washer: add 0A/B0 cycle labels; purifier: PM device classes
Table_02 codes 0A (Towels) and B0 (Mixed load) were reported for a WW90DG5G34ABLE (issue #363). Air-purifier Dust/FineDust/SuperFineDust map to PM10/PM2.5/PM1 in µg/m³ from a same-moment SmartThings correlation (issue #325).
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JayChickenK
@@ -15,13 +15,12 @@ A second `value` list element on the particulate-matter types (e.g. Dust's
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board confirms what its scale means -- left unbound rather than guessed;
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index 0 is the only slot any family has ever read.
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Dust/FineDust/SuperFineDust aren't assigned an HA `device_class`
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(pm10/pm25/pm1) or `unit` despite reading like plausible ug/m3 particulate
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values: Samsung's own two-tier Korean convention maps only to a PM10/PM2.5
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pair, and this board's three-tier naming doesn't confirm where the extra
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tier or a PM1 reading fits. A wrong guess would silently mislabel every
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reading forever, so they're plain `measurement` sensors named after the
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device's own field instead, matching air_purifier.AIR_QUALITY's precedent.
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Dust/FineDust/SuperFineDust stay without an HA `device_class`/`unit` on
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this board. The three-tier mapping (Dust=PM10, FineDust=PM2.5,
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SuperFineDust=PM1, µg/m³) is confirmed for the air-purifier family
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(issue #325) but this standalone monitor has no same-moment app
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correlation of its own, so it keeps the untyped measurement sensors
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rather than inheriting that label.
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"""
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from datetime import time as dt_time
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@@ -31,12 +30,13 @@ from ..entities import BinarySensorDesc, SensorDesc, SwitchDesc, TimeDesc
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from .air_purifier import _AIR_QUALITY_SENSORS
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from .common import int_or_none, sensor_item_value
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# _AIR_QUALITY_SENSORS' fourth column (state_class) is deliberately discarded
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# Extra columns (state_class, device_class, unit) are deliberately discarded
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# here: air_purifier leaves Odor/CleanLevel unstamped because they read as
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# graded indices on that family, while this board has stamped all five as
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# `measurement` since it was added (issue #210). Consuming the column would
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# silently drop long-term statistics for two sensors on shipped devices, so
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# the shared rows supply only the key/icon/type here.
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# `measurement` since it was added (issue #210). Consuming state_class would
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# silently drop long-term statistics for two sensors on shipped devices, and
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# the pm10/pm25/pm1 labels are confirmed only for the purifier family
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# (issue #325). The shared rows supply only the key/icon/type here.
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SENSORS = Capability(
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href="/sensors/vs/0",
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poll_tier="warm",
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@@ -49,7 +49,7 @@ SENSORS = Capability(
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state_class="measurement",
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value_fn=lambda items, t=sensor_type: sensor_item_value(items, t),
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)
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for key, icon, sensor_type, _ in _AIR_QUALITY_SENSORS
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for key, icon, sensor_type, *_ in _AIR_QUALITY_SENSORS
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),
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SensorDesc(
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key="co2",
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@@ -51,13 +51,13 @@ def _has_top_level_modes(rep, resources):
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return isinstance(rep.get("x.com.samsung.da.supportedModes"), (list, tuple))
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# The fourth column is state_class, which is what makes Home Assistant keep
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# long-term statistics for a sensor -- without one, a reading is only in the
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# short-term recorder history and disappears with the next purge (10 days by
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# default), so it can't back a long-range air-quality graph. The values are
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# already numeric (sensor_item_value returns int), so nothing else was in the
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# way; three sensors in this same module (filter_progress, fan_speed_level,
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# hepa_filter_usage) already declare one.
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# Columns: key, icon, device item type, state_class, device_class, unit.
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# state_class is what makes Home Assistant keep long-term statistics --
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# without one, a reading is only in the short-term recorder history and
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# disappears with the next purge (10 days by default), so it can't back a
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# long-range air-quality graph. The values are already numeric
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# (sensor_item_value returns int); three sensors in this same module
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# (filter_progress, fan_speed_level, hepa_filter_usage) already declare one.
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#
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# Only the three particulate readings get it. They fall monotonically with
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# particle size on three independent board families -- 11/9/5 on ARTIK051_TVTL
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@@ -67,15 +67,16 @@ def _has_top_level_modes(rep, resources):
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# indices instead, where the mean of a grade isn't obviously meaningful; left
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# without a state_class rather than guessing.
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#
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# Deliberately no device_class/unit here: pm1/pm25/pm10 would assert the
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# reading is a µg/m³ concentration, and the dumps never say so. That's a
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# separate call from making the series recordable at all.
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# device_class/unit confirmed on a live ARTIK051_TVTL against the SmartThings
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# app at the same moment (issue #325): Dust=PM10, FineDust=PM2.5,
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# SuperFineDust=PM1, all µg/m³. Dust matched PM10 exactly; the other two
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# were 1 µg/m³ off the app, same order.
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_AIR_QUALITY_SENSORS = (
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("dust", "mdi:blur", "Dust", "measurement"),
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("fine_dust", "mdi:blur", "FineDust", "measurement"),
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("super_fine_dust", "mdi:blur", "SuperFineDust", "measurement"),
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("odor", "mdi:scent", "Odor", None),
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("clean_level", "mdi:air-filter", "CleanLevel", None),
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("dust", "mdi:blur", "Dust", "measurement", "pm10", "µg/m³"),
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("fine_dust", "mdi:blur", "FineDust", "measurement", "pm25", "µg/m³"),
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("super_fine_dust", "mdi:blur", "SuperFineDust", "measurement", "pm1", "µg/m³"),
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("odor", "mdi:scent", "Odor", None, None, None),
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("clean_level", "mdi:air-filter", "CleanLevel", None, None, None),
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)
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AIR_QUALITY = Capability(
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@@ -87,9 +88,11 @@ AIR_QUALITY = Capability(
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field="x.com.samsung.da.items",
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icon=icon,
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state_class=state_class,
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device_class=device_class,
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unit=unit,
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value_fn=lambda items, t=sensor_type: sensor_item_value(items, t),
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)
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for key, icon, sensor_type, state_class in _AIR_QUALITY_SENSORS
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for key, icon, sensor_type, state_class, device_class, unit in _AIR_QUALITY_SENSORS
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),
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)
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@@ -39,9 +39,11 @@ from .laundry import (
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# editCourseList and screenshots (issue #22, a combo's own course set, not
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# implying anything about a plain washer's '1F'); 3 more (Eco Cold, Towels,
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# Self Clean+) verified directly on a WF50A8600AV/US by reading back the raw
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# code after selecting each cycle on the appliance (issue #80). Two code
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# pairs ('21'/'65' Colors, '27'/'5E' Rinse+Spin, and '24'/'54' Towels)
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# legitimately share a label across different course tables -- not typos.
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# code after selecting each cycle on the appliance (issue #80). 2 more
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# ('0A' Towels, 'B0' Mixed load) reported for a WW90DG5G34ABLE on the same
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# Table_02 family (issue #363). Two code pairs ('21'/'65' Colors,
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# '27'/'5E' Rinse+Spin, and '24'/'54' Towels) legitimately share a label
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# across different course tables -- not typos.
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#
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# No static fallback list is kept here: other models have different actual
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# course sets, so hardcoding one device's list would show/hide the wrong
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@@ -646,6 +646,7 @@
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"04": "Rychlé praní",
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"06": "XXL prádlo",
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"08": "Máchání+odstřeďování",
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"0a": "Ručníky",
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"17": "Stažený program",
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"1b": "Bavlna",
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"1c": "Eco 40-60",
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@@ -712,6 +713,7 @@
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"8f": "Intenzivní studená",
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"96": "Méně mikrovláken",
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"a0": "15min rychlé praní",
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"b0": "Smíšená náplň",
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"35": "Eko bavlna"
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}
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},
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@@ -609,6 +609,7 @@
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"04": "Schnellwäsche",
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"06": "XXL-Wäsche",
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"08": "Spülen + Schleudern",
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"0a": "Handtücher",
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"1b": "Baumwolle",
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"1c": "Eco 40-60",
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"1d": "Super Speed",
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@@ -656,6 +657,7 @@
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"8f": "Kaltwäsche Intensiv",
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"96": "Weniger Mikrofasern",
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"a0": "Schnelle Wäsche 15'",
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"b0": "Mischwäsche",
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"17": "Heruntergeladen",
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"69": "KI-Wäsche",
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"6a": "Wolle",
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@@ -646,6 +646,7 @@
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"04": "Quick Wash",
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"06": "XXL Laundry",
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"08": "Rinse+Spin",
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"0a": "Towels",
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"17": "Downloaded",
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"1b": "Cotton",
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"1c": "Eco 40-60",
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@@ -712,7 +713,8 @@
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"88": "Pet Care",
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"8f": "Intense Cold",
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"96": "Less Microfiber",
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"a0": "15' Quick Wash"
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"a0": "15' Quick Wash",
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"b0": "Mixed load"
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}
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},
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"washer_dry_level": {
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@@ -842,6 +842,7 @@
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"04": "Lavado rápido",
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"06": "Colada XXL",
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"08": "Aclarar + Centrifugar",
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"0a": "Toallas",
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"17": "Descargado",
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"1b": "Algodón",
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"1c": "Eco 40-60",
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@@ -890,6 +891,7 @@
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"8f": "Lavado en frío",
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"96": "Menos microfibras",
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"a0": "Lavado rápido 15'",
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"b0": "Carga mixta",
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"69": "Lavado IA",
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"6a": "Lana",
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"6b": "Denim",
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@@ -646,6 +646,7 @@
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"04": "Lavaggio rapido",
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"06": "Bucato XXL",
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"08": "Risciacquo+Centrifuga",
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"0a": "Asciugamani",
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"17": "Scaricato",
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"1b": "Cotone",
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"1c": "Eco 40-60",
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@@ -712,7 +713,8 @@
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"79": "Solo centrifuga",
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"88": "Cura animali",
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"35": "Cotone E",
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"a0": "Rapido 15'"
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"a0": "Rapido 15'",
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"b0": "Carico misto"
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}
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},
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"washer_dry_level": {
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@@ -646,6 +646,7 @@
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"04": "쾌속세탁",
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"06": "XXL 세탁",
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"08": "헹굼+탈수",
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"0a": "타월",
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"17": "다운로드 코스",
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"1b": "면",
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"1c": "에코 40-60",
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@@ -694,6 +695,7 @@
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"8f": "강력 냉수 세탁",
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"96": "미세플라스틱저감",
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"a0": "15분 쾌속세탁",
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"b0": "혼합",
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"69": "AI 맞춤세탁",
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"6a": "울",
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"6b": "데님",
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@@ -646,6 +646,7 @@
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"04": "Snelle was",
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"06": "XXL was",
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"08": "Spoelen+centrifugeren",
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"0a": "Handdoeken",
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"17": "Gedownload",
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"1b": "Katoen",
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"1c": "Eco 40-60",
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@@ -712,6 +713,7 @@
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"8f": "Intensief koud",
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"96": "Minder microvezels",
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"a0": "15' Snelle was",
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"b0": "Gemengde was",
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"35": "Eco katoen"
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}
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},
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@@ -30,30 +30,39 @@ def test_graded_sensors_are_left_without_a_state_class():
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assert _desc(key).state_class is None, key
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def test_no_unit_or_device_class_is_asserted():
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"""state_class alone makes the series recordable. pm1/pm25/pm10 with
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µg/m³ would additionally assert the reading is a mass concentration,
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which no dump states."""
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for key in PARTICULATE + GRADED:
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def test_particulate_sensors_declare_pm_device_class_and_unit():
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"""Live same-moment SmartThings correlation on ARTIK051_TVTL (issue #325)
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maps Dust/FineDust/SuperFineDust to PM10/PM2.5/PM1 in µg/m³."""
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expected = {
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"dust": ("pm10", "µg/m³"),
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"fine_dust": ("pm25", "µg/m³"),
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"super_fine_dust": ("pm1", "µg/m³"),
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}
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for key, (device_class, unit) in expected.items():
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desc = _desc(key)
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assert desc.device_class == device_class, key
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assert desc.unit == unit, key
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for key in GRADED:
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desc = _desc(key)
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assert desc.unit is None, key
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assert desc.device_class is None, key
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assert desc.unit is None, key
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def test_state_class_comes_from_the_shared_tuples_fourth_column():
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"""The rows carry their own state_class rather than a parallel lookup, so
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a new sensor can't be added here without deciding the question."""
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for row in air_purifier._AIR_QUALITY_SENSORS:
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assert len(row) == 4, row
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assert len(row) == 6, row
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assert row[3] in ("measurement", None), row
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assert row[4] in ("pm10", "pm25", "pm1", None), row
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def test_air_monitor_keeps_stamping_every_shared_sensor():
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"""air_monitor imports _AIR_QUALITY_SENSORS and discards the fourth column
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"""air_monitor imports _AIR_QUALITY_SENSORS and discards the extra columns
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on purpose: that board (issue #210) has stamped all five as `measurement`
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since it was added, and consuming the column would silently drop long-term
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statistics for Odor/CleanLevel there. Guards the import end to end and the
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deliberate divergence together."""
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since it was added, and consuming state_class would silently drop
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long-term statistics for Odor/CleanLevel there. Guards the import end to
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end and the deliberate divergence together."""
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from custom_components.localthings.registry.capabilities import air_monitor
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assert air_monitor.SENSORS.href == "/sensors/vs/0"
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@@ -62,6 +71,8 @@ def test_air_monitor_keeps_stamping_every_shared_sensor():
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d for d in air_monitor.SENSORS.entities if d.key == key and isinstance(d, SensorDesc)
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)
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assert desc.state_class == "measurement", key
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assert desc.device_class is None, key
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assert desc.unit is None, key
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def test_every_air_quality_sensor_still_reads_a_plain_int():
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Reference in New Issue
Block a user