hass.tibber_prices/custom_components/tibber_prices/entity_utils/icons.py
Julian Pawlowski 5fc1f4db33 feat(sensors): add 5-level price trend scale with configurable thresholds
Extends trend sensors from 3-level (rising/stable/falling) to 5-level scale
(strongly_rising/rising/stable/falling/strongly_falling) for finer granularity.

Changes:
- Add PRICE_TREND_MAPPING with integer values (-2, -1, 0, +1, +2) matching
  PRICE_LEVEL_MAPPING pattern for consistent automation comparisons
- Add configurable thresholds for strongly_rising (default: 6%) and
  strongly_falling (default: -6%) independent from base thresholds
- Update calculate_price_trend() to return 3-tuple: (trend_state, diff_pct, trend_value)
- Add trend_value attribute to all trend sensors for numeric comparisons
- Update sensor entity descriptions with 5-level options
- Add validation with cross-checks (strongly_rising > rising, etc.)
- Update icons: chevron-double-up/down for strong trends, trending-up/down for normal

Files changed:
- const.py: PRICE_TREND_* constants, PRICE_TREND_MAPPING, config constants
- utils/price.py: Extended calculate_price_trend() signature and return value
- sensor/calculators/trend.py: Pass new thresholds, handle 3-tuple return
- sensor/definitions.py: 5-level options for all 9 trend sensors
- sensor/core.py: 5-level icon mapping
- entity_utils/icons.py: 5-level trend icons
- config_flow_handlers/: validators, schemas, options_flow for new settings
- translations/*.json: Labels and error messages (en, de, nb, sv, nl)
- tests/test_percentage_calculations.py: Updated for 3-tuple return

Impact: Users get more nuanced trend information for automation decisions.
New trend_value attribute enables numeric comparisons (e.g., > 0 for any rise).
Existing automations using "rising"/"falling"/"stable" continue to work.
2026-01-20 13:36:01 +00:00

391 lines
14 KiB
Python

"""Icon utilities for Tibber Prices entities."""
from __future__ import annotations
from collections.abc import Callable
from dataclasses import dataclass
from datetime import timedelta
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from custom_components.tibber_prices.coordinator.time_service import TibberPricesTimeService
from custom_components.tibber_prices.const import (
BINARY_SENSOR_ICON_MAPPING,
PRICE_LEVEL_CASH_ICON_MAPPING,
PRICE_LEVEL_ICON_MAPPING,
PRICE_RATING_ICON_MAPPING,
VOLATILITY_ICON_MAPPING,
)
from custom_components.tibber_prices.coordinator.helpers import get_intervals_for_day_offsets
from custom_components.tibber_prices.entity_utils.helpers import find_rolling_hour_center_index
from custom_components.tibber_prices.sensor.helpers import aggregate_level_data
from custom_components.tibber_prices.utils.price import find_price_data_for_interval
# Icon update logic uses timedelta directly (cosmetic, independent - allowed per AGENTS.md)
_INTERVAL_MINUTES = 15 # Tibber's 15-minute intervals
@dataclass
class TibberPricesIconContext:
"""Context data for dynamic icon selection."""
is_on: bool | None = None
coordinator_data: dict | None = None
has_future_periods_callback: Callable[[], bool] | None = None
period_is_active_callback: Callable[[], bool] | None = None
time: TibberPricesTimeService | None = None
if TYPE_CHECKING:
from collections.abc import Callable
# Timing sensor icon thresholds (in minutes)
TIMING_URGENT_THRESHOLD = 15 # ≤15 min: Alert icon
TIMING_SOON_THRESHOLD = 60 # ≤1 hour: Timer icon
TIMING_MEDIUM_THRESHOLD = 180 # ≤3 hours: Sand timer icon
# >3 hours: Outline timer icon
# Progress sensor constants
PROGRESS_MAX = 100 # Maximum progress value (100%)
def get_dynamic_icon(
key: str,
value: Any,
*,
context: TibberPricesIconContext | None = None,
) -> str | None:
"""
Get dynamic icon based on sensor state.
Unified function for both sensor and binary_sensor platforms.
Args:
key: Entity description key
value: Native value of the sensor
context: Optional context with is_on state, coordinator_data, and callbacks
Returns:
Icon string or None if no dynamic icon applies
"""
ctx = context or TibberPricesIconContext()
# Try various icon sources in order
return (
get_trend_icon(key, value)
or get_timing_sensor_icon(key, value, period_is_active_callback=ctx.period_is_active_callback)
or get_price_sensor_icon(key, ctx.coordinator_data, time=ctx.time)
or get_level_sensor_icon(key, value)
or get_rating_sensor_icon(key, value)
or get_volatility_sensor_icon(key, value)
or get_binary_sensor_icon(key, is_on=ctx.is_on, has_future_periods_callback=ctx.has_future_periods_callback)
)
def get_trend_icon(key: str, value: Any) -> str | None:
"""Get icon for trend sensors using 5-level trend scale."""
# Handle next_price_trend_change TIMESTAMP sensor differently
# (icon based on attributes, not value which is a timestamp)
if key == "next_price_trend_change":
return None # Will be handled by sensor's icon property using attributes
if not key.startswith("price_trend_") and key != "current_price_trend":
return None
if not isinstance(value, str):
return None
# 5-level trend icons: strongly uses double arrows, normal uses single
trend_icons = {
"strongly_rising": "mdi:chevron-double-up", # Strong upward movement
"rising": "mdi:trending-up", # Normal upward trend
"stable": "mdi:trending-neutral", # No significant change
"falling": "mdi:trending-down", # Normal downward trend
"strongly_falling": "mdi:chevron-double-down", # Strong downward movement
}
return trend_icons.get(value)
def get_timing_sensor_icon(
key: str,
value: Any,
*,
period_is_active_callback: Callable[[], bool] | None = None,
) -> str | None:
"""
Get dynamic icon for best_price/peak_price timing sensors.
Progress sensors: Different icons based on period state
- No period: mdi:help-circle-outline (Unknown/gray)
- Waiting (0%, period not active): mdi:timer-pause-outline (paused/waiting)
- Active (0%, period running): mdi:circle-outline (just started)
- Progress 1-99%: mdi:circle-slice-1 to mdi:circle-slice-7
- Complete (100%): mdi:circle-slice-8
Remaining/Next-in sensors: Different timer icons based on time remaining
Timestamp sensors: Static icons (handled by entity description)
Args:
key: Entity description key
value: Sensor value (percentage for progress, minutes for countdown)
period_is_active_callback: Callback to check if related period is currently active
Returns:
Icon string or None if not a timing sensor with dynamic icon
"""
# Unknown state: Show help icon for all timing sensors
if value is None and key.startswith(("best_price_", "peak_price_")):
return "mdi:help-circle-outline"
# Progress sensors: Circle-slice icons for visual progress indication
# mdi:circle-slice-N where N represents filled portions (1=12.5%, 8=100%)
if key.endswith("_progress") and isinstance(value, (int, float)):
# Special handling for 0%: Distinguish between waiting and active
if value <= 0:
# Check if period is currently active via callback
is_active = (
period_is_active_callback()
if (period_is_active_callback and callable(period_is_active_callback))
else True
)
# Period just started (0% but running) vs waiting for next
return "mdi:circle-outline" if is_active else "mdi:timer-pause-outline"
# Calculate slice based on progress percentage
slice_num = 8 if value >= PROGRESS_MAX else min(7, max(1, int((value / PROGRESS_MAX) * 8)))
return f"mdi:circle-slice-{slice_num}"
# Remaining/Next-in minutes sensors: Timer icons based on urgency thresholds
if key.endswith(("_remaining_minutes", "_next_in_minutes")) and isinstance(value, (int, float)):
# Map time remaining to appropriate timer icon
urgency_map = [
(0, "mdi:timer-off-outline"), # Exactly 0 minutes
(TIMING_URGENT_THRESHOLD, "mdi:timer-alert"), # < 15 min: urgent
(TIMING_SOON_THRESHOLD, "mdi:timer"), # < 60 min: soon
(TIMING_MEDIUM_THRESHOLD, "mdi:timer-sand"), # < 180 min: medium
]
for threshold, icon in urgency_map:
if value <= threshold:
return icon
return "mdi:timer-outline" # >= 180 min: far away
# Timestamp sensors use static icons from entity description
return None
def get_price_sensor_icon(
key: str,
coordinator_data: dict | None,
*,
time: TibberPricesTimeService | None,
) -> str | None:
"""
Get icon for current price sensors (dynamic based on price level).
Dynamic icons for: current_interval_price, next_interval_price,
current_hour_average_price, next_hour_average_price
Other price sensors (previous interval) use static icons from entity description.
Args:
key: Entity description key
coordinator_data: Coordinator data for price level lookups
time: TibberPricesTimeService instance (required for determining current interval)
Returns:
Icon string or None if not a current price sensor
"""
# Early exit if coordinator_data or time not available
if not coordinator_data or time is None:
return None
# Only current price sensors get dynamic icons
if key in ("current_interval_price", "current_interval_price_base"):
level = get_price_level_for_icon(coordinator_data, interval_offset=0, time=time)
if level:
return PRICE_LEVEL_CASH_ICON_MAPPING.get(level.upper())
elif key == "next_interval_price":
# For next interval, use the next interval price level to determine icon
level = get_price_level_for_icon(coordinator_data, interval_offset=1, time=time)
if level:
return PRICE_LEVEL_CASH_ICON_MAPPING.get(level.upper())
elif key == "current_hour_average_price":
# For current hour average, use the current hour price level to determine icon
level = get_rolling_hour_price_level_for_icon(coordinator_data, hour_offset=0, time=time)
if level:
return PRICE_LEVEL_CASH_ICON_MAPPING.get(level.upper())
elif key == "next_hour_average_price":
# For next hour average, use the next hour price level to determine icon
level = get_rolling_hour_price_level_for_icon(coordinator_data, hour_offset=1, time=time)
if level:
return PRICE_LEVEL_CASH_ICON_MAPPING.get(level.upper())
# For all other price sensors, let entity description handle the icon
return None
def get_level_sensor_icon(key: str, value: Any) -> str | None:
"""Get icon for price level sensors."""
if key not in [
"current_interval_price_level",
"next_interval_price_level",
"previous_interval_price_level",
"current_hour_price_level",
"next_hour_price_level",
"yesterday_price_level",
"today_price_level",
"tomorrow_price_level",
] or not isinstance(value, str):
return None
return PRICE_LEVEL_ICON_MAPPING.get(value.upper())
def get_rating_sensor_icon(key: str, value: Any) -> str | None:
"""Get icon for price rating sensors."""
if key not in [
"current_interval_price_rating",
"next_interval_price_rating",
"previous_interval_price_rating",
"current_hour_price_rating",
"next_hour_price_rating",
"yesterday_price_rating",
"today_price_rating",
"tomorrow_price_rating",
] or not isinstance(value, str):
return None
return PRICE_RATING_ICON_MAPPING.get(value.upper())
def get_volatility_sensor_icon(key: str, value: Any) -> str | None:
"""Get icon for volatility sensors."""
if not key.endswith("_volatility") or not isinstance(value, str):
return None
return VOLATILITY_ICON_MAPPING.get(value.upper())
def get_binary_sensor_icon(
key: str,
*,
is_on: bool | None,
has_future_periods_callback: Callable[[], bool] | None = None,
) -> str | None:
"""
Get icon for binary sensors with dynamic state-based icons.
Args:
key: Entity description key
is_on: Binary sensor state
has_future_periods_callback: Callback to check if future periods exist
Returns:
Icon string or None if not a binary sensor with dynamic icons
"""
if key not in BINARY_SENSOR_ICON_MAPPING or is_on is None:
return None
if is_on:
# Sensor is ON - use "on" icon
return BINARY_SENSOR_ICON_MAPPING[key].get("on")
# Sensor is OFF - check if future periods exist
has_future_periods = has_future_periods_callback() if has_future_periods_callback else False
if has_future_periods:
return BINARY_SENSOR_ICON_MAPPING[key].get("off")
return BINARY_SENSOR_ICON_MAPPING[key].get("off_no_future")
def get_price_level_for_icon(
coordinator_data: dict,
*,
interval_offset: int | None = None,
time: TibberPricesTimeService,
) -> str | None:
"""
Get the price level for icon determination.
Supports interval-based lookups (current/next/previous interval).
Args:
coordinator_data: Coordinator data
interval_offset: Interval offset (0=current, 1=next, -1=previous)
time: TibberPricesTimeService instance (required)
Returns:
Price level string or None if not found
"""
if not coordinator_data or interval_offset is None:
return None
now = time.now()
# Interval-based lookup
target_time = now + timedelta(minutes=_INTERVAL_MINUTES * interval_offset)
interval_data = find_price_data_for_interval(coordinator_data, target_time, time=time)
if not interval_data or "level" not in interval_data:
return None
return interval_data["level"]
def get_rolling_hour_price_level_for_icon(
coordinator_data: dict,
*,
hour_offset: int = 0,
time: TibberPricesTimeService,
) -> str | None:
"""
Get the aggregated price level for rolling hour icon determination.
Uses the same logic as the sensor platform: 5-interval rolling window
(2 before + center + 2 after) to determine the price level.
This ensures icon calculation matches the actual sensor value calculation.
Args:
coordinator_data: Coordinator data
hour_offset: Hour offset (0=current hour, 1=next hour)
time: TibberPricesTimeService instance (required)
Returns:
Aggregated price level string or None if not found
"""
if not coordinator_data:
return None
# Get all intervals (yesterday, today, tomorrow) via helper
all_prices = get_intervals_for_day_offsets(coordinator_data, [-1, 0, 1])
if not all_prices:
return None
# Find center index using the same helper function as the sensor platform
now = time.now()
center_idx = find_rolling_hour_center_index(all_prices, now, hour_offset, time=time)
if center_idx is None:
return None
# Collect data from 5-interval window (-2, -1, 0, +1, +2) - same as sensor platform
window_data = []
for offset in range(-2, 3):
idx = center_idx + offset
if 0 <= idx < len(all_prices):
window_data.append(all_prices[idx])
if not window_data:
return None
# Use the same aggregation function as the sensor platform
return aggregate_level_data(window_data)