get_current_price(self):
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"""Get current price based on current time."""
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if not self.coordinator.data or not self.coordinator.data.get("prices"):
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return None
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now_utc = dt_util.utcnow()
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for price_entry in self.coordinator.data.get("prices", []):
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try:
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if "start" not in price_entry:
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continue
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price_datetime = dt_util.parse_datetime(price_entry["start"])
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if not price_datetime:
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continue
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# Konwersja do UTC dla porównania
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price_datetime_utc = dt_util.as_utc(price_datetime)
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price_end_utc = price_datetime_utc + timedelta(hours=1)
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if price_datetime_utc <= now_utc < price_end_utc:
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return price_entry.get("price")
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except Exception as e:
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_LOGGER.error("Error determining current price: %s", str(e))
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return None
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@property
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def native_value(self):
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if self.coordinator.data is None:
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return None
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return self.coordinator.data.get("current")
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# Próbujemy znaleźć aktualną cenę na podstawie czasu
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current_price = self._get_current_price()
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# Jeśli nie znaleźliśmy, używamy wartości z koordynatora
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if current_price is None:
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current_price = self.coordinator.data.get("current")
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return current_price
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@property
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def native_unit_of_measurement(self) -> str:
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@ -151,10 +222,10 @@ class PstrykPriceSensor(CoordinatorEntity, SensorEntity):
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next_hour = (now + timedelta(hours=1)).replace(minute=0, second=0, microsecond=0)
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# Use translations for debug messages
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debug_msg = self._translations.get(
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debug_msg = _TRANSLATIONS_CACHE.get(
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"debug.looking_for_next_hour",
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"Looking for price for next hour: {next_hour}"
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).format(next_hour=next_hour.isoformat())
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).format(next_hour=next_hour.strftime("%Y-%m-%d %H:%M:%S"))
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_LOGGER.debug(debug_msg)
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# Check if we're looking for the next day's hour (midnight)
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@ -176,10 +247,10 @@ class PstrykPriceSensor(CoordinatorEntity, SensorEntity):
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if price_datetime.hour == next_hour.hour and price_datetime.day == next_hour.day:
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price_found = price_data.get("price")
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_LOGGER.debug("Found price for %s in today's list: %s", next_hour.isoformat(), price_found)
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_LOGGER.debug("Found price for %s in today's list: %s", next_hour.strftime("%Y-%m-%d %H:%M:%S"), price_found)
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return price_found
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except Exception as e:
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error_msg = self._translations.get(
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error_msg = _TRANSLATIONS_CACHE.get(
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"debug.error_processing_date",
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"Error processing date: {error}"
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).format(error=str(e))
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@ -203,10 +274,10 @@ class PstrykPriceSensor(CoordinatorEntity, SensorEntity):
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# Check if this matches the hour and day we're looking for
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if price_datetime.hour == next_hour.hour and price_datetime.day == next_hour.day:
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price_found = price_data.get("price")
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_LOGGER.debug("Found price for %s in full 48h list: %s", next_hour.isoformat(), price_found)
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_LOGGER.debug("Found price for %s in full 48h list: %s", next_hour.strftime("%Y-%m-%d %H:%M:%S"), price_found)
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return price_found
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except Exception as e:
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full_list_error_msg = self._translations.get(
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full_list_error_msg = _TRANSLATIONS_CACHE.get(
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"debug.error_processing_full_list",
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"Error processing date for full list: {error}"
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).format(error=str(e))
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@ -214,78 +285,314 @@ class PstrykPriceSensor(CoordinatorEntity, SensorEntity):
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# If no price found for next hour
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if is_looking_for_next_day:
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midnight_msg = self._translations.get(
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midnight_msg = _TRANSLATIONS_CACHE.get(
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"debug.no_price_midnight",
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"No price found for next day midnight. Data probably not loaded yet."
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)
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_LOGGER.info(midnight_msg)
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else:
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no_price_msg = self._translations.get(
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no_price_msg = _TRANSLATIONS_CACHE.get(
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"debug.no_price_next_hour",
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"No price found for next hour: {next_hour}"
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).format(next_hour=next_hour.isoformat())
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).format(next_hour=next_hour.strftime("%Y-%m-%d %H:%M:%S"))
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_LOGGER.warning(no_price_msg)
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return None
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@property
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def extra_state_attributes(self) -> dict:
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"""Include the price table attributes in the current price sensor."""
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now = dt_util.as_local(dt_util.utcnow())
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def _get_cached_sorted_prices(self, today):
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"""Get cached sorted prices or compute if data changed."""
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# Create a simple hash of the data to detect changes
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data_hash = hash(tuple((p["start"], p["price"]) for p in today))
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# Get translated attribute name
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next_hour_key = self._translations.get(
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"entity.sensor.next_hour",
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"Next hour"
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)
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# Get translated cache info
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using_cached_key = self._translations.get(
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"entity.sensor.using_cached_data",
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"Using cached data"
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)
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if self.coordinator.data is None:
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return {
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next_hour_key: None,
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"all_prices": [],
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"best_prices": [],
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"worst_prices": [],
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"top_count": self.top_count,
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"worst_count": self.worst_count,
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"last_updated": now.isoformat(),
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"price_count": 0,
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using_cached_key: False
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}
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next_hour_data = self._get_next_hour_price()
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today = self.coordinator.data.get("prices_today", [])
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is_cached = self.coordinator.data.get("is_cached", False)
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if self._last_data_hash != data_hash or self._cached_sorted_prices is None:
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_LOGGER.debug("Price data changed, recalculating sorted prices")
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# Sortowanie dla najlepszych cen
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sorted_best_prices = sorted(
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sorted_best = sorted(
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today,
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key=lambda x: x["price"],
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reverse=(self.price_type == "sell"),
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)
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# Sortowanie dla najgorszych cen (odwrotna kolejność sortowania)
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sorted_worst_prices = sorted(
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sorted_worst = sorted(
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today,
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key=lambda x: x["price"],
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reverse=(self.price_type != "sell"),
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)
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self._cached_sorted_prices = {
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"best": sorted_best[: self.top_count],
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"worst": sorted_worst[: self.worst_count]
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}
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self._last_data_hash = data_hash
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return self._cached_sorted_prices
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def _is_likely_placeholder_data(self, prices_for_day):
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"""Check if prices for a day are likely placeholders.
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Returns True if:
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- There are no prices
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- ALL prices have exactly the same value (suggesting API returned default values)
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- There are too many consecutive hours with the same value (e.g., 10+ hours)
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"""
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if not prices_for_day:
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return True
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# Get all price values
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price_values = [p.get("price") for p in prices_for_day if p.get("price") is not None]
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if not price_values:
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return True
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# If we have less than 20 prices for a day, it's incomplete data
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if len(price_values) < 20:
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_LOGGER.debug(f"Only {len(price_values)} prices for the day, likely incomplete data")
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return True
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# Check if ALL values are identical
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unique_values = set(price_values)
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if len(unique_values) == 1:
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_LOGGER.debug(f"All {len(price_values)} prices have the same value ({price_values[0]}), likely placeholders")
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return True
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# Additional check: if more than 90% of values are the same, it's suspicious
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most_common_value = max(set(price_values), key=price_values.count)
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count_most_common = price_values.count(most_common_value)
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if count_most_common / len(price_values) > 0.9:
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_LOGGER.debug(f"{count_most_common}/{len(price_values)} prices have value {most_common_value}, likely placeholders")
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return True
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return False
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def _count_consecutive_same_values(self, prices):
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"""Count maximum consecutive hours with the same price."""
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if not prices:
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return 0
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# Sort by time to ensure consecutive checking
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sorted_prices = sorted(prices, key=lambda x: x.get("start", ""))
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max_consecutive = 1
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current_consecutive = 1
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last_value = None
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for price in sorted_prices:
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value = price.get("price")
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if value is not None:
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if value == last_value:
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current_consecutive += 1
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max_consecutive = max(max_consecutive, current_consecutive)
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else:
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current_consecutive = 1
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last_value = value
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return max_consecutive
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def _get_mqtt_price_count(self):
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"""Get the actual count of prices that would be published to MQTT."""
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if not self.coordinator.data:
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return 0
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if not self.coordinator.mqtt_48h_mode:
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# If not in 48h mode, we only publish today's prices
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prices_today = self.coordinator.data.get("prices_today", [])
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return len(prices_today)
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else:
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# In 48h mode, we need to count valid prices
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all_prices = self.coordinator.data.get("prices", [])
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# Just count today's prices as they're always valid
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now = dt_util.as_local(dt_util.utcnow())
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today_str = now.strftime("%Y-%m-%d")
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today_prices = [p for p in all_prices if p.get("start", "").startswith(today_str)]
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# For tomorrow, check if data looks valid
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tomorrow_str = (now + timedelta(days=1)).strftime("%Y-%m-%d")
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tomorrow_prices = [p for p in all_prices if p.get("start", "").startswith(tomorrow_str)]
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# Count today's prices always
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valid_count = len(today_prices)
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# Add tomorrow's prices only if they look like real data
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if tomorrow_prices and not self._is_likely_placeholder_data(tomorrow_prices):
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valid_count += len(tomorrow_prices)
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return valid_count
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@property
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def extra_state_attributes(self) -> dict:
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"""Include the price table attributes in the current price sensor."""
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now = dt_util.as_local(dt_util.utcnow())
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# Get translated attribute names from cache
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next_hour_key = _TRANSLATIONS_CACHE.get(
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"entity.sensor.next_hour",
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"Next hour"
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)
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using_cached_key = _TRANSLATIONS_CACHE.get(
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"entity.sensor.using_cached_data",
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"Using cached data"
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)
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all_prices_key = _TRANSLATIONS_CACHE.get(
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"entity.sensor.all_prices",
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"All prices"
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)
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best_prices_key = _TRANSLATIONS_CACHE.get(
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"entity.sensor.best_prices",
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"Best prices"
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)
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worst_prices_key = _TRANSLATIONS_CACHE.get(
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"entity.sensor.worst_prices",
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"Worst prices"
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)
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||||
|
||||
best_count_key = _TRANSLATIONS_CACHE.get(
|
||||
"entity.sensor.best_count",
|
||||
"Best count"
|
||||
)
|
||||
|
||||
worst_count_key = _TRANSLATIONS_CACHE.get(
|
||||
"entity.sensor.worst_count",
|
||||
"Worst count"
|
||||
)
|
||||
|
||||
price_count_key = _TRANSLATIONS_CACHE.get(
|
||||
"entity.sensor.price_count",
|
||||
"Price count"
|
||||
)
|
||||
|
||||
last_updated_key = _TRANSLATIONS_CACHE.get(
|
||||
"entity.sensor.last_updated",
|
||||
"Last updated"
|
||||
)
|
||||
|
||||
avg_price_key = _TRANSLATIONS_CACHE.get(
|
||||
"entity.sensor.avg_price",
|
||||
"Average price today"
|
||||
)
|
||||
|
||||
avg_price_remaining_key = _TRANSLATIONS_CACHE.get(
|
||||
"entity.sensor.avg_price_remaining",
|
||||
"Average price remaining"
|
||||
)
|
||||
|
||||
avg_price_full_day_key = _TRANSLATIONS_CACHE.get(
|
||||
"entity.sensor.avg_price_full_day",
|
||||
"Average price full day"
|
||||
)
|
||||
|
||||
tomorrow_available_key = _TRANSLATIONS_CACHE.get(
|
||||
"entity.sensor.tomorrow_available",
|
||||
"Tomorrow prices available"
|
||||
)
|
||||
|
||||
mqtt_price_count_key = _TRANSLATIONS_CACHE.get(
|
||||
"entity.sensor.mqtt_price_count",
|
||||
"MQTT price count"
|
||||
)
|
||||
|
||||
if self.coordinator.data is None:
|
||||
return {
|
||||
f"{avg_price_key} /0": None,
|
||||
f"{avg_price_key} /24": None,
|
||||
next_hour_key: None,
|
||||
all_prices_key: [],
|
||||
best_prices_key: [],
|
||||
worst_prices_key: [],
|
||||
best_count_key: self.top_count,
|
||||
worst_count_key: self.worst_count,
|
||||
price_count_key: 0,
|
||||
using_cached_key: False,
|
||||
tomorrow_available_key: False,
|
||||
mqtt_price_count_key: 0
|
||||
}
|
||||
|
||||
next_hour_data = self._get_next_hour_price()
|
||||
today = self.coordinator.data.get("prices_today", [])
|
||||
is_cached = self.coordinator.data.get("is_cached", False)
|
||||
|
||||
# Calculate average price for remaining hours today (from current hour)
|
||||
avg_price_remaining = None
|
||||
remaining_hours_count = 0
|
||||
avg_price_full_day = None
|
||||
|
||||
if today:
|
||||
# Full day average (all 24 hours)
|
||||
total_price_full = sum(p.get("price", 0) for p in today if p.get("price") is not None)
|
||||
valid_prices_count_full = sum(1 for p in today if p.get("price") is not None)
|
||||
if valid_prices_count_full > 0:
|
||||
avg_price_full_day = round(total_price_full / valid_prices_count_full, 2)
|
||||
|
||||
# Remaining hours average (from current hour onwards)
|
||||
current_hour = now.strftime("%Y-%m-%dT%H:")
|
||||
remaining_prices = []
|
||||
|
||||
for p in today:
|
||||
if p.get("price") is not None and p.get("start", "") >= current_hour:
|
||||
remaining_prices.append(p.get("price"))
|
||||
|
||||
remaining_hours_count = len(remaining_prices)
|
||||
if remaining_hours_count > 0:
|
||||
avg_price_remaining = round(sum(remaining_prices) / remaining_hours_count, 2)
|
||||
|
||||
# Create keys with hour count in user's preferred format
|
||||
avg_price_remaining_with_hours = f"{avg_price_key} /{remaining_hours_count}"
|
||||
avg_price_full_day_with_hours = f"{avg_price_key} /24"
|
||||
|
||||
# Check if tomorrow's prices are available (more robust check)
|
||||
all_prices = self.coordinator.data.get("prices", [])
|
||||
tomorrow = (now + timedelta(days=1)).strftime("%Y-%m-%d")
|
||||
tomorrow_prices = []
|
||||
|
||||
# Only check for tomorrow prices if we have a reasonable amount of data
|
||||
if len(all_prices) > 0:
|
||||
tomorrow_prices = [p for p in all_prices if p.get("start", "").startswith(tomorrow)]
|
||||
|
||||
# Log what we found for debugging
|
||||
if tomorrow_prices:
|
||||
unique_values = set(p.get("price") for p in tomorrow_prices if p.get("price") is not None)
|
||||
consecutive = self._count_consecutive_same_values(tomorrow_prices)
|
||||
_LOGGER.debug(
|
||||
f"Tomorrow has {len(tomorrow_prices)} prices, "
|
||||
f"{len(unique_values)} unique values, "
|
||||
f"max {consecutive} consecutive same values"
|
||||
)
|
||||
|
||||
# Tomorrow is available only if:
|
||||
# 1. We have at least 20 hours of data for tomorrow
|
||||
# 2. The data doesn't look like placeholders
|
||||
tomorrow_available = (
|
||||
len(tomorrow_prices) >= 20 and
|
||||
not self._is_likely_placeholder_data(tomorrow_prices)
|
||||
)
|
||||
|
||||
# Get cached sorted prices
|
||||
sorted_prices = self._get_cached_sorted_prices(today) if today else {"best": [], "worst": []}
|
||||
|
||||
# Get actual MQTT price count
|
||||
mqtt_price_count = self._get_mqtt_price_count()
|
||||
|
||||
return {
|
||||
avg_price_remaining_with_hours: avg_price_remaining,
|
||||
avg_price_full_day_with_hours: avg_price_full_day,
|
||||
next_hour_key: next_hour_data,
|
||||
"all_prices": today,
|
||||
"best_prices": sorted_best_prices[: self.top_count],
|
||||
"worst_prices": sorted_worst_prices[: self.worst_count],
|
||||
"top_count": self.top_count,
|
||||
"worst_count": self.worst_count,
|
||||
"price_count": len(today),
|
||||
"last_updated": now.isoformat(),
|
||||
using_cached_key: is_cached
|
||||
all_prices_key: today,
|
||||
best_prices_key: sorted_prices["best"],
|
||||
worst_prices_key: sorted_prices["worst"],
|
||||
best_count_key: self.top_count,
|
||||
worst_count_key: self.worst_count,
|
||||
price_count_key: len(today),
|
||||
last_updated_key: now.strftime("%Y-%m-%d %H:%M:%S"),
|
||||
using_cached_key: is_cached,
|
||||
tomorrow_available_key: tomorrow_available,
|
||||
mqtt_price_count_key: mqtt_price_count,
|
||||
"mqtt_48h_mode": self.coordinator.mqtt_48h_mode
|
||||
}
|
||||
|
||||
@property
|
||||
|
||||
Reference in New Issue
Block a user