Files
chitai/backend/migrations/versions/2026-08-15_canonicalize_author_names_49a9e85a0ffc.py
patrick ff75f2c758 chore: clear the lint in the files this branch touches
Unused imports, duplicated import lines, and bare excepts that swallowed
KeyboardInterrupt along with everything else.
2026-08-15 22:01:04 -04:00

131 lines
4.7 KiB
Python

"""canonicalize author names
Revision ID: 49a9e85a0ffc
Revises: ed41acf21270
Create Date: 2026-08-15 15:59:47.331545
"""
import warnings
import sqlalchemy as sa
from alembic import op
from advanced_alchemy.types import EncryptedString, EncryptedText, GUID, ORA_JSONB, DateTimeUTC, StoredObject, PasswordHash, FernetBackend
from advanced_alchemy.types.encrypted_string import PGCryptoBackend
from advanced_alchemy.types.password_hash.argon2 import Argon2Hasher
from advanced_alchemy.types.password_hash.passlib import PasslibHasher
from advanced_alchemy.types.password_hash.pwdlib import PwdlibHasher
from sqlalchemy import Text # noqa: F401
__all__ = ["downgrade", "upgrade", "schema_upgrades", "schema_downgrades", "data_upgrades", "data_downgrades"]
sa.GUID = GUID
sa.DateTimeUTC = DateTimeUTC
sa.ORA_JSONB = ORA_JSONB
sa.EncryptedString = EncryptedString
sa.EncryptedText = EncryptedText
sa.StoredObject = StoredObject
sa.PasswordHash = PasswordHash
sa.Argon2Hasher = Argon2Hasher
sa.PasslibHasher = PasslibHasher
sa.PwdlibHasher = PwdlibHasher
sa.FernetBackend = FernetBackend
sa.PGCryptoBackend = PGCryptoBackend
# revision identifiers, used by Alembic.
revision = '49a9e85a0ffc'
down_revision = 'ed41acf21270'
branch_labels = None
depends_on = None
def upgrade() -> None:
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=UserWarning)
with op.get_context().autocommit_block():
schema_upgrades()
data_upgrades()
def downgrade() -> None:
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=UserWarning)
with op.get_context().autocommit_block():
data_downgrades()
schema_downgrades()
def schema_upgrades() -> None:
"""schema upgrade migrations go here."""
pass
def schema_downgrades() -> None:
"""schema downgrade migrations go here."""
pass
def data_upgrades() -> None:
"""
Rewrite every author into the canonical form, merging the rows that collide.
`Author.name` is only now guaranteed tidy — until this revision extractors wrote
whatever the file said, so one person could hold several rows: "Sam Newman" beside
"Newman, Sam;" beside "Sam Newman.epub" (the last from a filename whose extension
was never stripped). Each showed up as its own author in the sidebar and its own
filter, and no amount of fixing the extractors repairs a row already written.
Rows that canonicalize onto one name are merged into the lowest id, which keeps
whichever row the library has been referring to longest. `book.path` is stored, not
derived, so renaming an author moves nothing on disk.
"""
from chitai.services.matching import format_author_name, normalize_author
connection = op.get_bind()
authors = connection.execute(sa.text("SELECT id, name FROM authors")).fetchall()
groups: dict[str, list[int]] = {}
for id, name in sorted(authors):
# A name with nothing left of it after tidying is left exactly as it was:
# merging those together would invent one author out of several unrelated
# broken rows, which is worse than leaving the mess visible.
if canonical := format_author_name(name):
groups.setdefault(canonical, []).append(id)
for canonical, ids in groups.items():
winner, losers = ids[0], ids[1:]
for loser in losers:
# A book credited to both rows would otherwise breach the
# (book_id, author_id) unique constraint the moment the link is repointed.
connection.execute(
sa.text(
"DELETE FROM book_author_links WHERE author_id = :loser AND book_id IN"
" (SELECT book_id FROM book_author_links WHERE author_id = :winner)"
),
{"loser": loser, "winner": winner},
)
connection.execute(
sa.text(
"UPDATE book_author_links SET author_id = :winner"
" WHERE author_id = :loser"
),
{"loser": loser, "winner": winner},
)
connection.execute(
sa.text("DELETE FROM authors WHERE id = :loser"), {"loser": loser}
)
# Only after the losers are gone, or this collides with the unique index.
connection.execute(
sa.text(
"UPDATE authors SET name = :name, normalized_name = :key WHERE id = :id"
),
{"id": winner, "name": canonical, "key": normalize_author(canonical)},
)
def data_downgrades() -> None:
"""
Nothing to undo.
The rows a merge removed are gone, and the spellings it replaced were never
recorded anywhere else — there is nothing to restore them from.
"""