refactor(services): one periodic-task shape, one APScheduler job shape, one token hash, one summary rule — the services pass of the shape audit (#2830, milestone 296)
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- background.start_periodic(interval, work, label=) replaces the three hand-rolled while-True/sleep/try loops in logging, auth and notifications. - services/scheduler.ScheduledJob replaces the four private BackgroundScheduler copies in recurrence/version_pinning/trash/db_maintenance schedulers; public start_/stop_/reschedule_ surfaces unchanged. - api_keys.hash_token is the one sha256 helper; auth.py used to inline it 5x. - auth.is_registration_open reads via settings.get_admin_setting; notification prefs read via settings.get_setting; _fire_share_email uses _get_user_email. - projects.get_project_summary / milestones.get_project_milestone_summary are now the one-id view of their batch siblings instead of a second copy of the queries; sharing.best_permission_by (was _deduplicate_by_permission) is the one rank-dedup, now also used by list_projects_for_user. - backup: the row builders for every section both exporters carry are named functions, so a column added to one export cannot silently miss the other. - iso() from models.base replaces the attr.isoformat()-if-attr-else-None idiom and db_maintenance._iso across services; backup keeps its explicit shape. - trash.py hoists the sql_delete/timedelta imports it re-imported per function. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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@@ -21,6 +21,7 @@ from datetime import datetime, timezone
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from sqlalchemy import text
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from scribe.models import async_session, engine
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from scribe.models.base import iso
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from scribe.services.settings import get_admin_setting, set_admin_setting
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logger = logging.getLogger(__name__)
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@@ -128,10 +129,6 @@ _HEALTH_SQL = text("""
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""")
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def _iso(value) -> str | None:
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return value.isoformat() if value is not None else None
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async def get_table_health() -> dict:
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"""Per-table health from Postgres statistics + the total database size.
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@@ -156,8 +153,8 @@ async def get_table_health() -> dict:
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"dead_pct": float(r["dead_pct"] or 0),
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"total_bytes": int(r["total_bytes"] or 0),
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"mod_since_analyze": int(r["mod_since_analyze"] or 0),
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"last_vacuum": _iso(r["last_vacuum"]),
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"last_analyze": _iso(r["last_analyze"]),
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"last_vacuum": iso(r["last_vacuum"]),
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"last_analyze": iso(r["last_analyze"]),
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}
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for r in rows
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]
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