core/homeassistant/components/sensor/recorder.py

136 lines
4.8 KiB
Python

"""Statistics helper for sensor."""
from __future__ import annotations
import datetime
import itertools
from statistics import fmean
from homeassistant.components.recorder import history, statistics
from homeassistant.components.sensor import (
ATTR_STATE_CLASS,
DEVICE_CLASS_BATTERY,
DEVICE_CLASS_ENERGY,
DEVICE_CLASS_HUMIDITY,
DEVICE_CLASS_PRESSURE,
DEVICE_CLASS_TEMPERATURE,
STATE_CLASS_MEASUREMENT,
)
from homeassistant.const import ATTR_DEVICE_CLASS
from homeassistant.core import HomeAssistant
import homeassistant.util.dt as dt_util
from . import DOMAIN
DEVICE_CLASS_STATISTICS = {
DEVICE_CLASS_BATTERY: {"mean", "min", "max"},
DEVICE_CLASS_ENERGY: {"sum"},
DEVICE_CLASS_HUMIDITY: {"mean", "min", "max"},
DEVICE_CLASS_PRESSURE: {"mean", "min", "max"},
DEVICE_CLASS_TEMPERATURE: {"mean", "min", "max"},
}
def _get_entities(hass: HomeAssistant) -> list[tuple[str, str]]:
"""Get (entity_id, device_class) of all sensors for which to compile statistics."""
all_sensors = hass.states.all(DOMAIN)
entity_ids = []
for state in all_sensors:
device_class = state.attributes.get(ATTR_DEVICE_CLASS)
state_class = state.attributes.get(ATTR_STATE_CLASS)
if not state_class or state_class != STATE_CLASS_MEASUREMENT:
continue
if not device_class or device_class not in DEVICE_CLASS_STATISTICS:
continue
entity_ids.append((state.entity_id, device_class))
return entity_ids
# Faster than try/except
# From https://stackoverflow.com/a/23639915
def _is_number(s: str) -> bool: # pylint: disable=invalid-name
"""Return True if string is a number."""
return s.replace(".", "", 1).isdigit()
def compile_statistics(
hass: HomeAssistant, start: datetime.datetime, end: datetime.datetime
) -> dict:
"""Compile statistics for all entities during start-end.
Note: This will query the database and must not be run in the event loop
"""
result: dict = {}
entities = _get_entities(hass)
# Get history between start and end
history_list = history.get_significant_states( # type: ignore
hass, start - datetime.timedelta.resolution, end, [i[0] for i in entities]
)
for entity_id, device_class in entities:
wanted_statistics = DEVICE_CLASS_STATISTICS[device_class]
if entity_id not in history_list:
continue
entity_history = history_list[entity_id]
fstates = [
(float(el.state), el) for el in entity_history if _is_number(el.state)
]
if not fstates:
continue
result[entity_id] = {}
# Make calculations
if "max" in wanted_statistics:
result[entity_id]["max"] = max(*itertools.islice(zip(*fstates), 1))
if "min" in wanted_statistics:
result[entity_id]["min"] = min(*itertools.islice(zip(*fstates), 1))
# Note: The average calculation will be incorrect for unevenly spaced readings,
# this needs to be improved by weighting with time between measurements
if "mean" in wanted_statistics:
result[entity_id]["mean"] = fmean(*itertools.islice(zip(*fstates), 1))
if "sum" in wanted_statistics:
last_reset = old_last_reset = None
new_state = old_state = None
_sum = 0
last_stats = statistics.get_last_statistics(hass, 1, entity_id) # type: ignore
if entity_id in last_stats:
# We have compiled history for this sensor before, use that as a starting point
last_reset = old_last_reset = last_stats[entity_id][0]["last_reset"]
new_state = old_state = last_stats[entity_id][0]["state"]
_sum = last_stats[entity_id][0]["sum"]
for fstate, state in fstates:
if "last_reset" not in state.attributes:
continue
if (last_reset := state.attributes["last_reset"]) != old_last_reset:
# The sensor has been reset, update the sum
if old_state is not None:
_sum += new_state - old_state
# ..and update the starting point
new_state = fstate
old_last_reset = last_reset
old_state = new_state
else:
new_state = fstate
if last_reset is None or new_state is None or old_state is None:
# No valid updates
result.pop(entity_id)
continue
# Update the sum with the last state
_sum += new_state - old_state
result[entity_id]["last_reset"] = dt_util.parse_datetime(last_reset)
result[entity_id]["sum"] = _sum
result[entity_id]["state"] = new_state
return result