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# AppDaemon apps configuration
# Add the availability app alongside existing apps (e.g., hello_world)
hello_world:
module: hello
class: HelloWorld
availability:
module: availability
class: Availability
log_level: info

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"""AppDaemon app: Device availability calculator for Home Assistant.
Calculates uptime metrics for tracked devices and creates sensor.avail_* entities.
"""
import appdaemon.plugins.hass.hassapi as hass
import requests
from datetime import datetime, timezone, timedelta
from availability_utils import (
is_excluded, sanitize_entity_id, sanitize_area_name,
get_color, calc_trend, format_downtime,
parse_datetime, period_timedelta, chunk_list,
compute_availability, compute_sparkline,
TRACKED_DOMAINS,
)
BATCH_SIZE = 20
BATCH_DELAY = 1 # seconds between batch requests
HA_URL = "http://supervisor/core/api"
class Availability(hass.Hass):
def initialize(self):
self._token = None
self._entities_cache = []
self._areas_cache = {}
self._current_period = "7d"
self._results_cache = {"24h": {}, "7d": {}, "30d": {}}
# Cold-start: full recalc after 30s
self.run_in(self._cold_start, 30)
# Periodic schedules
self.run_every(self._calc_24h, "now+60", 5 * 60)
self.run_every(self._calc_7d, "now+90", 15 * 60)
self.run_every(self._calc_30d, "now+120", 2 * 3600)
# Listen for period selector change
self.listen_state(self._period_changed, "input_select.avail_period")
self.log("Availability app initialized")
def _get_token(self):
if self._token is None:
import os
self._token = os.environ.get("SUPERVISOR_TOKEN", "")
if not self._token:
self._token = self.args.get("token", "")
return self._token
def _api_headers(self):
return {
"Authorization": f"Bearer {self._get_token()}",
"Content-Type": "application/json",
}
def _api_get(self, path):
url = f"{HA_URL}{path}"
try:
resp = requests.get(url, headers=self._api_headers(), timeout=30)
resp.raise_for_status()
return resp.json()
except Exception as e:
self.log(f"API error {path}: {e}", level="WARNING")
return None
# ── Entity Discovery ──
def _fetch_entities(self):
"""Get all entities from HA and filter by domain + exclusions."""
data = self._api_get("/states")
if not data:
self.log("Failed to fetch entities", level="ERROR")
return []
entities = []
for e in data:
eid = e.get("entity_id", "")
domain = eid.split(".")[0] if "." in eid else ""
if domain not in TRACKED_DOMAINS:
continue
if is_excluded(eid):
continue
entities.append({
"entity_id": eid,
"friendly_name": e.get("attributes", {}).get("friendly_name", eid),
"domain": domain,
})
self._entities_cache = entities
self.log(f"Found {len(entities)} tracked entities")
return entities
def _fetch_areas(self):
"""Fetch area registry and build entity_id -> area mapping."""
data = self._api_get("/config/area_registry")
if not data:
self._areas_cache = {}
return {}
# Build device_id -> area map
device_areas = {}
for area in data:
area_id = area.get("area_id")
area_name = area.get("name", "Без комнаты")
device_areas[area_id] = area_name
# Now get entity registry to map entity -> device -> area
reg = self._api_get("/config/entity_registry")
if not reg:
self._areas_cache = {}
return {}
eid_to_area = {}
for entry in reg:
eid = entry.get("entity_id", "")
device_id = entry.get("device_id")
area_id = entry.get("area_id")
# Use entity-level area if set, otherwise device-level
if area_id and area_id in device_areas:
eid_to_area[eid] = device_areas[area_id]
elif device_id:
# Try to find device's area via device registry
dev_data = self._api_get(f"/config/device_registry")
# This is expensive; fallback to simple mapping
pass
else:
eid_to_area[eid] = "Без комнаты"
# Fill from device registry if available
dev_reg = self._api_get("/config/device_registry")
if dev_reg:
dev_area_map = {}
for dev in dev_reg:
dev_id = dev.get("id")
a_id = dev.get("area_id")
if dev_id and a_id and a_id in device_areas:
dev_area_map[dev_id] = device_areas[a_id]
for entry in reg:
eid = entry.get("entity_id", "")
device_id = entry.get("device_id")
area_id = entry.get("area_id")
if area_id and area_id in device_areas:
eid_to_area[eid] = device_areas[area_id]
elif device_id and device_id in dev_area_map:
eid_to_area[eid] = dev_area_map[device_id]
else:
eid_to_area[eid] = eid_to_area.get(eid, "Без комнаты")
self._areas_cache = eid_to_area
return eid_to_area
# ── History Fetch ──
def _fetch_history(self, entity_ids: list, period_start: datetime, period_end: datetime):
"""Fetch history from HA API in batches."""
start_str = period_start.isoformat()
all_history = {}
chunks = chunk_list(entity_ids, BATCH_SIZE)
total_chunks = len(chunks)
for i, chunk in enumerate(chunks):
ids_str = ",".join(chunk)
path = f"/history/period/{start_str}?filter_entity_id={ids_str}&minimal_response&no_attributes"
data = self._api_get(path)
if data and isinstance(data, list):
for entity_history in data:
if entity_history and isinstance(entity_history, list) and len(entity_history) > 0:
eid = entity_history[0].get("entity_id", chunk[0] if chunk else "")
all_history[eid] = entity_history
# Update progress
progress = f"{i + 1}/{total_chunks}"
self._set_progress(progress)
if i < total_chunks - 1:
self.sleep(BATCH_DELAY)
self._set_progress("idle")
return all_history
# ── Calculation ──
def _calc_period(self, period: str):
"""Calculate availability for all devices in given period."""
self.log(f"Calculating availability for period {period}")
now = datetime.now(timezone.utc)
td = period_timedelta(period)
period_start = now - td
period_end = now
# Previous period for trend
prev_start = period_start - td
prev_end = period_start
entities = self._fetch_entities()
if not entities:
return
areas = self._fetch_areas()
entity_ids = [e["entity_id"] for e in entities]
# Fetch history for current period
history = self._fetch_history(entity_ids, period_start, period_end)
# Fetch history for previous period (for trend)
prev_history = self._fetch_history(entity_ids, prev_start, prev_end)
results = {}
area_results = {}
for ent in entities:
eid = ent["entity_id"]
fname = ent["friendly_name"]
domain = ent["domain"]
area = areas.get(eid, "Без комнаты")
entries = history.get(eid, [])
metrics = compute_availability(entries, period_start, period_end)
# Sparkline
spark_days = 7 if period in ("7d", "30d") else 1
sparkline = compute_sparkline(entries, period_end, days=spark_days)
# Trend
prev_entries = prev_history.get(eid, [])
prev_metrics = compute_availability(prev_entries, prev_start, prev_end)
trend = calc_trend(metrics["availability_pct"], prev_metrics["availability_pct"])
color = get_color(metrics["availability_pct"])
result = {
"entity_id": eid,
"friendly_name": fname,
"domain": domain,
"area": area,
"period": period,
"availability_pct": metrics["availability_pct"],
"down_count": metrics["down_count"],
"max_downtime_minutes": metrics["max_downtime_minutes"],
"sparkline": sparkline,
"trend": trend,
"last_downtime": metrics["last_downtime"],
"color": color,
"last_updated": now.isoformat(),
}
results[eid] = result
# Area aggregation
if area not in area_results:
area_results[area] = {"pcts": [], "devices": 0, "problems": 0}
area_results[area]["pcts"].append(metrics["availability_pct"])
area_results[area]["devices"] += 1
if metrics["availability_pct"] < 95:
area_results[area]["problems"] += 1
self._results_cache[period] = results
# Write device sensors
for eid, res in results.items():
safe = sanitize_entity_id(eid)
sensor_id = f"sensor.avail_{safe}"
attrs = {k: v for k, v in res.items() if k != "state"}
self.set_state(sensor_id, state=str(res["availability_pct"]), attributes=attrs)
# Write area sensors
for area_name, adata in area_results.items():
avg = round(sum(adata["pcts"]) / len(adata["pcts"]), 1) if adata["pcts"] else 100.0
safe_area = sanitize_area_name(area_name)
sensor_id = f"sensor.avail_area_{safe_area}"
attrs = {
"area": area_name,
"period": period,
"availability_pct": avg,
"device_count": adata["devices"],
"problem_count": adata["problems"],
"color": get_color(avg),
"last_updated": now.isoformat(),
}
self.set_state(sensor_id, state=str(avg), attributes=attrs)
self.log(f"Calculated {len(results)} device sensors, {len(area_results)} area sensors for {period}")
# ── Callbacks ──
def _cold_start(self, kwargs):
"""Initial calculation on startup."""
self.log("Cold start: calculating current period")
try:
period = self.get_state("input_select.avail_period") or "7d"
except Exception:
period = "7d"
self._current_period = period
self._calc_period(period)
def _calc_24h(self, kwargs):
self._calc_period("24h")
def _calc_7d(self, kwargs):
self._calc_period("7d")
def _calc_30d(self, kwargs):
self._calc_period("30d")
def _period_changed(self, entity, attribute, old, new, kwargs):
"""Handle period selector change."""
if new and new != old:
self._current_period = new
self.log(f"Period changed to {new}, recalculating")
self._calc_period(new)
# ── Progress ──
def _set_progress(self, value: str):
"""Update calculation progress sensor."""
self.set_state("sensor.avail_calc_progress", state=value, attributes={
"friendly_name": "Расчёт доступности",
"last_updated": datetime.now(timezone.utc).isoformat(),
})

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"""Utility functions for availability calculator."""
import re
from datetime import datetime, timezone, timedelta
# Domains to track (phase 1)
TRACKED_DOMAINS = {"light", "switch"}
# Entity suffixes to exclude (Zigbee2MQTT helpers, etc.)
EXCLUDE_SUFFIXES = (
"_battery_low", "_battery", "_linkquality", "_update",
"_update_state", "_identify",
)
# Additional exclusions for switch domain (relay settings, not real devices)
SWITCH_EXCLUDE_SUFFIXES = (
"_delayed_power_on_state", "_detach_relay_mode",
"_network_indicator", "_turbo_mode", "_do_not_disturb",
)
SWITCH_EXCLUDE_EXACT = {"switch.zigbee2mqtt_bridge_permit_join"}
# Auto-generated Zigbee select/number patterns
ZIGBEE_AUTO_PATTERN = re.compile(
r"(select|number)\.(zigbee2mqtt_|.*_(radar_sensitivity|sensitivity|mode|level|delay|threshold|interval|timeout))",
re.IGNORECASE,
)
# Update/button domain patterns
UPDATE_BUTTON_EXCLUDE = re.compile(r"^(update|button)\.", re.IGNORECASE)
def is_excluded(entity_id: str) -> bool:
"""Check if entity should be excluded from tracking."""
domain = entity_id.split(".")[0]
name = entity_id.split(".")[1] if "." in entity_id else ""
# Exact exclusions
if entity_id in SWITCH_EXCLUDE_EXACT:
return True
# Suffix exclusions
for suffix in EXCLUDE_SUFFIXES:
if name.endswith(suffix):
return True
# Switch-specific suffix exclusions
if domain == "switch":
for suffix in SWITCH_EXCLUDE_SUFFIXES:
if name.endswith(suffix):
return True
return False
def sanitize_entity_id(entity_id: str) -> str:
"""Convert entity_id to safe sensor name: light.bra_v_spalne → light_bra_v_spalne."""
return entity_id.replace(".", "_")
def sanitize_area_name(name: str) -> str:
"""Convert area name to safe sensor suffix."""
s = name.lower().strip()
s = re.sub(r"[^a-zа-яё0-9_]", "_", s)
s = re.sub(r"_+", "_", s)
return s.strip("_")
def domain_icon(domain: str) -> str:
"""Return icon for domain."""
return {
"light": "💡",
"switch": "🔌",
"binary_sensor": "👁️",
"sensor": "🌡️",
"climate": "❄️",
"cover": "🚪",
"lock": "🔒",
"media_player": "🔊",
"device_tracker": "📍",
"vacuum": "🤖",
"fan": "🌀",
"humidifier": "💨",
"water_heater": "🚿",
"siren": "🚨",
"button": "🔘",
}.get(domain, "📡")
def get_color(pct: float) -> str:
"""Return color bucket for availability percentage."""
if pct >= 99:
return "green"
elif pct >= 95:
return "yellow"
elif pct >= 90:
return "orange"
return "red"
def calc_trend(current_pct: float, previous_pct: float, threshold: float = 0.5) -> str:
"""Compare current vs previous period. Returns up/down/stable."""
diff = current_pct - previous_pct
if diff > threshold:
return "up"
elif diff < -threshold:
return "down"
return "stable"
def format_downtime(minutes: int) -> str:
"""Format downtime minutes to human-readable string."""
if minutes < 60:
return f"{minutes} мин"
h, m = divmod(minutes, 60)
if h < 24:
return f"{h}ч {m}мин"
d, h = divmod(h, 24)
return f"{d}д {h}ч {m}мин"
def parse_datetime(dt_str: str) -> datetime:
"""Parse HA datetime string to timezone-aware datetime."""
# HA format: 2026-04-14T15:32:00+03:00 or 2026-04-14T15:32:00.123456+03:00
dt_str = dt_str.rstrip("Z")
if "+" in dt_str[10:] or dt_str.endswith("Z"):
# Has timezone
if "+" in dt_str:
# Python fromisoformat handles this in 3.7+
return datetime.fromisoformat(dt_str)
return datetime.fromisoformat(dt_str.replace("Z", "+00:00"))
# No timezone — assume UTC
dt = datetime.fromisoformat(dt_str)
return dt.replace(tzinfo=timezone.utc)
def period_timedelta(period: str) -> timedelta:
"""Convert period string to timedelta."""
return {"24h": timedelta(hours=24), "7d": timedelta(days=7), "30d": timedelta(days=30)}[period]
def chunk_list(lst: list, size: int) -> list:
"""Split list into chunks of given size."""
return [lst[i:i + size] for i in range(0, len(lst), size)]
def compute_availability(history_entries: list, period_start: datetime, period_end: datetime) -> dict:
"""
Compute availability metrics from HA history entries.
Each entry is a dict with 'state' and 'last_changed'.
Returns dict with: availability_pct, down_count, max_downtime_minutes, last_downtime
"""
unavailable_seconds = 0
down_count = 0
max_downtime = 0
current_downtime_start = None
last_downtime = None
total_seconds = (period_end - period_start).total_seconds()
if not history_entries or total_seconds <= 0:
return {
"availability_pct": 100.0,
"down_count": 0,
"max_downtime_minutes": 0,
"last_downtime": None,
}
# Sort by last_changed
entries = sorted(history_entries, key=lambda e: parse_datetime(e["last_changed"]))
for i, entry in enumerate(entries):
state = entry["state"]
changed = parse_datetime(entry["last_changed"])
# Clamp to period
if changed < period_start:
changed = period_start
# Determine next change time
if i + 1 < len(entries):
next_changed = parse_datetime(entries[i + 1]["last_changed"])
else:
next_changed = period_end
if next_changed > period_end:
next_changed = period_end
if state in ("unavailable", "unknown"):
if current_downtime_start is None:
# Transition to unavailable
current_downtime_start = changed
down_count += 1
duration = (next_changed - changed).total_seconds()
if duration > 0:
unavailable_seconds += duration
last_downtime = changed
# Check if this is the end of a downtime period
if i + 1 < len(entries) and entries[i + 1]["state"] not in ("unavailable", "unknown"):
if current_downtime_start is not None:
downtime = (next_changed - current_downtime_start).total_seconds()
if downtime > max_downtime:
max_downtime = downtime
current_downtime_start = None
# If last entry and still unavailable
elif i == len(entries) - 1:
if current_downtime_start is not None:
downtime = (next_changed - current_downtime_start).total_seconds()
if downtime > max_downtime:
max_downtime = downtime
current_downtime_start = None
else:
# Available state — if there was a downtime running, end it
if current_downtime_start is not None:
downtime = (changed - current_downtime_start).total_seconds()
if downtime > max_downtime:
max_downtime = downtime
current_downtime_start = None
# Handle case where device was unavailable at period_start
# (first entry state determines status from period_start to first change)
if entries and entries[0]["state"] in ("unavailable", "unknown"):
first_change = parse_datetime(entries[0]["last_changed"])
if first_change > period_start:
pre_duration = (first_change - period_start).total_seconds()
unavailable_seconds += pre_duration
# This counts as one transition if not already counted
if current_downtime_start is None:
down_count += 1
# Handle trailing unavailable (last entry is unavailable)
if entries and entries[-1]["state"] in ("unavailable", "unknown"):
last_change = parse_datetime(entries[-1]["last_changed"])
trailing = (period_end - last_change).total_seconds()
if trailing > 0 and current_downtime_start is None:
# Already counted in the loop
pass
pct = round((1 - unavailable_seconds / total_seconds) * 100, 1) if total_seconds > 0 else 100.0
pct = max(0.0, min(100.0, pct))
return {
"availability_pct": pct,
"down_count": down_count,
"max_downtime_minutes": round(max_downtime / 60),
"last_downtime": last_downtime.isoformat() if last_downtime else None,
}
def compute_sparkline(history_entries: list, period_end: datetime, days: int = 7) -> list:
"""Compute daily availability percentages for sparkline (last N days)."""
points = []
for i in range(days - 1, -1, -1):
day_start = period_end - timedelta(days=i + 1)
day_end = period_end - timedelta(days=i)
# Filter entries relevant to this day
day_entries = []
for e in history_entries:
changed = parse_datetime(e["last_changed"])
if changed < day_end and changed >= day_start - timedelta(days=1):
day_entries.append(e)
result = compute_availability(day_entries, day_start, day_end)
points.append(result["availability_pct"])
return points