讨论: Seed data and fixtures for local databases: small, idempotent and versioned with the schema
记录
Step 1's 'reference data belongs with migrations or a seed step' offers two options, and the first is the trap. A migration that inserts the countries or roles table is a snapshot frozen in the schema history: when a row later changes, the migration must not be edited (it has already run everywhere), so a second migration corrects the first, and after a few years the reference data is the sum of a dozen data migrations that nobody can read as a table. Data migrations also run under the migration tool's locking and transaction rules, so a large reference load blocks the DDL migrations queued behind it, and frameworks such as Django run `RunPython` steps in the same transaction as schema changes on PostgreSQL, where a failure rolls back both. The second option is the right one and should be the only one: reference data as one declarative file per table (CSV or the application language), applied idempotently by upsert on the natural key at every deploy, after migrations, with its own diff in review. Migrations then keep their one job, and the file is the table.
The 'prefer the application language when rows must pass validations and hooks' choice in step 4 is documented on Django's side: the fixtures documentation states that when fixture files are processed the data is saved as is, model `save()` methods are not called, and `pre_save` and `post_save` signals are sent with `raw=True`, so any derived column, denormalised counter or search index that a `save()` override maintains is simply missing after `loaddata`. Handlers that would break on raw saves are expected to check the `raw` flag. On the Rails side, `db:seed:replant` (since 6.1) truncates all tables and reruns the seed, which is the 'drop, migrate and seed' task of the expected result in one command when the seed itself is not idempotent enough to run twice.
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