hass.tibber_prices/custom_components/tibber_prices/sensor/attributes/interval.py
Julian Pawlowski edabb49309 feat(sensors): expose energy/tax breakdown as sensor attributes
Add energy_price and tax attributes to interval and daily stat sensors:

- Interval sensors (current/next/previous): energy_price and tax from
  the specific 15-minute interval
- Daily min/max sensors: energy_price and tax from the extreme interval
- Daily average sensors: energy_price_mean, energy_price_median,
  tax_mean, tax_median — matching the existing mean/median pattern
  used for the main price attribute

Calculator caches both mean and median for energy/tax using
calculate_median() from utils/average. All new attributes are
excluded from Recorder to prevent database bloat.

Impact: Users can see price composition (spot price vs. taxes) on
all major price sensors. Enables solar feed-in and net metering
automations based on raw energy prices.
2026-04-09 18:27:36 +00:00

306 lines
11 KiB
Python

"""Interval attribute builders for Tibber Prices sensors."""
from __future__ import annotations
from datetime import timedelta
from typing import TYPE_CHECKING, Any
from custom_components.tibber_prices.const import (
PRICE_LEVEL_MAPPING,
PRICE_RATING_MAPPING,
get_display_unit_factor,
)
from custom_components.tibber_prices.entity_utils import add_icon_color_attribute
from custom_components.tibber_prices.utils.price import find_price_data_for_interval
if TYPE_CHECKING:
from custom_components.tibber_prices.coordinator.core import (
TibberPricesDataUpdateCoordinator,
)
from custom_components.tibber_prices.coordinator.time_service import TibberPricesTimeService
from custom_components.tibber_prices.data import TibberPricesConfigEntry
from .helpers import add_alternate_average_attribute
from .metadata import get_current_interval_data
def _get_interval_data_for_attributes(
key: str,
coordinator: TibberPricesDataUpdateCoordinator,
attributes: dict,
*,
time: TibberPricesTimeService,
) -> dict | None:
"""
Get interval data and set timestamp based on sensor type.
Refactored to reduce branch complexity in main function.
Args:
key: The sensor entity key
coordinator: The data update coordinator
attributes: Attributes dict to update with timestamp if needed
time: TibberPricesTimeService instance
Returns:
Interval data if found, None otherwise
"""
now = time.now()
# Current/next price sensors - override timestamp with interval's startsAt
next_sensors = ["next_interval_price", "next_interval_price_level", "next_interval_price_rating"]
prev_sensors = ["previous_interval_price", "previous_interval_price_level", "previous_interval_price_rating"]
next_hour = ["next_hour_average_price", "next_hour_price_level", "next_hour_price_rating"]
curr_interval = ["current_interval_price", "current_interval_price_base"]
curr_hour = ["current_hour_average_price", "current_hour_price_level", "current_hour_price_rating"]
if key in next_sensors:
target_time = time.get_next_interval_start()
interval_data = find_price_data_for_interval(coordinator.data, target_time, time=time)
if interval_data:
attributes["timestamp"] = interval_data["startsAt"]
return interval_data
if key in prev_sensors:
target_time = time.get_interval_offset_time(-1)
interval_data = find_price_data_for_interval(coordinator.data, target_time, time=time)
if interval_data:
attributes["timestamp"] = interval_data["startsAt"]
return interval_data
if key in next_hour:
target_time = now + timedelta(hours=1)
interval_data = find_price_data_for_interval(coordinator.data, target_time, time=time)
if interval_data:
attributes["timestamp"] = interval_data["startsAt"]
return interval_data
# Current interval sensors (both variants)
if key in curr_interval:
interval_data = get_current_interval_data(coordinator, time=time)
if interval_data and "startsAt" in interval_data:
attributes["timestamp"] = interval_data["startsAt"]
return interval_data
# Current hour sensors - keep default timestamp
if key in curr_hour:
return get_current_interval_data(coordinator, time=time)
return None
def _add_energy_tax_attributes(
attributes: dict,
interval_data: dict | None,
*,
config_entry: TibberPricesConfigEntry,
) -> None:
"""
Add energy_price and tax attributes from interval data.
The API provides `energy` (raw spot price) and `tax` (tax component) in base
currency. These are converted to display units using the same factor as `total`.
Args:
attributes: Dictionary to add attributes to
interval_data: Price interval data dict (may contain energy/tax fields)
config_entry: Config entry for display unit preference
"""
if not interval_data:
return
factor = get_display_unit_factor(config_entry)
energy = interval_data.get("energy")
if energy is not None:
attributes["energy_price"] = round(float(energy) * factor, 2)
tax = interval_data.get("tax")
if tax is not None:
attributes["tax"] = round(float(tax) * factor, 2)
def add_current_interval_price_attributes( # noqa: PLR0913
attributes: dict,
key: str,
coordinator: TibberPricesDataUpdateCoordinator,
native_value: Any,
cached_data: dict,
*,
time: TibberPricesTimeService,
config_entry: TibberPricesConfigEntry,
) -> None:
"""
Add attributes for current interval price sensors.
Args:
attributes: Dictionary to add attributes to
key: The sensor entity key
coordinator: The data update coordinator
native_value: The current native value of the sensor
cached_data: Dictionary containing cached sensor data
time: TibberPricesTimeService instance (required)
config_entry: Config entry for user preferences
"""
# Get interval data and handle timestamp overrides
interval_data = _get_interval_data_for_attributes(key, coordinator, attributes, time=time)
# Add icon_color for price sensors (based on their price level)
if key in [
"current_interval_price",
"current_interval_price_base",
"next_interval_price",
"previous_interval_price",
]:
# For interval-based price sensors, get level from interval_data
if interval_data and "level" in interval_data:
level = interval_data["level"]
add_icon_color_attribute(attributes, key="price_level", state_value=level)
# Add energy_price and tax attributes from raw API data
_add_energy_tax_attributes(attributes, interval_data, config_entry=config_entry)
elif key in ["current_hour_average_price", "next_hour_average_price"]:
# For hour-based price sensors, get level from cached_data
level = cached_data.get("rolling_hour_level")
if level:
add_icon_color_attribute(attributes, key="price_level", state_value=level)
# Add alternate average attribute for rolling hour average price sensors
base_key = "rolling_hour_0" if key == "current_hour_average_price" else "rolling_hour_1"
add_alternate_average_attribute(
attributes,
cached_data,
base_key,
config_entry=config_entry,
)
# Add price level attributes for all level sensors
add_level_attributes_for_sensor(
attributes=attributes,
key=key,
interval_data=interval_data,
coordinator=coordinator,
native_value=native_value,
time=time,
)
# Add price rating attributes for all rating sensors
add_rating_attributes_for_sensor(
attributes=attributes,
key=key,
interval_data=interval_data,
coordinator=coordinator,
native_value=native_value,
time=time,
)
def add_level_attributes_for_sensor( # noqa: PLR0913
attributes: dict,
key: str,
interval_data: dict | None,
coordinator: TibberPricesDataUpdateCoordinator,
native_value: Any,
*,
time: TibberPricesTimeService,
) -> None:
"""
Add price level attributes based on sensor type.
Args:
attributes: Dictionary to add attributes to
key: The sensor entity key
interval_data: Interval data for next/previous sensors
coordinator: The data update coordinator
native_value: The current native value of the sensor
time: TibberPricesTimeService instance (required)
"""
# For interval-based level sensors (next/previous), use interval data
if key in ["next_interval_price_level", "previous_interval_price_level"]:
if interval_data and "level" in interval_data:
add_price_level_attributes(attributes, interval_data["level"])
# For hour-aggregated level sensors, use native_value
elif key in ["current_hour_price_level", "next_hour_price_level"]:
level_value = native_value
if level_value and isinstance(level_value, str):
add_price_level_attributes(attributes, level_value.upper())
# For current price level sensor
elif key == "current_interval_price_level":
current_interval_data = get_current_interval_data(coordinator, time=time)
if current_interval_data and "level" in current_interval_data:
add_price_level_attributes(attributes, current_interval_data["level"])
def add_price_level_attributes(attributes: dict, level: str) -> None:
"""
Add price level specific attributes.
Args:
attributes: Dictionary to add attributes to
level: The price level value (e.g., VERY_CHEAP, NORMAL, etc.)
"""
if level in PRICE_LEVEL_MAPPING:
attributes["level_value"] = PRICE_LEVEL_MAPPING[level]
attributes["level_id"] = level
# Add icon_color for dynamic styling
add_icon_color_attribute(attributes, key="price_level", state_value=level)
def add_rating_attributes_for_sensor( # noqa: PLR0913
attributes: dict,
key: str,
interval_data: dict | None,
coordinator: TibberPricesDataUpdateCoordinator,
native_value: Any,
*,
time: TibberPricesTimeService,
) -> None:
"""
Add price rating attributes based on sensor type.
Args:
attributes: Dictionary to add attributes to
key: The sensor entity key
interval_data: Interval data for next/previous sensors
coordinator: The data update coordinator
native_value: The current native value of the sensor
time: TibberPricesTimeService instance (required)
"""
# For interval-based rating sensors (next/previous), use interval data
if key in ["next_interval_price_rating", "previous_interval_price_rating"]:
if interval_data and "rating_level" in interval_data:
add_price_rating_attributes(attributes, interval_data["rating_level"])
# For hour-aggregated rating sensors, use native_value
elif key in ["current_hour_price_rating", "next_hour_price_rating"]:
rating_value = native_value
if rating_value and isinstance(rating_value, str):
add_price_rating_attributes(attributes, rating_value.upper())
# For current price rating sensor
elif key == "current_interval_price_rating":
current_interval_data = get_current_interval_data(coordinator, time=time)
if current_interval_data and "rating_level" in current_interval_data:
add_price_rating_attributes(attributes, current_interval_data["rating_level"])
def add_price_rating_attributes(attributes: dict, rating: str) -> None:
"""
Add price rating specific attributes.
Args:
attributes: Dictionary to add attributes to
rating: The price rating value (e.g., LOW, NORMAL, HIGH)
"""
if rating in PRICE_RATING_MAPPING:
attributes["rating_value"] = PRICE_RATING_MAPPING[rating]
attributes["rating_id"] = rating
# Add icon_color for dynamic styling
add_icon_color_attribute(attributes, key="price_rating", state_value=rating)