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Code Issues Packages Projects Releases Wiki Activity

Allow selection of statistics state characteristic (#49960)

Browse Source 
* Make statistics state characteristic selectable

* Move computation in helper function

* Add relevant config elements for clarity

* Rename variables for better readability

* Avoid reserved prefix ATTR_ for stats

* Fix NoneType base_unit error

* Add testcases for statistics characteristic

* Add testcases for state_class, unitless, and characteristics

* Add testcase coverage for no unit with binary

* Replace error catching by an exception

* Attend to review comments
This commit is contained in:
Thomas Dietrich 2021-11-17 12:31:32 +01:00 committed by GitHub
parent 0f64e7036f
commit 0ab3b10aed
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2 changed files with 403 additions and 156 deletions
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368
homeassistant/components/statistics/sensor.py
View File

@ -8,12 +8,15 @@ import voluptuous as vol
from homeassistant.components.recorder.models import States
from homeassistant.components.recorder.util import execute, session_scope
from homeassistant.components.sensor import PLATFORM_SCHEMA, SensorEntity
from homeassistant.components.sensor import (
PLATFORM_SCHEMA,
STATE_CLASS_MEASUREMENT,
SensorEntity,
)
from homeassistant.const import (
ATTR_UNIT_OF_MEASUREMENT,
CONF_ENTITY_ID,
CONF_NAME,
EVENT_HOMEASSISTANT_START,
STATE_UNAVAILABLE,
STATE_UNKNOWN,
)
@ -24,36 +27,37 @@ from homeassistant.helpers.event import (
async_track_state_change_event,
)
from homeassistant.helpers.reload import async_setup_reload_service
from homeassistant.helpers.start import async_at_start
from homeassistant.util import dt as dt_util
from . import DOMAIN, PLATFORMS
_LOGGER = logging.getLogger(__name__)
ATTR_AVERAGE_CHANGE = "average_change"
ATTR_CHANGE = "change"
ATTR_CHANGE_RATE = "change_rate"
ATTR_COUNT = "count"
ATTR_MAX_AGE = "max_age"
ATTR_MAX_VALUE = "max_value"
ATTR_MEAN = "mean"
ATTR_MEDIAN = "median"
ATTR_MIN_AGE = "min_age"
ATTR_MIN_VALUE = "min_value"
ATTR_QUANTILES = "quantiles"
ATTR_SAMPLING_SIZE = "sampling_size"
ATTR_STANDARD_DEVIATION = "standard_deviation"
ATTR_TOTAL = "total"
ATTR_VARIANCE = "variance"
STAT_AVERAGE_CHANGE = "average_change"
STAT_CHANGE = "change"
STAT_CHANGE_RATE = "change_rate"
STAT_COUNT = "count"
STAT_MAX_AGE = "max_age"
STAT_MAX_VALUE = "max_value"
STAT_MEAN = "mean"
STAT_MEDIAN = "median"
STAT_MIN_AGE = "min_age"
STAT_MIN_VALUE = "min_value"
STAT_QUANTILES = "quantiles"
STAT_STANDARD_DEVIATION = "standard_deviation"
STAT_TOTAL = "total"
STAT_VARIANCE = "variance"
CONF_SAMPLING_SIZE = "sampling_size"
CONF_STATE_CHARACTERISTIC = "state_characteristic"
CONF_SAMPLES_MAX_BUFFER_SIZE = "sampling_size"
CONF_MAX_AGE = "max_age"
CONF_PRECISION = "precision"
CONF_QUANTILE_INTERVALS = "quantile_intervals"
CONF_QUANTILE_METHOD = "quantile_method"
DEFAULT_NAME = "Stats"
DEFAULT_SIZE = 20
DEFAULT_BUFFER_SIZE = 20
DEFAULT_PRECISION = 2
DEFAULT_QUANTILE_INTERVALS = 4
DEFAULT_QUANTILE_METHOD = "exclusive"
@ -63,9 +67,27 @@ PLATFORM_SCHEMA = PLATFORM_SCHEMA.extend(
{
vol.Required(CONF_ENTITY_ID): cv.entity_id,
vol.Optional(CONF_NAME, default=DEFAULT_NAME): cv.string,
vol.Optional(CONF_SAMPLING_SIZE, default=DEFAULT_SIZE): vol.All(
vol.Coerce(int), vol.Range(min=1)
vol.Optional(CONF_STATE_CHARACTERISTIC, default=STAT_MEAN): vol.In(
[
STAT_AVERAGE_CHANGE,
STAT_CHANGE,
STAT_CHANGE_RATE,
STAT_COUNT,
STAT_MAX_AGE,
STAT_MAX_VALUE,
STAT_MEAN,
STAT_MEDIAN,
STAT_MIN_AGE,
STAT_MIN_VALUE,
STAT_QUANTILES,
STAT_STANDARD_DEVIATION,
STAT_TOTAL,
STAT_VARIANCE,
]
),
vol.Optional(
CONF_SAMPLES_MAX_BUFFER_SIZE, default=DEFAULT_BUFFER_SIZE
): vol.All(vol.Coerce(int), vol.Range(min=1)),
vol.Optional(CONF_MAX_AGE): cv.time_period,
vol.Optional(CONF_PRECISION, default=DEFAULT_PRECISION): vol.Coerce(int),
vol.Optional(
@ -83,29 +105,21 @@ async def async_setup_platform(hass, config, async_add_entities, discovery_info=
await async_setup_reload_service(hass, DOMAIN, PLATFORMS)
entity_id = config.get(CONF_ENTITY_ID)
name = config.get(CONF_NAME)
sampling_size = config.get(CONF_SAMPLING_SIZE)
max_age = config.get(CONF_MAX_AGE)
precision = config.get(CONF_PRECISION)
quantile_intervals = config.get(CONF_QUANTILE_INTERVALS)
quantile_method = config.get(CONF_QUANTILE_METHOD)
async_add_entities(
[
StatisticsSensor(
entity_id,
name,
sampling_size,
max_age,
precision,
quantile_intervals,
quantile_method,
source_entity_id=config.get(CONF_ENTITY_ID),
name=config.get(CONF_NAME),
state_characteristic=config.get(CONF_STATE_CHARACTERISTIC),
samples_max_buffer_size=config.get(CONF_SAMPLES_MAX_BUFFER_SIZE),
samples_max_age=config.get(CONF_MAX_AGE),
precision=config.get(CONF_PRECISION),
quantile_intervals=config.get(CONF_QUANTILE_INTERVALS),
quantile_method=config.get(CONF_QUANTILE_METHOD),
)
],
True,
)
return True
@ -114,33 +128,45 @@ class StatisticsSensor(SensorEntity):
def __init__(
self,
entity_id,
source_entity_id,
name,
sampling_size,
max_age,
state_characteristic,
samples_max_buffer_size,
samples_max_age,
precision,
quantile_intervals,
quantile_method,
):
"""Initialize the Statistics sensor."""
self._entity_id = entity_id
self.is_binary = self._entity_id.split(".")[0] == "binary_sensor"
self._source_entity_id = source_entity_id
self.is_binary = self._source_entity_id.split(".")[0] == "binary_sensor"
self._name = name
self._available = False
self._sampling_size = sampling_size
self._max_age = max_age
self._state_characteristic = state_characteristic
self._samples_max_buffer_size = samples_max_buffer_size
self._samples_max_age = samples_max_age
self._precision = precision
self._quantile_intervals = quantile_intervals
self._quantile_method = quantile_method
self._unit_of_measurement = None
self.states = deque(maxlen=self._sampling_size)
self.ages = deque(maxlen=self._sampling_size)
self.count = 0
self.mean = self.median = self.quantiles = self.stdev = self.variance = None
self.total = self.min = self.max = None
self.min_age = self.max_age = None
self.change = self.average_change = self.change_rate = None
self.states = deque(maxlen=self._samples_max_buffer_size)
self.ages = deque(maxlen=self._samples_max_buffer_size)
self.attr = {
STAT_COUNT: 0,
STAT_TOTAL: None,
STAT_MEAN: None,
STAT_MEDIAN: None,
STAT_STANDARD_DEVIATION: None,
STAT_VARIANCE: None,
STAT_MIN_VALUE: None,
STAT_MAX_VALUE: None,
STAT_MIN_AGE: None,
STAT_MAX_AGE: None,
STAT_CHANGE: None,
STAT_AVERAGE_CHANGE: None,
STAT_CHANGE_RATE: None,
STAT_QUANTILES: None,
}
self._update_listener = None
async def async_added_to_hass(self):
@ -151,9 +177,7 @@ class StatisticsSensor(SensorEntity):
"""Handle the sensor state changes."""
if (new_state := event.data.get("new_state")) is None:
return
self._add_state_to_queue(new_state)
self.async_schedule_update_ha_state(True)
@callback
@ -163,17 +187,16 @@ class StatisticsSensor(SensorEntity):
self.async_on_remove(
async_track_state_change_event(
self.hass, [self._entity_id], async_stats_sensor_state_listener
self.hass,
[self._source_entity_id],
async_stats_sensor_state_listener,
)
)
if "recorder" in self.hass.config.components:
# Only use the database if it's configured
self.hass.async_create_task(self._initialize_from_database())
self.hass.bus.async_listen_once(
EVENT_HOMEASSISTANT_START, async_stats_sensor_startup
)
async_at_start(self.hass, async_stats_sensor_startup)
def _add_state_to_queue(self, new_state):
"""Add the state to the queue."""
@ -195,27 +218,75 @@ class StatisticsSensor(SensorEntity):
)
return
self._unit_of_measurement = new_state.attributes.get(ATTR_UNIT_OF_MEASUREMENT)
self._unit_of_measurement = self._derive_unit_of_measurement(new_state)
def _derive_unit_of_measurement(self, new_state):
base_unit = new_state.attributes.get(ATTR_UNIT_OF_MEASUREMENT)
if not base_unit:
unit = None
elif self.is_binary:
unit = None
elif self._state_characteristic in (
STAT_COUNT,
STAT_MIN_AGE,
STAT_MAX_AGE,
STAT_QUANTILES,
):
unit = None
elif self._state_characteristic in (
STAT_TOTAL,
STAT_MEAN,
STAT_MEDIAN,
STAT_STANDARD_DEVIATION,
STAT_MIN_VALUE,
STAT_MAX_VALUE,
STAT_CHANGE,
):
unit = base_unit
elif self._state_characteristic == STAT_VARIANCE:
unit = base_unit + "²"
elif self._state_characteristic == STAT_AVERAGE_CHANGE:
unit = base_unit + "/sample"
elif self._state_characteristic == STAT_CHANGE_RATE:
unit = base_unit + "/s"
return unit
@property
def name(self):
"""Return the name of the sensor."""
return self._name
@property
def state_class(self):
"""Return the state class of this entity."""
if self._state_characteristic in (
STAT_MIN_AGE,
STAT_MAX_AGE,
STAT_QUANTILES,
):
return None
return STATE_CLASS_MEASUREMENT
@property
def native_value(self):
"""Return the state of the sensor."""
if self.is_binary:
return self.count
return self.attr[STAT_COUNT]
if self._state_characteristic in (
STAT_MIN_AGE,
STAT_MAX_AGE,
STAT_QUANTILES,
):
return self.attr[self._state_characteristic]
if self._precision == 0:
with contextlib.suppress(TypeError, ValueError):
return int(self.mean)
return self.mean
return int(self.attr[self._state_characteristic])
return self.attr[self._state_characteristic]
@property
def native_unit_of_measurement(self):
"""Return the unit the value is expressed in."""
return self._unit_of_measurement if not self.is_binary else None
return self._unit_of_measurement
@property
def available(self):
@ -230,24 +301,9 @@ class StatisticsSensor(SensorEntity):
@property
def extra_state_attributes(self):
"""Return the state attributes of the sensor."""
if not self.is_binary:
return {
ATTR_SAMPLING_SIZE: self._sampling_size,
ATTR_COUNT: self.count,
ATTR_MEAN: self.mean,
ATTR_MEDIAN: self.median,
ATTR_QUANTILES: self.quantiles,
ATTR_STANDARD_DEVIATION: self.stdev,
ATTR_VARIANCE: self.variance,
ATTR_TOTAL: self.total,
ATTR_MIN_VALUE: self.min,
ATTR_MAX_VALUE: self.max,
ATTR_MIN_AGE: self.min_age,
ATTR_MAX_AGE: self.max_age,
ATTR_CHANGE: self.change,
ATTR_AVERAGE_CHANGE: self.average_change,
ATTR_CHANGE_RATE: self.change_rate,
}
if self.is_binary:
return None
return self.attr
@property
def icon(self):
@ -255,17 +311,17 @@ class StatisticsSensor(SensorEntity):
return ICON
def _purge_old(self):
"""Remove states which are older than self._max_age."""
"""Remove states which are older than self._samples_max_age."""
now = dt_util.utcnow()
_LOGGER.debug(
"%s: purging records older then %s(%s)",
self.entity_id,
dt_util.as_local(now - self._max_age),
self._max_age,
dt_util.as_local(now - self._samples_max_age),
self._samples_max_age,
)
while self.ages and (now - self.ages[0]) > self._max_age:
while self.ages and (now - self.ages[0]) > self._samples_max_age:
_LOGGER.debug(
"%s: purging record with datetime %s(%s)",
self.entity_id,
@ -277,73 +333,91 @@ class StatisticsSensor(SensorEntity):
def _next_to_purge_timestamp(self):
"""Find the timestamp when the next purge would occur."""
if self.ages and self._max_age:
if self.ages and self._samples_max_age:
# Take the oldest entry from the ages list and add the configured max_age.
# If executed after purging old states, the result is the next timestamp
# in the future when the oldest state will expire.
return self.ages[0] + self._max_age
return self.ages[0] + self._samples_max_age
return None
def _update_characteristics(self):
"""Calculate and update the various statistical characteristics."""
states_count = len(self.states)
self.attr[STAT_COUNT] = states_count
if self.is_binary:
return
if states_count >= 2:
self.attr[STAT_STANDARD_DEVIATION] = round(
statistics.stdev(self.states), self._precision
)
self.attr[STAT_VARIANCE] = round(
statistics.variance(self.states), self._precision
)
else:
self.attr[STAT_STANDARD_DEVIATION] = STATE_UNKNOWN
self.attr[STAT_VARIANCE] = STATE_UNKNOWN
if states_count > self._quantile_intervals:
self.attr[STAT_QUANTILES] = [
round(quantile, self._precision)
for quantile in statistics.quantiles(
self.states,
n=self._quantile_intervals,
method=self._quantile_method,
)
]
else:
self.attr[STAT_QUANTILES] = STATE_UNKNOWN
if states_count == 0:
self.attr[STAT_MEAN] = STATE_UNKNOWN
self.attr[STAT_MEDIAN] = STATE_UNKNOWN
self.attr[STAT_TOTAL] = STATE_UNKNOWN
self.attr[STAT_MIN_VALUE] = self.attr[STAT_MAX_VALUE] = STATE_UNKNOWN
self.attr[STAT_MIN_AGE] = self.attr[STAT_MAX_AGE] = STATE_UNKNOWN
self.attr[STAT_CHANGE] = self.attr[STAT_AVERAGE_CHANGE] = STATE_UNKNOWN
self.attr[STAT_CHANGE_RATE] = STATE_UNKNOWN
return
self.attr[STAT_MEAN] = round(statistics.mean(self.states), self._precision)
self.attr[STAT_MEDIAN] = round(statistics.median(self.states), self._precision)
self.attr[STAT_TOTAL] = round(sum(self.states), self._precision)
self.attr[STAT_MIN_VALUE] = round(min(self.states), self._precision)
self.attr[STAT_MAX_VALUE] = round(max(self.states), self._precision)
self.attr[STAT_MIN_AGE] = self.ages[0]
self.attr[STAT_MAX_AGE] = self.ages[-1]
self.attr[STAT_CHANGE] = self.states[-1] - self.states[0]
self.attr[STAT_AVERAGE_CHANGE] = self.attr[STAT_CHANGE]
self.attr[STAT_CHANGE_RATE] = 0
if states_count > 1:
self.attr[STAT_AVERAGE_CHANGE] /= len(self.states) - 1
time_diff = (
self.attr[STAT_MAX_AGE] - self.attr[STAT_MIN_AGE]
).total_seconds()
if time_diff > 0:
self.attr[STAT_CHANGE_RATE] = self.attr[STAT_CHANGE] / time_diff
self.attr[STAT_CHANGE] = round(self.attr[STAT_CHANGE], self._precision)
self.attr[STAT_AVERAGE_CHANGE] = round(
self.attr[STAT_AVERAGE_CHANGE], self._precision
)
self.attr[STAT_CHANGE_RATE] = round(
self.attr[STAT_CHANGE_RATE], self._precision
)
async def async_update(self):
"""Get the latest data and updates the states."""
_LOGGER.debug("%s: updating statistics", self.entity_id)
if self._max_age is not None:
if self._samples_max_age is not None:
self._purge_old()
self.count = len(self.states)
if not self.is_binary:
try: # require only one data point
self.mean = round(statistics.mean(self.states), self._precision)
self.median = round(statistics.median(self.states), self._precision)
except statistics.StatisticsError as err:
_LOGGER.debug("%s: %s", self.entity_id, err)
self.mean = self.median = STATE_UNKNOWN
try: # require at least two data points
self.stdev = round(statistics.stdev(self.states), self._precision)
self.variance = round(statistics.variance(self.states), self._precision)
if self._quantile_intervals < self.count:
self.quantiles = [
round(quantile, self._precision)
for quantile in statistics.quantiles(
self.states,
n=self._quantile_intervals,
method=self._quantile_method,
)
]
except statistics.StatisticsError as err:
_LOGGER.debug("%s: %s", self.entity_id, err)
self.stdev = self.variance = self.quantiles = STATE_UNKNOWN
if self.states:
self.total = round(sum(self.states), self._precision)
self.min = round(min(self.states), self._precision)
self.max = round(max(self.states), self._precision)
self.min_age = self.ages[0]
self.max_age = self.ages[-1]
self.change = self.states[-1] - self.states[0]
self.average_change = self.change
self.change_rate = 0
if len(self.states) > 1:
self.average_change /= len(self.states) - 1
time_diff = (self.max_age - self.min_age).total_seconds()
if time_diff > 0:
self.change_rate = self.change / time_diff
self.change = round(self.change, self._precision)
self.average_change = round(self.average_change, self._precision)
self.change_rate = round(self.change_rate, self._precision)
else:
self.total = self.min = self.max = STATE_UNKNOWN
self.min_age = self.max_age = dt_util.utcnow()
self.change = self.average_change = STATE_UNKNOWN
self.change_rate = STATE_UNKNOWN
self._update_characteristics()
# If max_age is set, ensure to update again after the defined interval.
next_to_purge_timestamp = self._next_to_purge_timestamp()
@ -381,11 +455,11 @@ class StatisticsSensor(SensorEntity):
with session_scope(hass=self.hass) as session:
query = session.query(States).filter(
States.entity_id == self._entity_id.lower()
States.entity_id == self._source_entity_id.lower()
)
if self._max_age is not None:
records_older_then = dt_util.utcnow() - self._max_age
if self._samples_max_age is not None:
records_older_then = dt_util.utcnow() - self._samples_max_age
_LOGGER.debug(
"%s: retrieve records not older then %s",
self.entity_id,
@ -396,7 +470,7 @@ class StatisticsSensor(SensorEntity):
_LOGGER.debug("%s: retrieving all records", self.entity_id)
query = query.order_by(States.last_updated.desc()).limit(
self._sampling_size
self._samples_max_buffer_size
)
states = execute(query, to_native=True, validate_entity_ids=False)

191
tests/components/statistics/test_sensor.py
View File

@ -8,6 +8,7 @@ import pytest
from homeassistant import config as hass_config
from homeassistant.components import recorder
from homeassistant.components.sensor import ATTR_STATE_CLASS, STATE_CLASS_MEASUREMENT
from homeassistant.components.statistics.sensor import DOMAIN, StatisticsSensor
from homeassistant.const import (
ATTR_UNIT_OF_MEASUREMENT,
@ -64,11 +65,18 @@ class TestStatisticsSensor(unittest.TestCase):
self.hass,
"sensor",
{
"sensor": {
"platform": "statistics",
"name": "test",
"entity_id": "binary_sensor.test_monitored",
}
"sensor": [
{
"platform": "statistics",
"name": "test",
"entity_id": "binary_sensor.test_monitored",
},
{
"platform": "statistics",
"name": "test_unitless",
"entity_id": "binary_sensor.test_monitored_unitless",
},
]
},
)
@ -77,12 +85,21 @@ class TestStatisticsSensor(unittest.TestCase):
self.hass.block_till_done()
for value in values:
self.hass.states.set("binary_sensor.test_monitored", value)
self.hass.states.set(
"binary_sensor.test_monitored",
value,
{ATTR_UNIT_OF_MEASUREMENT: TEMP_CELSIUS},
)
self.hass.states.set("binary_sensor.test_monitored_unitless", value)
self.hass.block_till_done()
state = self.hass.states.get("sensor.test")
assert state.state == str(len(values))
assert state.attributes.get(ATTR_UNIT_OF_MEASUREMENT) is None
assert state.attributes.get(ATTR_STATE_CLASS) == STATE_CLASS_MEASUREMENT
assert str(len(values)) == state.state
state = self.hass.states.get("sensor.test_unitless")
assert state.attributes.get(ATTR_UNIT_OF_MEASUREMENT) is None
def test_sensor_source(self):
"""Test if source is a sensor."""
@ -121,17 +138,18 @@ class TestStatisticsSensor(unittest.TestCase):
assert self.mean == state.attributes.get("mean")
assert self.count == state.attributes.get("count")
assert self.total == state.attributes.get("total")
assert state.attributes.get(ATTR_UNIT_OF_MEASUREMENT) == TEMP_CELSIUS
assert self.change == state.attributes.get("change")
assert self.average_change == state.attributes.get("average_change")
assert state.attributes.get(ATTR_UNIT_OF_MEASUREMENT) == TEMP_CELSIUS
assert state.attributes.get(ATTR_STATE_CLASS) == STATE_CLASS_MEASUREMENT
# Source sensor turns unavailable, then available with valid value,
# statistics sensor should follow
state = self.hass.states.get("sensor.test")
self.hass.states.set(
"sensor.test_monitored",
STATE_UNAVAILABLE,
{ATTR_UNIT_OF_MEASUREMENT: TEMP_CELSIUS},
)
self.hass.block_till_done()
new_state = self.hass.states.get("sensor.test")
@ -445,6 +463,161 @@ class TestStatisticsSensor(unittest.TestCase):
state = self.hass.states.get("sensor.test")
assert state.state == str(round(sum(self.values) / len(self.values), 1))
def test_state_characteristic_unit(self):
"""Test statistics characteristic selection (via config)."""
assert setup_component(
self.hass,
"sensor",
{
"sensor": [
{
"platform": "statistics",
"name": "test_min_age",
"entity_id": "sensor.test_monitored",
"state_characteristic": "min_age",
},
{
"platform": "statistics",
"name": "test_variance",
"entity_id": "sensor.test_monitored",
"state_characteristic": "variance",
},
{
"platform": "statistics",
"name": "test_average_change",
"entity_id": "sensor.test_monitored",
"state_characteristic": "average_change",
},
{
"platform": "statistics",
"name": "test_change_rate",
"entity_id": "sensor.test_monitored",
"state_characteristic": "change_rate",
},
]
},
)
self.hass.block_till_done()
self.hass.start()
self.hass.block_till_done()
for value in self.values:
self.hass.states.set(
"sensor.test_monitored",
value,
{ATTR_UNIT_OF_MEASUREMENT: TEMP_CELSIUS},
)
self.hass.states.set(
"sensor.test_monitored_unitless",
value,
)
self.hass.block_till_done()
state = self.hass.states.get("sensor.test_min_age")
assert state.state == str(state.attributes.get("min_age"))
assert state.attributes.get(ATTR_UNIT_OF_MEASUREMENT) is None
state = self.hass.states.get("sensor.test_variance")
assert state.state == str(state.attributes.get("variance"))
assert state.attributes.get(ATTR_UNIT_OF_MEASUREMENT) == TEMP_CELSIUS + "²"
state = self.hass.states.get("sensor.test_average_change")
assert state.state == str(state.attributes.get("average_change"))
assert (
state.attributes.get(ATTR_UNIT_OF_MEASUREMENT) == TEMP_CELSIUS + "/sample"
)
state = self.hass.states.get("sensor.test_change_rate")
assert state.state == str(state.attributes.get("change_rate"))
assert state.attributes.get(ATTR_UNIT_OF_MEASUREMENT) == TEMP_CELSIUS + "/s"
def test_state_class(self):
"""Test state class, which depends on the characteristic configured."""
assert setup_component(
self.hass,
"sensor",
{
"sensor": [
{
"platform": "statistics",
"name": "test_normal",
"entity_id": "sensor.test_monitored",
"state_characteristic": "count",
},
{
"platform": "statistics",
"name": "test_nan",
"entity_id": "sensor.test_monitored",
"state_characteristic": "min_age",
},
]
},
)
self.hass.block_till_done()
self.hass.start()
self.hass.block_till_done()
for value in self.values:
self.hass.states.set(
"sensor.test_monitored",
value,
{ATTR_UNIT_OF_MEASUREMENT: TEMP_CELSIUS},
)
self.hass.block_till_done()
state = self.hass.states.get("sensor.test_normal")
assert state.attributes.get(ATTR_STATE_CLASS) == STATE_CLASS_MEASUREMENT
state = self.hass.states.get("sensor.test_nan")
assert state.attributes.get(ATTR_STATE_CLASS) is None
def test_unitless_source_sensor(self):
"""Statistics for a unitless source sensor should never have a unit."""
assert setup_component(
self.hass,
"sensor",
{
"sensor": [
{
"platform": "statistics",
"name": "test_unitless_1",
"entity_id": "sensor.test_monitored_unitless",
"state_characteristic": "count",
},
{
"platform": "statistics",
"name": "test_unitless_2",
"entity_id": "sensor.test_monitored_unitless",
"state_characteristic": "mean",
},
{
"platform": "statistics",
"name": "test_unitless_3",
"entity_id": "sensor.test_monitored_unitless",
"state_characteristic": "change_rate",
},
]
},
)
self.hass.block_till_done()
self.hass.start()
self.hass.block_till_done()
for value in self.values:
self.hass.states.set(
"sensor.test_monitored_unitless",
value,
)
self.hass.block_till_done()
state = self.hass.states.get("sensor.test_unitless_1")
assert state.attributes.get(ATTR_UNIT_OF_MEASUREMENT) is None
state = self.hass.states.get("sensor.test_unitless_2")
assert state.attributes.get(ATTR_UNIT_OF_MEASUREMENT) is None
state = self.hass.states.get("sensor.test_unitless_3")
assert state.attributes.get(ATTR_UNIT_OF_MEASUREMENT) is None
assert state.attributes.get(ATTR_STATE_CLASS) == STATE_CLASS_MEASUREMENT
def test_initialize_from_database(self):
"""Test initializing the statistics from the database."""
# enable the recorder