58 lines
2.0 KiB
Python
58 lines
2.0 KiB
Python
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#!/usr/bin/env python3
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"""回填 chapters.evidence_bundle_json（Phase 九：历史 chapter 无快照时可批量物化）。
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用法（需在已执行 Alembic 0009+ 的库上）::
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cd api && uv run python scripts/backfill_chapter_evidence_snapshots.py
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cd api && uv run python scripts/backfill_chapter_evidence_snapshots.py --user-id <uuid>
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"""
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from __future__ import annotations
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import argparse
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from sqlalchemy import select
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from app.features.auth import models as _auth_models # noqa: F401
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from app.features.conversation import models as _conv_models # noqa: F401
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from app.features.memory import models as _memory_models # noqa: F401
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from app.features.memoir import models as _memoir_models # noqa: F401
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from app.features.payment import models as _payment_models # noqa: F401
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from app.features.story import models as _story_models # noqa: F401
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from app.features.user import models as _user_models # noqa: F401
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from app.core.db import SessionLocal
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from app.features.memoir.chapter_evidence_snapshot import (
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refresh_chapter_evidence_snapshot_sync,
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)
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from app.features.memoir.models import Chapter
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def main() -> None:
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p = argparse.ArgumentParser()
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p.add_argument("--user-id", default="", help="仅刷新该用户的章节；默认全表")
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p.add_argument("--limit", type=int, default=0, help="最多处理条数，0 表示不限制")
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args = p.parse_args()
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uid = (args.user_id or "").strip()
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session = SessionLocal()
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n_ok = 0
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try:
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stmt = select(Chapter.id)
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if uid:
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stmt = stmt.where(Chapter.user_id == uid)
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if args.limit > 0:
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stmt = stmt.limit(args.limit)
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ids = list(session.execute(stmt).scalars().all())
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for cid in ids:
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if refresh_chapter_evidence_snapshot_sync(session, str(cid)):
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n_ok += 1
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session.commit()
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print(f"refreshed_snapshots={n_ok} chapter_rows={len(ids)}")
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finally:
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session.close()
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if __name__ == "__main__":
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main()
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