NestQuest/custom_components/nestquest/materialize.py

"""The materialization walk (Feature 07 core).

:func:`materialize` turns the schedule rules + custody presence of the
active quest definitions into concrete ``quest_instances`` rows over a
date range.  It is the pure walk over definitions x dates x assignees x
windows; HA scheduling (day-rollover triggers) and skip-completed
generation are separate later tasks and live elsewhere.

The walk is deterministic and idempotent:

- Every active definition is read with its decoded
  :class:`~.recurrence.ScheduleRule`, assignees and windows through the
  Feature 06 snapshot helpers, so each bundle is a coherent read.
- Presence is snapshotted into an immutable
  :class:`~.presence.PresenceEngine` from the schedules and overrides of
  every assignee child, read in one locked transaction (see
  :func:`~.dao_presence.load_snapshot`).
- For each date in the range, each definition whose decoded rule
  :func:`~.recurrence.occurs_on` on that date, each assignee who is
  ``is_present`` on that date and each declared window, one instance is
  upserted through :class:`~.dao_instances.QuestInstancesDao.upsert` with
  the window's ``due_time`` snapshotted and a ``generated_at`` stamp
  shared by the whole batch (one coherent time per run).

The upsert is idempotent on (definition_id, child_id, due_date, window),
so re-running the materialization over the same range never duplicates a
row; skipped-completed handling is deliberately NOT done here.
"""
from __future__ import annotations

import datetime

from .dao_instances import QuestInstancesDao
from .dao_presence import load_snapshot
from .dao_rules import (
    QuestDefinitionsDao,
    _validate_date,
    schedule_rule_from_storage,
    schedule_rule_storage_from_record,
)
from .db import NestQuestDatabase
from .presence import PresenceEngine, PresenceOverride, PresenceSchedule
from .recurrence import ScheduleRule, occurs_on


def _now_stamp() -> str:
    """Return the batch's shared UTC second-precision generation stamp."""
    return datetime.datetime.now(datetime.timezone.utc).isoformat(
        timespec="seconds"
    )


def _decode_rule(snapshot) -> ScheduleRule:
    """Decode a snapshot's rule record back into a ScheduleRule.

    The record carried by the snapshot is the one the definition
    referenced at read time, so decoding it here (rather than re-reading
    through ``ScheduleRulesDao``) preserves the coherence the snapshot
    guarantees.
    """
    return schedule_rule_from_storage(
        schedule_rule_storage_from_record(snapshot.rule)
    )


def _build_engine(
    schedules_records,
    overrides_records,
) -> PresenceEngine:
    """Convert raw presence records into an immutable PresenceEngine."""
    schedules: dict[int, PresenceSchedule] = {}
    for child_id, record in schedules_records.items():
        schedules[child_id] = PresenceSchedule.decode(
            child_id, record.anchor_date, record.pattern
        )
    overrides: dict[int, list[PresenceOverride]] = {}
    for child_id, records in overrides_records.items():
        overrides[child_id] = [
            PresenceOverride(
                record.child_id,
                record.start_date,
                record.end_date,
                record.is_present,
                record.note,
            )
            for record in records
        ]
    return PresenceEngine(schedules, overrides)


async def materialize(
    database: NestQuestDatabase,
    start_date: str,
    end_date: str,
) -> int:
    """Generate quest instances for the closed range [start_date, end_date].

    ``start_date`` and ``end_date`` must be strict ISO calendar dates
    (YYYY-MM-DD) with ``end_date`` on or after ``start_date``; anything
    else raises ValueError naming the offending field.  Returns the number
    of instances upserted (idempotent — a re-run for the same batch
    refreshes the same rows, never duplicates them).

    The active definitions and the presence inputs are each read as a
    coherent snapshot, and the presence schedule/overrides are read under
    one locked transaction so the walk sees a single stable view of who
    is where on each date.
    """
    _validate_date(start_date, "start_date")
    _validate_date(end_date, "end_date")
    if end_date < start_date:
        raise ValueError(
            f"end_date must be on or after start_date, got "
            f"{end_date!r} < {start_date!r}"
        )

    snapshots = await QuestDefinitionsDao(database).list_snapshots_active()
    assignee_child_ids = sorted(
        {
            child.id
            for snapshot in snapshots
            for child in snapshot.assignees
        }
    )

    schedules_records, overrides_records = await load_snapshot(
        database, assignee_child_ids, start_date, end_date
    )
    engine = _build_engine(schedules_records, overrides_records)

    definitions = [
        (snapshot.definition.id, _decode_rule(snapshot),
         snapshot.assignees, snapshot.windows)
        for snapshot in snapshots
    ]

    generated_at = _now_stamp()
    instances = QuestInstancesDao(database)

    start = datetime.datetime.strptime(start_date, "%Y-%m-%d").date()
    end = datetime.datetime.strptime(end_date, "%Y-%m-%d").date()

    count = 0
    cursor = start
    while cursor <= end:
        iso = cursor.isoformat()
        for definition_id, rule, assignees, windows in definitions:
            if not occurs_on(rule, cursor):
                continue
            for child in assignees:
                if not engine.is_present(child.id, cursor):
                    continue
                for window in windows:
                    await instances.upsert(
                        definition_id,
                        child.id,
                        iso,
                        generated_at,
                        window=window.window,
                        due_time=window.due_time,
                    )
                    count += 1
        cursor += datetime.timedelta(days=1)
    return count