589 lines
25 KiB
Python
589 lines
25 KiB
Python
"""Maintenance task model."""
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from __future__ import annotations
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from dataclasses import dataclass, field
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from datetime import date, time
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from typing import Any
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from uuid import uuid4
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from homeassistant.util import dt as dt_util
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from ..const import (
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DEFAULT_MAX_HISTORY_ENTRIES,
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DEFAULT_WARNING_DAYS,
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HistoryEntryType,
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MaintenanceStatus,
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MaintenanceTypeEnum,
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ScheduleType,
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)
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from ..helpers.dates import parse_iso_date
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from ..helpers.schedule import Schedule, read_legacy_fields
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@dataclass
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class MaintenanceTask:
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"""Represents a specific maintenance task belonging to an object.
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Examples: 'Filter Cleaning' for Pool Pump, 'Oil Change' for Car.
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"""
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# --- Identity ---
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id: str = field(default_factory=lambda: uuid4().hex)
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object_id: str = ""
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name: str = ""
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type: str = MaintenanceTypeEnum.CUSTOM
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enabled: bool = True
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# --- Schedule ---
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schedule_type: str = ScheduleType.TIME_BASED
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interval_days: int | None = None
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interval_unit: str = "days" # days | weeks | months | years (calendar-aware)
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warning_days: int = DEFAULT_WARNING_DAYS
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# Completion window: max days *before* the due date a task may be completed.
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# None = no restriction (complete any time). 0 = only on/after the due date.
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earliest_completion_days: int | None = None
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last_performed: str | None = None # ISO format YYYY-MM-DD
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created_at: str | None = None # ISO date: fallback anchor for next_due when last_performed is None
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interval_anchor: str = "completion" # "completion" or "planned"
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last_planned_due: str | None = None # ISO date: anchor for planned mode
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schedule_time: str | None = None # "HH:MM" in HA's configured TZ; None = midnight (default)
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due_date: str | None = None # ISO date: one-time task due date (ScheduleType.ONE_TIME)
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# Per-occurrence postpone: an ISO date that overrides just the CURRENT
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# cycle's due date (see Schedule.next_due). Cleared on completion so the
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# next cycle returns to the normal cadence. Dynamic (lives in the Store).
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due_override: str | None = None
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# Raw nested schedule dict (schedule-model v2). The source of truth for the
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# calendar kinds (weekdays/nth_weekday/day_of_month), which the flat fields
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# above can't represent. None for legacy/flat-only data.
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schedule_raw: dict[str, Any] | None = None
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# --- Trigger ---
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trigger_config: dict[str, Any] | None = None
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# --- Metadata ---
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notes: str | None = None
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documentation_url: str | None = None
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custom_icon: str | None = None
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nfc_tag_id: str | None = None
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priority: str = "normal"
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labels: list[str] = field(default_factory=list)
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# --- Meter readings (v2.20, #83) ---
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# Display unit for the recorded value of a `reading`-type task ("kWh",
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# "m³", …). The value itself lives per completion in the history entry
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# (`reading_value`), so the unit is task-level config, not state.
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reading_unit: str | None = None
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# --- Archive (v2.10.0) ---
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# archived_at is an ISO timestamp; None means active. When set, the task
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# reads the ARCHIVED status (highest precedence) and goes inert everywhere
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# except budget/cost history. archived_reason is one of ARCHIVE_REASON_*
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# (manual | auto | object) and drives the auto-delete + object-cascade rules.
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archived_at: str | None = None
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archived_reason: str | None = None
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# --- User Assignment ---
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responsible_user_id: str | None = None # HA user UUID (current pointer)
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assignee_pool: list[str] = field(default_factory=list) # HA user UUIDs
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rotation_strategy: str | None = None # round_robin | least_completed | random
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# --- Checklist ---
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checklist: list[str] = field(default_factory=list)
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# --- Adaptive Scheduling ---
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adaptive_config: dict[str, Any] | None = None
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# --- History ---
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history: list[dict[str, Any]] = field(default_factory=list)
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# --- Runtime (not persisted) ---
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_trigger_active: bool = field(default=False, repr=False)
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_trigger_current_value: float | None = field(default=None, repr=False)
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# --- Computed Properties ---
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@property
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def next_due(self) -> date | None:
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"""Calculate the next due date.
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- ``one_time`` tasks are due on ``due_date`` and return ``None`` once
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completed (they archive instead of re-arming).
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- Otherwise the date is ``last_performed (or created_at) + interval``,
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where the interval honours ``interval_unit`` (days/weeks/months/years).
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With ``interval_anchor == "planned"`` the date is computed from the
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previously planned due date to avoid drift for strictly periodic tasks.
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Example (30-day interval, planned for March 1):
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- Completed March 5 → next due: March 31 (not April 4)
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- If never completed the date may be in the past → OVERDUE.
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"""
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# Recurrence is computed by the Schedule value object
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# (helpers/schedule.py, Phase 2). ISO parsing stays here at the boundary;
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# a *malformed* last_performed preserves the historical "no next_due".
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last: date | None = None
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if self.last_performed:
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try:
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last = date.fromisoformat(self.last_performed)
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except (ValueError, TypeError):
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return None
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return self._schedule().next_due(
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last_performed=last,
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created_at=parse_iso_date(self.created_at),
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last_planned_due=parse_iso_date(self.last_planned_due),
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today=dt_util.now().date(),
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times_performed=self.times_performed,
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due_override=parse_iso_date(self.due_override),
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)
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def _schedule(self) -> Schedule:
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"""The recurrence as a value object (see docs/design/schedule-model-v2.md).
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A nested ``schedule_raw`` is authoritative — it's the only representation
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that carries the calendar kinds (weekdays / nth_weekday / day_of_month).
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Otherwise fall back to the flat fields (legacy / old exports)."""
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if isinstance(self.schedule_raw, dict) and self.schedule_raw.get("kind"):
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return Schedule.from_dict(self.schedule_raw)
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return Schedule.from_legacy(
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schedule_type=self.schedule_type,
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interval_days=self.interval_days,
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interval_unit=self.interval_unit,
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interval_anchor=self.interval_anchor,
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due_date=self.due_date,
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)
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@property
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def days_until_due(self) -> int | None:
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"""Calculate days until the task is due. Negative means overdue."""
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due = self.next_due
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if due is None:
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return None
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return (due - dt_util.now().date()).days
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def _is_past_schedule_time(self) -> bool:
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"""True iff a `schedule_time` is set AND current local time is past it.
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Used as a sub-day refinement of the OVERDUE transition: when `days_until_due`
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is exactly 0, the task is considered overdue once the configured HH:MM has
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passed (in HA's configured TZ). Returns False when no `schedule_time` is set
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— that preserves the historical "due at midnight" semantic.
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"""
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if not self.schedule_time:
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return False
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try:
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# Tolerate both "HH:MM" (panel/WS) and "HH:MM:SS" (HA TimeSelector
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# in the config-flow) — take the first two components.
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parts = str(self.schedule_time).split(":")
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target = time(int(parts[0]), int(parts[1]))
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except (ValueError, TypeError, IndexError):
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return False
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return dt_util.now().time() >= target
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@property
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def archived(self) -> bool:
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"""True iff the task is archived (retired but retained)."""
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return self.archived_at is not None
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@property
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def status(self) -> MaintenanceStatus:
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"""Determine the current status of this task."""
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# Archived takes precedence over everything — a retired task is inert.
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# Mirror this in helpers/status.compute_status_from_task_dict (the dict
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# twin used where only coordinator data is available).
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if self.archived_at is not None:
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return MaintenanceStatus.ARCHIVED
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# Trigger takes precedence
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if self._trigger_active:
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return MaintenanceStatus.TRIGGERED
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days = self.days_until_due
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if days is None:
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# Manual task or no schedule: always OK unless triggered
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return MaintenanceStatus.OK
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if days < 0:
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return MaintenanceStatus.OVERDUE
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# Sub-day refinement: same-day past schedule_time also counts as overdue.
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# Without this, a task with schedule_time="09:00" would only flip at midnight.
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if days == 0 and self._is_past_schedule_time():
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return MaintenanceStatus.OVERDUE
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# Don't let the warning window exceed one interval, measured in real
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# days via the Schedule (a 6-*month* task must not collapse a 14-day
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# warning to min(14, 6) — issue #58). Single source: the Schedule, not
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# raw interval fields.
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span = self._schedule().span_days()
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effective_warning = min(self.warning_days, span) if span else self.warning_days
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if days <= effective_warning:
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return MaintenanceStatus.DUE_SOON
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return MaintenanceStatus.OK
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@property
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def can_complete_now(self) -> bool:
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"""Whether completion is currently allowed by the completion window.
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A task with ``earliest_completion_days`` set may only be completed once
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it's within that many days of its due date (or overdue). Tasks without
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a schedule (``days_until_due is None``) are always completable.
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"""
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if self.earliest_completion_days is None:
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return True
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days = self.days_until_due
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if days is None:
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return True
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return days <= self.earliest_completion_days
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@property
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def is_done(self) -> bool:
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"""True for a completed one-time task, or a finite series that has ended.
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("Done" is the terminal state of a one-off. It is distinct from
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"archived" — see ``archived`` — which is the retire-but-retain state
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added in v2.10.0 and reserved for that feature.)
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"""
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if self.schedule_type == ScheduleType.ONE_TIME and self.last_performed is not None:
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return True
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# A finite recurring series (repeat N times / recur until a date) is
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# terminally done once it has been performed and no longer re-arms.
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if self.last_performed is not None and self._schedule().is_finite() and self.next_due is None:
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return True
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return False
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@property
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def times_performed(self) -> int:
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"""Count the number of completed maintenance entries in history."""
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return sum(1 for entry in self.history if entry.get("type") == HistoryEntryType.COMPLETED)
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@property
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def total_cost(self) -> float:
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"""Sum of all costs in history."""
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total = 0.0
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for entry in self.history:
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cost = entry.get("cost")
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if cost is None:
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continue
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try:
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total += float(cost)
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except (ValueError, TypeError):
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continue
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return total
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@property
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def average_duration(self) -> float | None:
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"""Average duration of completed maintenance in minutes."""
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durations = [
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entry["duration"]
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for entry in self.history
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if entry.get("type") == HistoryEntryType.COMPLETED and entry.get("duration") is not None
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]
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if not durations:
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return None
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return float(sum(durations)) / len(durations)
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@property
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def last_entry(self) -> dict[str, Any] | None:
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"""Return the most recent history entry."""
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if not self.history:
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return None
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return self.history[-1]
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# --- Methods ---
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def complete(
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self,
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notes: str | None = None,
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cost: float | None = None,
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duration: int | None = None,
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checklist_state: dict[str, bool] | None = None,
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feedback: str | None = None,
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completed_by: str | None = None,
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photo_doc_id: str | None = None,
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reading_value: float | None = None,
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used_parts: list[dict[str, Any]] | None = None,
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auto: bool = False,
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) -> None:
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"""Mark this task as completed.
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``auto`` marks a completion nobody performed in the UI (a trigger
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recovering on its own): the history entry is flagged so surfaces can
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label it, and the rotation pointer stays put — advancing it would
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credit/skip a pool member for work nobody attributed."""
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# Save current next_due as anchor for planned mode before resetting
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if self.interval_anchor == "planned" and self.next_due is not None:
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self.last_planned_due = self.next_due.isoformat()
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now = dt_util.now()
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self.last_performed = now.date().isoformat()
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self._trigger_active = False
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self._trigger_current_value = None
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# A postponed occurrence is consumed by completing it — the next cycle
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# returns to the normal cadence.
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self.due_override = None
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self.add_history_entry(
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entry_type=HistoryEntryType.COMPLETED,
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notes=notes,
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cost=cost,
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duration=duration,
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checklist_state=checklist_state,
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feedback=feedback,
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completed_by=completed_by,
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photo_doc_id=photo_doc_id,
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reading_value=reading_value,
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used_parts=used_parts,
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auto=auto,
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)
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# Shared tasks: rotate the "currently responsible" pointer to the next
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# assignee for the coming cycle (after this completion is recorded, so
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# least_completed sees it). Auto-completions don't rotate — see above.
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if not auto:
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self.advance_rotation()
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def advance_rotation(self) -> None:
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"""Advance ``responsible_user_id`` to the next pool member.
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No-op unless a rotation strategy is set and the pool has ≥2 members.
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- ``round_robin``: next after the current pointer (wraps).
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- ``least_completed``: the pool member credited with the fewest
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completions in history (tie-break by pool order).
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- ``random``: a random *other* member (falls back to the pool if the
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current pointer is the only entry left).
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"""
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pool = [u for u in self.assignee_pool if u]
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if len(pool) < 2 or not self.rotation_strategy:
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return
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current = self.responsible_user_id
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if self.rotation_strategy == "round_robin":
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idx = pool.index(current) if current in pool else -1
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self.responsible_user_id = pool[(idx + 1) % len(pool)]
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elif self.rotation_strategy == "least_completed":
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counts = dict.fromkeys(pool, 0)
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for h in self.history:
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who = h.get("completed_by")
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if who in counts:
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counts[who] += 1
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self.responsible_user_id = min(pool, key=lambda u: counts[u])
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elif self.rotation_strategy == "random":
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import random
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others = [u for u in pool if u != current] or pool
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self.responsible_user_id = random.choice(others)
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def reset(self, reset_date: date | None = None) -> None:
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"""Reset last performed to a specific date."""
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if reset_date is None:
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reset_date = dt_util.now().date()
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self.last_performed = reset_date.isoformat()
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# Clear planned anchor so next_due is computed from the reset date
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self.last_planned_due = None
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self.add_history_entry(
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entry_type=HistoryEntryType.RESET,
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notes=f"Reset to {reset_date.isoformat()}",
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)
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def skip(self, reason: str | None = None, *, as_missed: bool = False) -> None:
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"""Skip the current maintenance cycle.
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``as_missed=True`` records the cycle as MISSED (was due and never done)
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rather than a deliberate SKIPPED — clearer history + compliance views.
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The cycle restarts either way.
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"""
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# Save current next_due as anchor for planned mode before resetting
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if self.interval_anchor == "planned" and self.next_due is not None:
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self.last_planned_due = self.next_due.isoformat()
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# Move last_performed to today to restart the cycle
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self.last_performed = dt_util.now().date().isoformat()
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self._trigger_active = False
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# A postponed occurrence is consumed by skipping it too — otherwise the
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# override (> last_performed) would keep winning in next_due and the
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# "cycle restarts either way" promise above would be false.
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self.due_override = None
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self.add_history_entry(
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entry_type=HistoryEntryType.MISSED if as_missed else HistoryEntryType.SKIPPED,
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notes=reason,
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)
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def add_history_entry(
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self,
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entry_type: str,
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notes: str | None = None,
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cost: float | None = None,
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duration: int | None = None,
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trigger_value: float | None = None,
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checklist_state: dict[str, bool] | None = None,
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feedback: str | None = None,
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completed_by: str | None = None,
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photo_doc_id: str | None = None,
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reading_value: float | None = None,
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used_parts: list[dict[str, Any]] | None = None,
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auto: bool = False,
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) -> None:
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"""Add an entry to the maintenance history."""
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entry: dict[str, Any] = {
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"timestamp": dt_util.now().isoformat(),
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"type": entry_type,
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}
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if auto:
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entry["auto"] = True
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if notes is not None:
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entry["notes"] = notes
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if cost is not None:
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entry["cost"] = cost
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if duration is not None:
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entry["duration"] = duration
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if trigger_value is not None:
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entry["trigger_value"] = trigger_value
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if checklist_state is not None:
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entry["checklist_state"] = checklist_state
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if feedback is not None:
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entry["feedback"] = feedback
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if completed_by is not None:
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entry["completed_by"] = completed_by
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if photo_doc_id is not None:
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entry["photo_doc_id"] = photo_doc_id
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# Meter readings (v2.20, #83): the recorded value rides on the
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# completion entry — the delta view derives from consecutive entries.
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if reading_value is not None:
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entry["reading_value"] = reading_value
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if used_parts:
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# #99: the parts actually used on THIS completion ([{part_id,
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# name, quantity}]) — explicit per-completion consumption record.
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entry["used_parts"] = used_parts
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self.history.append(entry)
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# Trim history to max entries — TYPE-AWARE (journey K1): trigger
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# noise is evicted first, so a flapping sensor (hundreds of
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# `triggered` entries) can never push out the completion record that
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# `times_performed` / `total_cost` / adaptive learning are computed
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# from. Only if dropping all trigger entries still isn't enough does
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# the trim fall back to oldest-first over everything.
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if len(self.history) > DEFAULT_MAX_HISTORY_ENTRIES:
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overflow = len(self.history) - DEFAULT_MAX_HISTORY_ENTRIES
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noise_types = {
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HistoryEntryType.TRIGGERED,
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HistoryEntryType.TRIGGER_REMOVED,
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}
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kept: list[dict[str, Any]] = []
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dropped = 0
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for h in self.history:
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if dropped < overflow and h.get("type") in noise_types:
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dropped += 1
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continue
|
|
kept.append(h)
|
|
if len(kept) > DEFAULT_MAX_HISTORY_ENTRIES:
|
|
kept = kept[-DEFAULT_MAX_HISTORY_ENTRIES:]
|
|
self.history = kept
|
|
|
|
# --- Serialization ---
|
|
|
|
def to_dict(self) -> dict[str, Any]:
|
|
"""Serialize to dictionary for config entry storage."""
|
|
data: dict[str, Any] = {
|
|
"id": self.id,
|
|
"object_id": self.object_id,
|
|
"name": self.name,
|
|
"type": self.type,
|
|
"enabled": self.enabled,
|
|
"warning_days": self.warning_days,
|
|
"history": self.history,
|
|
}
|
|
# Recurrence as the nested `schedule` value object (schedule-model v2).
|
|
# Sensor-ness stays in trigger_config; schedule_type is derived on read
|
|
# via read_legacy_fields, so it is no longer stored.
|
|
data["schedule"] = self._schedule().to_dict()
|
|
if self.last_planned_due is not None:
|
|
data["last_planned_due"] = self.last_planned_due
|
|
if self.due_override is not None:
|
|
data["due_override"] = self.due_override
|
|
if self.schedule_time is not None:
|
|
data["schedule_time"] = self.schedule_time
|
|
if self.last_performed is not None:
|
|
data["last_performed"] = self.last_performed
|
|
if self.created_at is not None:
|
|
data["created_at"] = self.created_at
|
|
if self.trigger_config is not None:
|
|
data["trigger_config"] = self.trigger_config
|
|
if self.notes is not None:
|
|
data["notes"] = self.notes
|
|
if self.documentation_url is not None:
|
|
data["documentation_url"] = self.documentation_url
|
|
if self.custom_icon is not None:
|
|
data["custom_icon"] = self.custom_icon
|
|
if self.nfc_tag_id is not None:
|
|
data["nfc_tag_id"] = self.nfc_tag_id
|
|
if self.reading_unit is not None:
|
|
data["reading_unit"] = self.reading_unit
|
|
# Only persist a non-default priority to keep stored dicts lean.
|
|
if self.priority and self.priority != "normal":
|
|
data["priority"] = self.priority
|
|
if self.labels:
|
|
data["labels"] = self.labels
|
|
if self.earliest_completion_days is not None:
|
|
data["earliest_completion_days"] = self.earliest_completion_days
|
|
if self.archived_at is not None:
|
|
data["archived_at"] = self.archived_at
|
|
if self.archived_reason is not None:
|
|
data["archived_reason"] = self.archived_reason
|
|
if self.responsible_user_id is not None:
|
|
data["responsible_user_id"] = self.responsible_user_id
|
|
if self.assignee_pool:
|
|
data["assignee_pool"] = self.assignee_pool
|
|
if self.rotation_strategy:
|
|
data["rotation_strategy"] = self.rotation_strategy
|
|
if self.checklist:
|
|
data["checklist"] = self.checklist
|
|
if self.adaptive_config is not None:
|
|
data["adaptive_config"] = self.adaptive_config
|
|
return data
|
|
|
|
@classmethod
|
|
def from_dict(cls, data: dict[str, Any]) -> MaintenanceTask:
|
|
"""Deserialize from dictionary.
|
|
|
|
Accepts both the nested ``schedule`` storage (Phase 3) and the flat
|
|
v2.6.x fields via :func:`read_legacy_fields` — the recurrence is held
|
|
in flat attributes in memory either way, so every existing reader of
|
|
``task.interval_days`` etc. is unaffected.
|
|
"""
|
|
sched = read_legacy_fields(data)
|
|
return cls(
|
|
id=data.get("id", uuid4().hex),
|
|
object_id=data.get("object_id", ""),
|
|
name=data.get("name", ""),
|
|
type=data.get("type", MaintenanceTypeEnum.CUSTOM),
|
|
enabled=data.get("enabled", True),
|
|
schedule_type=sched["schedule_type"],
|
|
interval_days=sched["interval_days"],
|
|
interval_unit=sched["interval_unit"],
|
|
due_date=sched["due_date"],
|
|
schedule_raw=data.get("schedule") if isinstance(data.get("schedule"), dict) else None,
|
|
warning_days=data.get("warning_days", DEFAULT_WARNING_DAYS),
|
|
earliest_completion_days=data.get("earliest_completion_days"),
|
|
last_performed=data.get("last_performed"),
|
|
created_at=data.get("created_at"),
|
|
interval_anchor=sched["interval_anchor"],
|
|
last_planned_due=data.get("last_planned_due"),
|
|
due_override=data.get("due_override"),
|
|
schedule_time=data.get("schedule_time"),
|
|
trigger_config=data.get("trigger_config"),
|
|
notes=data.get("notes"),
|
|
documentation_url=data.get("documentation_url"),
|
|
custom_icon=data.get("custom_icon"),
|
|
nfc_tag_id=data.get("nfc_tag_id"),
|
|
reading_unit=data.get("reading_unit"),
|
|
priority=data.get("priority", "normal"),
|
|
labels=data.get("labels", []),
|
|
archived_at=data.get("archived_at"),
|
|
archived_reason=data.get("archived_reason"),
|
|
responsible_user_id=data.get("responsible_user_id"),
|
|
assignee_pool=data.get("assignee_pool", []),
|
|
rotation_strategy=data.get("rotation_strategy"),
|
|
checklist=data.get("checklist", []),
|
|
adaptive_config=data.get("adaptive_config"),
|
|
history=data.get("history", []),
|
|
)
|