# Aurora Core — Database PostgreSQL is authoritative (principle 4). Nothing important lives only in Redis. See [erd.md](erd.md) for the full entity-relationship diagram. ## Aurora IDs vs. primary keys Every table's primary key is a UUIDv7 (`app/models/base.py:UUIDPrimaryKeyMixin`), generated in the application, not the database. UUIDv7 is time-ordered, so it stays btree-friendly (unlike UUIDv4) and can double as a rough creation-order cursor. The public "Aurora ID" strings clients see (`aur_movie_01m1q7p1c...`) are a lossless, sortable Crockford-base32 encoding of that same UUID, produced by `app/core/ids.py:aurora_id()`. Encoding (not a second stored column) keeps the public ID and the primary key from ever drifting apart. See section 3 of `docs/aurora-core-spec.md` for why Aurora never uses a provider's ID (TMDb, IMDb, ...) as a primary key. ## Reference data - `languages` (ISO 639-1), `countries` (ISO 3166-1 alpha-2), `certifications` (country + rating system + rating, e.g. US/MPA/PG-13) — populated incrementally as ingestion encounters new codes (`get_or_create_*` in `app/repositories/reference_repository.py`), not preloaded. A curated seed list is a reasonable follow-up (see Known limitations). - `genres`, `keywords` — deduplicated by a slugified name. Two providers' "Sci-Fi" and "Science Fiction" are **not** currently merged; that requires a curated synonym table, deliberately deferred (section 33 lists dedup *foundations*, not a finished thesaurus). ## Movies / TV `movies` and `series` hold the record itself; per-locale and per-relationship data lives in satellite tables (`movie_alternate_titles`, `movie_spoken_languages`, `movie_production_countries`, `release_dates`, `movie_recommendations`, and the `series_*` equivalents) rather than JSON blobs, per section 26. `seasons` and `episodes` form a strict `series -> season -> episode` hierarchy; `episodes.series_id` is denormalized (in addition to `season_id`) purely so episode queries don't need to hop through `seasons` to filter/join by series. `movies.status` / `series.status` are native Postgres enums, values `.value` of `app/models/enums.py:MovieStatus`/`SeriesStatus` — see "Enum storage" below. ## Credits `credits` is the flexible cast/crew system from section 7: one row per (person, media entity, department/job/character), not per-movie text blobs. `department == "Acting"` rows carry `character`/`billing_order`; everything else carries `job`. Series-level "Creator" credits and episode `is_guest` (guest stars) reuse the same table rather than adding new ones. ## Companies / Collections A single `companies` table serves production companies, studios, networks, and distributors, distinguished by `company_type` (section 8) — a TV network and a movie studio have the same shape (name, logo, country, parent company), so a separate `Network` entity would just duplicate columns. `collections` (franchises) are first-class, with their own artwork and `collection_relations` for shared-universe links between collections (section 9). ## Artwork / Videos Never a `poster_url` column (section 10/11). `artwork` and `videos` are their own tables carrying provider, provider-native asset ID, dimensions, and (for artwork) `attribution`/`license` fields — Aurora doesn't assume externally-sourced images can be freely redistributed. Aurora never downloads video media; `videos.url` is a reference to the provider's hosted copy (YouTube, Vimeo, ...). ## Polymorphic associations `credits`, `artwork`, `videos`, `external_ids`, and `release_dates` attach to more than one entity type via an `(entity_type, entity_id)` pair instead of a typed foreign key, because a single column can't reference "movies.id or series.id or people.id depending on a sibling column" in Postgres. The tradeoff: **the schema does not enforce that `entity_id` actually points at a real row of `entity_type`.** That integrity is enforced by the repository/service layer (`app/repositories/polymorphic.py`, `app/services/ingestion/*`), which is the only code path allowed to write these tables. If Core grows enough that this becomes a real risk, the standard fix is per-type junction tables (`movie_credits`, `series_credits`, ...) at the cost of losing the single shared query path — deliberately not done for 0.1. ## External IDs & provenance `external_ids` is the generalized external-identifier system (section 12): `(provider, entity_type, external_id)` is unique (one Aurora entity per provider-native ID), and `(entity_type, entity_id, provider)` is unique (one mapping per provider per entity). `provider_records` is the full provenance ledger (section 14): one row per `(provider, entity_type, external_id)` holding the raw payload (`raw_data` JSONB), `match_confidence`, and which `ingestion_job` produced it. Entity-level provenance is coarse — `movies.source_provider_id` / `series.source_provider_id` point at "the provider that was authoritative at creation time" for quick display; full field-level provenance (which provider supplied *this specific* field) is not tracked in 0.1. See Known limitations. `ingestion_jobs` tracks async work with a unique `idempotency_key` (e.g. `tmdb:movie:603`) so re-triggering the same sync doesn't double-enqueue — see `app/services/ingestion/runner.py`. ## Enum storage Python enums in `app/models/enums.py` are `enum.StrEnum` (member value == member name's meaning, e.g. `MovieStatus.RELEASED == "released"`). SQLAlchemy's `Enum` type stores `.name` (`"RELEASED"`) by default, which would silently diverge from the lowercase strings the API and ingestion code use everywhere. `app/models/base.py:_enum_column()` overrides this via `values_callable` so the database, the ORM, and the API all agree on the same lowercase strings. ## Migrations Alembic (section 27); the application **never** creates tables at startup — see `app/core/database.py`. The initial migration (`migrations/versions/0001_initial_schema.py`) is hand-written rather than autogenerated (no throwaway Postgres was available in the environment this was built in — see the root README's Known Limitations), but was written directly from the same models this document describes and validated with `alembic history`; treat a first `alembic upgrade head` against a scratch database as the real acceptance test, and autogenerate future migrations against it (`alembic revision --autogenerate`) rather than the empty database this one was written from. ```bash alembic upgrade head # apply all migrations alembic revision --autogenerate -m "add xyz" # generate the next one alembic downgrade -1 # roll back one revision ``` Integration/API tests build schema directly from `Base.metadata.create_all` (see `tests/conftest.py`) for speed and to catch model drift quickly — this is a testing shortcut, not how the running application ever gets its schema. ## Search indexes `pg_trgm` (trigram similarity, for typo-tolerant matching) plus functional GIN indexes over `to_tsvector('simple', title || ' ' || original_title)` on `movies`/`series`, `name` on `people`/`collections`/`companies`, and trigram indexes on the alternate-title tables. See `app/services/search/postgresql_provider.py` and section 16 of the spec. ## Known limitations (tracked, not hidden) - No curated language/country seed data — rows are created on first encounter during ingestion, so `english_name`/`name` are sometimes just the code uppercased until backfilled. - No fuzzy/candidate entity matching — only exact external-ID matches are auto-linked (section 14: never silently merge ambiguous matches). A review queue for AMBIGUOUS matches is the natural next step once Core has an admin UI to act on it. - Field-level provenance (which provider supplied *this* value) is not tracked, only entity-level (`source_provider_id`) and per-provider raw payloads (`provider_records.raw_data`). - Satellite associations (credits, artwork, videos, genre/keyword/company links) are replaced wholesale on each re-sync rather than diffed, so their Aurora IDs are not stable across re-ingestion — see `app/services/ingestion/movie_ingestion.py`.