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Milestone 328's acceptance test compared a database built by the real
0001..0087 chain against one built from the models, and found ~130
places where they disagree. This closes them.
Almost all were the MODEL being wrong, so almost all of this is model
edits with no DDL — the database already had these things, nothing in it
changes, and no deploy is needed for this part:
* 92 columns gained server_default. The models carried Python-side
`default=` only, so the ORM filled the value and the column had no
database default. Anything inserting outside the ORM behaved
differently from production.
* Eleven indexes that existed only in migrations are now declared:
the three backup_run reporting indexes, the two date-ordered
image_record browse indexes, import_task and presentation_review,
and the three task_run history indexes. All use text() for their DESC
ordering and postgresql_where for the partial one.
* Two UNIQUE indexes that autogenerate silently proposed DROPPING,
because neither is expressible as a UniqueConstraint:
uq_tag_name_kind_fandom — an EXPRESSION index over
(name, kind, COALESCE(fandom_id, 0))
uq_post_artist_external_id_null_source — PARTIAL, WHERE source_id
IS NULL
post.py already had a comment describing the second one. The comment
was right; nothing declared it.
* The two external_link enum CHECKs (host, status) — rule 36 territory,
and absent from the model entirely.
* Two indexes were named explicitly. A bare index=True generated
ix_tag_alias_canonical_tag_id where the database has
ix_tag_alias_canonical, so autogenerate proposed a drop+create of an
index that was already there under another name. Same for
tag_suggestion_rejection.
Only ONE thing needed DDL, as 0088: tag.fandom_id is declared
index=True but no migration ever created that index.
Deliberately NOT here: image_record.sha256. The model says unique=True;
0001 created a plain index. Duplicates are possible today and the ORM
believes otherwise. The fix depends on whether duplicates already exist
— if they do, that is a dedupe decision, not a constraint — so it waits
on an answer about live data.
The real severity of #3275 is not the squash. It is that --autogenerate
has been unsafe on this project: run against the old models it would
have proposed dropping eleven indexes and two uniqueness guarantees.
46 lines
1.9 KiB
Python
46 lines
1.9 KiB
Python
"""HeadTrainingRun — persisted lifecycle of a head-training batch (#114).
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A persisted run row (not transient frontend state) so the run SURVIVES
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navigation and the admin card can show live + historical status.
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Training is idempotent (it upserts tag_head rows), so a SIGKILL'd run is harmless
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— a maintenance recovery sweep flips a stalled `running` row to `error`, and the
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next run re-trains. State machine: running → ready / error.
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"""
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from datetime import datetime
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from typing import Any
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from sqlalchemy import DateTime, Integer, String, Text, func
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from sqlalchemy.dialects.postgresql import JSONB
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from sqlalchemy.orm import Mapped, mapped_column
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from .base import Base
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class HeadTrainingRun(Base):
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__tablename__ = "head_training_run"
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id: Mapped[int] = mapped_column(Integer, primary_key=True)
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# Training parameters: {min_positives, neg_ratio, precision_target, ...}.
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params: Mapped[dict[str, Any]] = mapped_column(JSONB, nullable=False)
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status: Mapped[str] = mapped_column(
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String(16), nullable=False, default="running", index=True,
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server_default="running",
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)
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# running | ready | error
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started_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True), nullable=False, server_default=func.now()
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)
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finished_at: Mapped[datetime | None] = mapped_column(
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DateTime(timezone=True), nullable=True
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)
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# How many concepts got a (re)trained head vs were skipped (too few labels).
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n_trained: Mapped[int | None] = mapped_column(Integer, nullable=True)
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n_skipped: Mapped[int | None] = mapped_column(Integer, nullable=True)
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error: Mapped[str | None] = mapped_column(Text, nullable=True)
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# Last time the task made progress — the recovery sweep tells a live run
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# from a SIGKILL'd one by this.
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last_progress_at: Mapped[datetime | None] = mapped_column(
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DateTime(timezone=True), nullable=True
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)
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