refac: file table migration
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"""Update file table path
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Revision ID: c29facfe716b
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Revises: c69f45358db4
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Create Date: 2024-10-20 17:02:35.241684
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"""
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from alembic import op
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import sqlalchemy as sa
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import json
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from sqlalchemy.sql import table, column
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from sqlalchemy import String, Text, JSON, and_
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revision = "c29facfe716b"
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down_revision = "c69f45358db4"
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branch_labels = None
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depends_on = None
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def upgrade():
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# 1. Add the `path` column to the "file" table.
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op.add_column("file", sa.Column("path", sa.Text(), nullable=True))
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# 2. Convert the `meta` column from Text/JSONField to `JSON()`
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# Use Alembic's default batch_op for dialect compatibility.
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with op.batch_alter_table("file", schema=None) as batch_op:
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batch_op.alter_column(
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"meta",
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type_=sa.JSON(),
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existing_type=sa.Text(),
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existing_nullable=True,
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nullable=True,
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postgresql_using="meta::json",
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)
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# 3. Migrate legacy data from `meta` JSONField
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# Fetch and process `meta` data from the table, add values to the new `path` column as necessary.
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# We will use SQLAlchemy core bindings to ensure safety across different databases.
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file_table = table(
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"file", column("id", String), column("meta", JSON), column("path", Text)
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)
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# Create connection to the database
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connection = op.get_bind()
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# Get the rows where `meta` has a path and `path` column is null (new column)
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# Loop through each row in the result set to update the path
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results = connection.execute(
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sa.select(file_table.c.id, file_table.c.meta).where(
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and_(file_table.c.path.is_(None), file_table.c.meta.isnot(None))
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)
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).fetchall()
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# Iterate over each row to extract and update the `path` from `meta` column
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for row in results:
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if "path" in row.meta:
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# Extract the `path` field from the `meta` JSON
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path = row.meta.get("path")
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# Update the `file` table with the new `path` value
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connection.execute(
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file_table.update()
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.where(file_table.c.id == row.id)
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.values({"path": path})
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)
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def downgrade():
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# 1. Remove the `path` column
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op.drop_column("file", "path")
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# 2. Revert the `meta` column back to Text/JSONField
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with op.batch_alter_table("file", schema=None) as batch_op:
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batch_op.alter_column(
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"meta", type_=sa.Text(), existing_type=sa.JSON(), existing_nullable=True
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)
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