82 lines
2.6 KiB
Python
82 lines
2.6 KiB
Python
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"""Statistics helper for sensor."""
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from __future__ import annotations
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import datetime
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import statistics
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from homeassistant.components.recorder import history
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from homeassistant.components.sensor import ATTR_STATE_CLASS, STATE_CLASS_MEASUREMENT
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from homeassistant.const import ATTR_DEVICE_CLASS
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from homeassistant.core import HomeAssistant
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from . import DOMAIN
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DEVICE_CLASS_STATISTICS = {"temperature": {"mean", "min", "max"}}
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def _get_entities(hass: HomeAssistant) -> list[tuple[str, str]]:
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"""Get (entity_id, device_class) of all sensors for which to compile statistics."""
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all_sensors = hass.states.all(DOMAIN)
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entity_ids = []
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for state in all_sensors:
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device_class = state.attributes.get(ATTR_DEVICE_CLASS)
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state_class = state.attributes.get(ATTR_STATE_CLASS)
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if not state_class or state_class != STATE_CLASS_MEASUREMENT:
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continue
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if not device_class or device_class not in DEVICE_CLASS_STATISTICS:
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continue
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entity_ids.append((state.entity_id, device_class))
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return entity_ids
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# Faster than try/except
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# From https://stackoverflow.com/a/23639915
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def _is_number(s: str) -> bool: # pylint: disable=invalid-name
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"""Return True if string is a number."""
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return s.replace(".", "", 1).isdigit()
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def compile_statistics(
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hass: HomeAssistant, start: datetime.datetime, end: datetime.datetime
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) -> dict:
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"""Compile statistics for all entities during start-end.
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Note: This will query the database and must not be run in the event loop
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"""
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result: dict = {}
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entities = _get_entities(hass)
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# Get history between start and end
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history_list = history.get_significant_states( # type: ignore
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hass, start, end, [i[0] for i in entities]
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)
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for entity_id, device_class in entities:
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wanted_statistics = DEVICE_CLASS_STATISTICS[device_class]
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if entity_id not in history_list:
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continue
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entity_history = history_list[entity_id]
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fstates = [float(el.state) for el in entity_history if _is_number(el.state)]
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if not fstates:
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continue
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result[entity_id] = {}
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# Make calculations
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if "max" in wanted_statistics:
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result[entity_id]["max"] = max(fstates)
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if "min" in wanted_statistics:
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result[entity_id]["min"] = min(fstates)
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# Note: The average calculation will be incorrect for unevenly spaced readings,
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# this needs to be improved by weighting with time between measurements
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if "mean" in wanted_statistics:
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result[entity_id]["mean"] = statistics.fmean(fstates)
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return result
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