bvandeusen
3898ce7be4
- BACKFILL_TIMEOUT_SECONDS 1800→1170: keep the subprocess timeout 30s below Celery's hard time_limit=1200 so SIGKILL doesn't beat TimeoutExpired (matched the tick 870s/900s rationale). Backfill runs that hit the cap let the next tick continue via the archive. - recover_interrupted_tasks orphan UPDATE now stamps finished_at; without it cleanup_old_tasks' WHERE finished_at<cutoff never reaped orphan-swept rows. recover_stalled_task_runs also now sets duration_ms (matches celery_signals.finalize's millisecond math). - ExtensionService.quick_add_source arms NEW_SOURCE_BACKFILL_RUNS=3 on Source creation, mirroring SourceService.create. Without it, Firefox quick-add on a creator with >20 unsynced posts walked the full feed until subprocess timeout. Renamed the constant from _NEW_SOURCE_BACKFILL_RUNS so it can be imported cross-module. - gallery_dl.verify() accepts TIER_LIMITED as auth-success alongside NO_NEW_CONTENT — the download path (line 712) already does, and TIER_LIMITED proves auth reached the post and was told it was tier-gated. Verify endpoint previously showed red on this and prompted operators to rotate working cookies. - prune_unused_tags now runs a single DELETE with the NOT-IN predicate find_unused_tags uses, instead of SELECT-ids → DELETE-WHERE-IN. Removes the psycopg 65535-param cliff that would have surfaced on a tag explosion (>65k unused tags). - credentials.upload() reflects the returned record into the store cache (`.set(platform, rec)`) instead of evicting it; previously the card briefly rendered "no credential" between upload and loadAll().
595 lines
21 KiB
Python
595 lines
21 KiB
Python
"""FC-3k: first-class admin destructive operations.
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Projections are pure SELECTs used by both dry-run preview endpoints
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and Tier-B count prompts. Mutations (Task 2) are called from sync
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HTTP handlers (small ops) and from Celery tasks in
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backend.app.tasks.admin (long ops).
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This module is the PERMANENT home of artist-cascade + image-unlink
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logic. (The legacy migrators/cleanup.py copy was removed with the rest of
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the one-and-done GS/IR migration tooling.)
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"""
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from __future__ import annotations
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from datetime import UTC, datetime
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from pathlib import Path
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from typing import Any
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from sqlalchemy import func, or_, select, update
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from sqlalchemy.orm import Session
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from ..models import Artist, ImageRecord, LibraryAuditRun, Tag
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from ..models.series_page import SeriesPage
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from ..models.tag import image_tag
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def project_artist_cascade(session: Session, *, slug: str) -> dict:
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"""Read-only projection of what delete_artist_cascade would touch.
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Returns:
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{
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"artist": {"id": int, "name": str, "slug": str},
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"projected": {
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"images": int,
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"sources": int,
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"thumbs": int, # images with a thumbnail_path set
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"import_tasks": int, # ImportTask rows referencing the artist's images
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"bytes_on_disk": int, # SUM(image_record.size_bytes) — column is NOT NULL
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},
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}
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Raises LookupError if slug not found. No mutations.
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"""
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from ..models.import_task import ImportTask
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from ..models.source import Source
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artist = session.execute(
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select(Artist).where(Artist.slug == slug)
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).scalar_one_or_none()
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if artist is None:
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raise LookupError(f"artist slug not found: {slug!r}")
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images_count = session.execute(
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select(func.count(ImageRecord.id))
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.where(ImageRecord.artist_id == artist.id)
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).scalar_one()
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sources_count = session.execute(
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select(func.count(Source.id))
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.where(Source.artist_id == artist.id)
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).scalar_one()
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thumbs_count = session.execute(
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select(func.count(ImageRecord.id))
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.where(ImageRecord.artist_id == artist.id)
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.where(ImageRecord.thumbnail_path.is_not(None))
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).scalar_one()
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import_tasks_count = session.execute(
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select(func.count(ImportTask.id))
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.where(
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ImportTask.result_image_id.in_(
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select(ImageRecord.id).where(ImageRecord.artist_id == artist.id)
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)
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)
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).scalar_one()
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bytes_on_disk = session.execute(
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select(func.coalesce(func.sum(ImageRecord.size_bytes), 0))
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.where(ImageRecord.artist_id == artist.id)
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).scalar_one()
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return {
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"artist": {"id": artist.id, "name": artist.name, "slug": artist.slug},
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"projected": {
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"images": images_count,
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"sources": sources_count,
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"thumbs": thumbs_count,
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"import_tasks": import_tasks_count,
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"bytes_on_disk": int(bytes_on_disk),
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},
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}
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def project_bulk_image_delete(
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session: Session, *, image_ids: list[int],
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) -> dict:
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"""Read-only projection of what delete_images would touch.
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Returns:
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{
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"images_found": int,
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"thumbs_to_unlink": int,
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"bytes_on_disk": int,
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"missing_ids": list[int], # ids passed in that don't exist
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}
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No mutations.
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"""
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if not image_ids:
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return {
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"images_found": 0,
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"thumbs_to_unlink": 0,
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"bytes_on_disk": 0,
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"missing_ids": [],
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}
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rows = session.execute(
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select(
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ImageRecord.id,
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ImageRecord.thumbnail_path,
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ImageRecord.size_bytes,
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).where(ImageRecord.id.in_(image_ids))
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).all()
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found_ids = {r.id for r in rows}
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missing = sorted(set(image_ids) - found_ids)
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return {
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"images_found": len(rows),
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"thumbs_to_unlink": sum(1 for r in rows if r.thumbnail_path),
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"bytes_on_disk": sum(r.size_bytes for r in rows),
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"missing_ids": missing,
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}
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def count_tag_associations(session: Session, *, tag_id: int) -> int:
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"""COUNT(*) FROM image_tag WHERE tag_id=?. For Tier-B prompt."""
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return session.execute(
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select(func.count())
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.select_from(image_tag)
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.where(image_tag.c.tag_id == tag_id)
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).scalar_one()
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def find_unused_tags(
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session: Session, *, limit: int | None = None,
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) -> list[Tag]:
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"""Tags with no image_tag rows AND no series_page rows.
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Sorted by name. Used by both dry-run preview and the live prune.
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A tag is "unused" iff it has zero rows in image_tag AND zero rows
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in series_page (so we don't accidentally prune a series tag that
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happens to have no images yet).
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"""
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used_via_image_tag = select(image_tag.c.tag_id).distinct()
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used_via_series = select(SeriesPage.series_tag_id).where(
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SeriesPage.series_tag_id.is_not(None)
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).distinct()
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stmt = (
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select(Tag)
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.where(Tag.id.not_in(used_via_image_tag))
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.where(Tag.id.not_in(used_via_series))
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.order_by(Tag.name)
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)
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if limit is not None:
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stmt = stmt.limit(limit)
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return list(session.execute(stmt).scalars().all())
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def unlink_image_files(
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image: ImageRecord, images_root: Path,
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) -> dict:
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"""Best-effort unlink of all on-disk files for an ImageRecord.
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Targets: image.path (original), image.thumbnail_path (cached
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thumbnail), and the computed thumbs path at
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/images/thumbs/<sha256[:3]>/<sha256>.(jpg|png|webp) (tries all
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three extensions; missing extension is silently OK).
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Returns {"original": bool, "thumbnail": bool}. Missing files
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count as success (missing_ok semantics). OSErrors are swallowed
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and reported as False so the calling DB delete still proceeds.
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"""
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out = {"original": False, "thumbnail": False}
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if image.path:
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try:
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Path(image.path).unlink(missing_ok=True)
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out["original"] = True
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except OSError:
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out["original"] = False
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# Custom thumbnail_path (when set) — try it first.
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if image.thumbnail_path:
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try:
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Path(image.thumbnail_path).unlink(missing_ok=True)
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out["thumbnail"] = True
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except OSError:
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out["thumbnail"] = False
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# Convention thumbs dir — try all extensions; missing OK.
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if image.sha256:
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bucket = image.sha256[:3]
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for ext in ("jpg", "png", "webp"):
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try:
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(images_root / "thumbs" / bucket / f"{image.sha256}.{ext}").unlink(
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missing_ok=True,
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)
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except OSError:
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pass
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return out
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def delete_artist_cascade(
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session: Session, *, artist_id: int, images_root: Path,
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) -> dict:
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"""Batched delete of an artist's images + the artist row.
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Mirrors the cleanup_artist_async pattern: 500-row batches,
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commit between batches so partial progress survives a worker
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kill. Idempotent on missing artist (returns zeroed counts).
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Postgres cascades handle image_tag / image_provenance /
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series_page / tag_suggestion_rejection from ImageRecord delete,
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and source / post / download_event / etc. from Artist delete
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(via Artist.sources cascade="all, delete-orphan").
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"""
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artist = session.get(Artist, artist_id)
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if artist is None:
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return {
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"artist": None,
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"summary": {
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"images_deleted": 0,
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"files_deleted": 0,
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"thumbs_deleted": 0,
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"import_tasks_nulled": 0,
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"files_failed": 0,
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},
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}
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artist_info = {"id": artist.id, "name": artist.name, "slug": artist.slug}
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images_deleted = 0
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files_deleted = 0
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thumbs_deleted = 0
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files_failed = 0
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while True:
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rows = session.execute(
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select(ImageRecord)
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.where(ImageRecord.artist_id == artist.id)
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.limit(500)
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).scalars().all()
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if not rows:
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break
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for img in rows:
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unlinked = unlink_image_files(img, images_root)
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if unlinked["original"]:
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files_deleted += 1
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else:
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files_failed += 1
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if unlinked["thumbnail"]:
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thumbs_deleted += 1
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session.delete(img)
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images_deleted += 1
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session.commit()
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# ImportTask.result_image_id FK is SET NULL on image delete (Postgres
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# handles this in the cascade above). We don't separately count those
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# in FC-3k — the legacy cleanup_artist_async did it via
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# source_path_prefix matching that's out of scope here.
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import_tasks_nulled = 0
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session.delete(artist)
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session.commit()
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return {
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"artist": artist_info,
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"summary": {
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"images_deleted": images_deleted,
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"files_deleted": files_deleted,
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"thumbs_deleted": thumbs_deleted,
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"import_tasks_nulled": import_tasks_nulled,
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"files_failed": files_failed,
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},
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}
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def delete_images(
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session: Session, *, image_ids: list[int], images_root: Path,
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) -> dict:
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"""Delete a list of images in 500-row batches with commit between.
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Postgres CASCADE on image_tag / image_provenance / series_page /
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tag_suggestion_rejection / post_attachment(FK SET NULL) handles
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the DB side; this function handles file unlinks first then row
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deletes. Idempotent on missing IDs (returned as missing_ids;
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no error). On partial OSError, the row is still deleted and
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files_failed is incremented.
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"""
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if not image_ids:
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return {
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"images_deleted": 0,
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"files_deleted": 0,
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"thumbs_deleted": 0,
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"files_failed": 0,
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"missing_ids": [],
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}
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seen_ids: set[int] = set()
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images_deleted = 0
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files_deleted = 0
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thumbs_deleted = 0
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files_failed = 0
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pending = list(image_ids)
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while pending:
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batch_ids = pending[:500]
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pending = pending[500:]
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rows = session.execute(
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select(ImageRecord).where(ImageRecord.id.in_(batch_ids))
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).scalars().all()
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for img in rows:
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seen_ids.add(img.id)
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unlinked = unlink_image_files(img, images_root)
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if unlinked["original"]:
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files_deleted += 1
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else:
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files_failed += 1
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if unlinked["thumbnail"]:
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thumbs_deleted += 1
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session.delete(img)
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images_deleted += 1
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session.commit()
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missing = sorted(set(image_ids) - seen_ids)
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return {
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"images_deleted": images_deleted,
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"files_deleted": files_deleted,
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"thumbs_deleted": thumbs_deleted,
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"files_failed": files_failed,
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"missing_ids": missing,
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}
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def delete_tag(session: Session, *, tag_id: int) -> dict:
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"""Simple DELETE FROM tag WHERE id=?.
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Postgres cascades the rest (image_tag, tag_alias, tag_allowlist,
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tag_reference_embedding, tag_suggestion_rejection, series_page).
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Returns counts BEFORE delete so the caller can surface them.
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Raises LookupError if tag_id not found.
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"""
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tag = session.get(Tag, tag_id)
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if tag is None:
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raise LookupError(f"tag id not found: {tag_id}")
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associations_count = count_tag_associations(session, tag_id=tag_id)
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info = {"id": tag.id, "name": tag.name, "kind": tag.kind.value}
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session.delete(tag)
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session.commit()
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return {"deleted": info, "associations_removed": associations_count}
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def prune_unused_tags(session: Session, *, dry_run: bool = False) -> dict:
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"""Find tags with zero references and (unless dry_run) delete them.
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Returns:
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dry_run=True: {"count": N, "sample_names": [first 50]}
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dry_run=False: {"deleted": N, "sample_names": [first 50]}
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Implementation note: the previous SELECT-ids → DELETE-WHERE-IN
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pattern was vulnerable to the psycopg 65535-parameter ceiling on
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libraries with tag explosions. The live delete now runs a single
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DELETE with the same NOT-IN predicate find_unused_tags uses, so
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the row count scales without binding every id as a parameter.
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Audit 2026-06-02.
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"""
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sample_rows = find_unused_tags(session, limit=50)
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sample = [t.name for t in sample_rows]
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used_via_image_tag = select(image_tag.c.tag_id).distinct()
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used_via_series = select(SeriesPage.series_tag_id).where(
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SeriesPage.series_tag_id.is_not(None)
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).distinct()
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if dry_run:
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count = session.execute(
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select(func.count())
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.select_from(Tag)
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.where(Tag.id.not_in(used_via_image_tag))
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.where(Tag.id.not_in(used_via_series))
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).scalar_one()
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return {"count": count, "sample_names": sample}
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result = session.execute(
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Tag.__table__.delete()
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.where(Tag.id.not_in(used_via_image_tag))
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.where(Tag.id.not_in(used_via_series))
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)
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session.commit()
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return {"deleted": result.rowcount or 0, "sample_names": sample}
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# Legacy tags FC no longer uses, in two shapes:
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# (1) kinds the tag input never produces — archive/post/artist.
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# provenance (post grouping) + archive membership are their own
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# systems now, and artists are first-class Artist/Source rows.
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# meta/rating were already hard-deleted by alembic 0023.
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# (2) name prefixes from IR kinds FC never adopted — `source:*`.
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# ImageRepo had a `source` kind; FC's enum doesn't, so ir_ingest
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# fell those back to `general` (kind=general, name="source:patreon"
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# etc.). They can't be caught by kind, so we match the name prefix.
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PURGEABLE_TAG_KINDS = ("archive", "post", "artist")
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LEGACY_NAME_PREFIXES = ("source:",)
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def _legacy_tag_predicate():
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name_clauses = [Tag.name.like(f"{p}%") for p in LEGACY_NAME_PREFIXES]
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return or_(Tag.kind.in_(PURGEABLE_TAG_KINDS), *name_clauses)
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def purge_legacy_tags(session: Session, *, dry_run: bool = False) -> dict:
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"""Count (dry_run) or delete legacy IR-migration tags: archive/post/
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artist-kind tags PLUS general tags whose name matches a legacy
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prefix (source:*).
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CASCADE on image_tag / tag_alias / tag_allowlist /
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tag_reference_embedding / tag_suggestion_rejection / series_page
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clears the related rows on the parent DELETE.
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Returns:
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{"by_kind": {kind: count, ...}, # kind-matched rows
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"by_prefix": {"source:*": count}, # name-prefix-matched rows
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"count": total, "sample_names": [first 50],
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and on live runs "deleted": total}
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"""
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predicate = _legacy_tag_predicate()
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rows = session.execute(
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select(Tag.id, Tag.name, Tag.kind).where(predicate)
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).all()
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by_kind: dict[str, int] = {}
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by_prefix: dict[str, int] = {}
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for _id, name, kind in rows:
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# Classify by name-prefix first so a source:* row counts once,
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# under the prefix bucket, regardless of its (general) kind.
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matched_prefix = next(
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(p for p in LEGACY_NAME_PREFIXES if name.startswith(p)), None,
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)
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if matched_prefix is not None:
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label = f"{matched_prefix}*"
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by_prefix[label] = by_prefix.get(label, 0) + 1
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else:
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key = kind.value if hasattr(kind, "value") else str(kind)
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by_kind[key] = by_kind.get(key, 0) + 1
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sample = [name for _id, name, _kind in rows[:50]]
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total = len(rows)
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result = {
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"by_kind": by_kind, "by_prefix": by_prefix,
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"count": total, "sample_names": sample,
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}
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if dry_run:
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return result
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if total:
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session.execute(Tag.__table__.delete().where(predicate))
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session.commit()
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result["deleted"] = total
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return result
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# ---------------------------------------------------------------------------
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# FC-Cleanup additions (2026-05-26): retroactive audit of import-filter rules.
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# ---------------------------------------------------------------------------
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_MIN_DIM_SAMPLE_CAP = 50
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def project_min_dimension_violations(
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session: Session, *, min_width: int, min_height: int,
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) -> dict:
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"""Return {count, sample_ids} for image_record rows with width or
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height below the thresholds. Synchronous SQL — no PIL inspection
|
|
needed since width/height are stored columns."""
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base = select(ImageRecord.id).where(
|
|
(ImageRecord.width < min_width) | (ImageRecord.height < min_height)
|
|
)
|
|
count = session.execute(
|
|
select(func.count()).select_from(base.subquery())
|
|
).scalar_one()
|
|
sample_ids = session.execute(
|
|
base.order_by(ImageRecord.id).limit(_MIN_DIM_SAMPLE_CAP)
|
|
).scalars().all()
|
|
return {"count": count, "sample_ids": list(sample_ids)}
|
|
|
|
|
|
def delete_min_dimension_violations(
|
|
session: Session, *, min_width: int, min_height: int, images_root: Path,
|
|
) -> int:
|
|
"""Delete every image_record where width<min_w OR height<min_h.
|
|
Routes through delete_images so file-unlink + cascading FKs
|
|
(image_tag / image_provenance / etc.) are handled uniformly."""
|
|
ids = session.execute(
|
|
select(ImageRecord.id).where(
|
|
(ImageRecord.width < min_width) | (ImageRecord.height < min_height)
|
|
)
|
|
).scalars().all()
|
|
if not ids:
|
|
return 0
|
|
result = delete_images(
|
|
session, image_ids=list(ids), images_root=images_root,
|
|
)
|
|
return result["images_deleted"]
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Audit lifecycle (transparency + single_color async scans).
|
|
# ---------------------------------------------------------------------------
|
|
|
|
|
|
class AuditAlreadyRunning(Exception):
|
|
"""Another audit_run is currently in status='running' — wait or
|
|
cancel it before starting a new one. Surfaces as HTTP 409 in the
|
|
/api/cleanup/audit POST endpoint."""
|
|
|
|
|
|
class AuditNotReady(Exception):
|
|
"""apply_audit_run called on an audit whose status is not 'ready'."""
|
|
|
|
|
|
class ConfirmTokenMismatch(Exception):
|
|
"""Operator-supplied confirm token did not match server-recomputed token."""
|
|
|
|
|
|
_VALID_RULES = ("transparency", "single_color")
|
|
|
|
|
|
def start_audit_run(
|
|
session: Session, *, rule: str, params: dict[str, Any],
|
|
) -> int:
|
|
"""Create a LibraryAuditRun row in status='running' and dispatch the
|
|
scan_library_for_rule Celery task. Returns the new audit_id.
|
|
|
|
Concurrent-runs guard: raises AuditAlreadyRunning if any audit_run
|
|
has status='running'. Operator must cancel or wait."""
|
|
if rule not in _VALID_RULES:
|
|
raise ValueError(f"unknown rule {rule!r}; expected one of {_VALID_RULES}")
|
|
existing = session.execute(
|
|
select(LibraryAuditRun.id).where(LibraryAuditRun.status == "running")
|
|
).scalar_one_or_none()
|
|
if existing is not None:
|
|
raise AuditAlreadyRunning(existing)
|
|
audit = LibraryAuditRun(
|
|
rule=rule,
|
|
params=params,
|
|
status="running",
|
|
scanned_count=0,
|
|
matched_count=0,
|
|
matched_ids=[],
|
|
)
|
|
session.add(audit)
|
|
session.flush()
|
|
audit_id = audit.id
|
|
# Dispatch after flush so audit_id is populated; commit happens in
|
|
# the API handler so the audit row + dispatch are visible together.
|
|
from ..tasks.library_audit import scan_library_for_rule
|
|
scan_library_for_rule.delay(audit_id)
|
|
return audit_id
|
|
|
|
|
|
def apply_audit_run(
|
|
session: Session, *, audit_id: int, confirm_token: str, images_root: Path,
|
|
) -> int:
|
|
"""Delete all images in audit_run.matched_ids after confirming token.
|
|
Marks audit status='applied'. Routes through delete_images so files
|
|
+ cascading FK rows are handled uniformly."""
|
|
audit = session.execute(
|
|
select(LibraryAuditRun).where(LibraryAuditRun.id == audit_id)
|
|
).scalar_one_or_none()
|
|
if audit is None:
|
|
raise ValueError(f"audit_run {audit_id} not found")
|
|
if audit.status != "ready":
|
|
raise AuditNotReady(audit.status)
|
|
# Token format matches modal/DestructiveConfirmModal.vue convention:
|
|
# ${action}-${kind}-${runId}. The modal hardcodes action ∈ {'restore',
|
|
# 'delete'}; "apply audit" is semantically a delete of the matched
|
|
# images, so we use 'delete-audit-<id>' (not 'apply-audit-<id>').
|
|
expected = f"delete-audit-{audit_id}"
|
|
if confirm_token != expected:
|
|
raise ConfirmTokenMismatch(expected)
|
|
ids = list(audit.matched_ids or [])
|
|
deleted = 0
|
|
if ids:
|
|
result = delete_images(session, image_ids=ids, images_root=images_root)
|
|
deleted = result["images_deleted"]
|
|
session.execute(
|
|
update(LibraryAuditRun)
|
|
.where(LibraryAuditRun.id == audit_id)
|
|
.values(status="applied", finished_at=datetime.now(UTC))
|
|
)
|
|
return deleted
|
|
|
|
|
|
def cancel_audit_run(session: Session, *, audit_id: int) -> None:
|
|
"""Flip a running audit_run to 'cancelled'. The scan task checks
|
|
for status=='cancelled' between batches and exits cleanly."""
|
|
session.execute(
|
|
update(LibraryAuditRun)
|
|
.where(LibraryAuditRun.id == audit_id)
|
|
.where(LibraryAuditRun.status == "running")
|
|
.values(status="cancelled", finished_at=datetime.now(UTC))
|
|
)
|