mirror of
https://github.com/jpawlowski/hass.tibber_prices.git
synced 2026-05-28 18:43:40 +00:00
2f704a35a3
Remove unused functions, constants, and entity definitions that were left over from previous refactorings. All removed code was either superseded by better implementations or never actually called. Removed functions: - entity_utils/helpers.py: translate_level(), translate_rating_level() (HA handles ENUM translation automatically via translations/*.json) - entity_utils/attributes.py: build_timestamp_attribute(), build_period_attributes() (superseded by inline implementations) - sensor/helpers.py: get_hourly_price_value(), aggregate_window_data() (replaced by Calculator Pattern in sensor/calculators/) Removed constants and definitions: - const.py: CONF_CHART_DATA_CONFIG (DATA_CHART_CONFIG is the active one), PRICE_LEVEL_OPTIONS, PRICE_RATING_OPTIONS, VOLATILITY_OPTIONS, PRICE_TREND_OPTIONS (never imported; options defined inline in definitions.py due to HA import timing constraints), async_get_home_type_translation() (sync version used instead) - coordinator/core.py: FRESH_TO_CACHED_SECONDS (leftover from old caching strategy, never referenced) - switch/definitions.py: BEST_PRICE_SWITCH_ENTITIES (duplicate of BEST_PRICE_SWITCH_ENTITY_DESCRIPTIONS using base class instead of custom TibberPricesSwitchEntityDescription subclass) Cleanup: - entity_utils/__init__.py: Remove exports for deleted functions - sensor/helpers.py: Remove now-unused imports (timedelta, get_intervals_for_day_offsets, get_price_value, Callable) - entity_utils/helpers.py: Remove unused get_price_level_translation import after translate_level() removal - sensor/definitions.py: Update 7x "Keep in sync with *_OPTIONS" comments to reference individual PRICE_LEVEL_*/PRICE_RATING_*/ VOLATILITY_* constants instead Impact: No user-visible changes. Reduces codebase by ~130 lines. Improves maintainability by eliminating misleading dead code.
97 lines
3.1 KiB
Python
97 lines
3.1 KiB
Python
"""
|
|
Sensor platform-specific helper functions.
|
|
|
|
This module contains helper functions specific to the sensor platform:
|
|
- aggregate_price_data: Calculate average price from window data
|
|
- aggregate_level_data: Aggregate price levels from intervals
|
|
- aggregate_rating_data: Aggregate price ratings from intervals
|
|
|
|
For shared helper functions (used by both sensor and binary_sensor platforms),
|
|
see entity_utils/helpers.py:
|
|
- get_price_value: Price unit conversion
|
|
- find_rolling_hour_center_index: Rolling hour window calculations
|
|
"""
|
|
|
|
from __future__ import annotations
|
|
|
|
from typing import TYPE_CHECKING
|
|
|
|
from custom_components.tibber_prices.const import get_display_unit_factor
|
|
from custom_components.tibber_prices.utils.average import calculate_mean, calculate_median
|
|
from custom_components.tibber_prices.utils.price import (
|
|
aggregate_price_levels,
|
|
aggregate_price_rating,
|
|
)
|
|
|
|
if TYPE_CHECKING:
|
|
from homeassistant.config_entries import ConfigEntry
|
|
|
|
|
|
def aggregate_average_data(
|
|
window_data: list[dict],
|
|
config_entry: ConfigEntry,
|
|
) -> tuple[float | None, float | None]:
|
|
"""
|
|
Calculate average and median price from window data.
|
|
|
|
Args:
|
|
window_data: List of price interval dictionaries with 'total' key.
|
|
config_entry: Config entry to get display unit configuration.
|
|
|
|
Returns:
|
|
Tuple of (average price, median price) in display currency units,
|
|
or (None, None) if no prices.
|
|
|
|
"""
|
|
prices = [float(i["total"]) for i in window_data if "total" in i]
|
|
if not prices:
|
|
return None, None
|
|
# Calculate both mean and median
|
|
mean = calculate_mean(prices)
|
|
median = calculate_median(prices)
|
|
# Convert to display currency unit based on configuration
|
|
factor = get_display_unit_factor(config_entry)
|
|
return round(mean * factor, 2), round(median * factor, 2) if median is not None else None
|
|
|
|
|
|
def aggregate_level_data(window_data: list[dict]) -> str | None:
|
|
"""
|
|
Aggregate price levels from window data.
|
|
|
|
Args:
|
|
window_data: List of price interval dictionaries with 'level' key
|
|
|
|
Returns:
|
|
Aggregated price level (lowercase), or None if no levels
|
|
|
|
"""
|
|
levels = [i["level"] for i in window_data if "level" in i]
|
|
if not levels:
|
|
return None
|
|
aggregated = aggregate_price_levels(levels)
|
|
return aggregated.lower() if aggregated else None
|
|
|
|
|
|
def aggregate_rating_data(
|
|
window_data: list[dict],
|
|
threshold_low: float,
|
|
threshold_high: float,
|
|
) -> str | None:
|
|
"""
|
|
Aggregate price ratings from window data.
|
|
|
|
Args:
|
|
window_data: List of price interval dictionaries with 'difference' and 'rating_level'
|
|
threshold_low: Low threshold for rating calculation
|
|
threshold_high: High threshold for rating calculation
|
|
|
|
Returns:
|
|
Aggregated price rating (lowercase), or None if no ratings
|
|
|
|
"""
|
|
differences = [i["difference"] for i in window_data if "difference" in i and "rating_level" in i]
|
|
if not differences:
|
|
return None
|
|
|
|
aggregated, _ = aggregate_price_rating(differences, threshold_low, threshold_high)
|
|
return aggregated.lower() if aggregated else None
|