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Aurora-Core/app/services/ingestion/runner.py
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NixReaperandClaude Sonnet 5 3f6332559a
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Add series/season/episode ingestion pipeline
Movie and person ingestion existed, but the series/season/episode API
endpoints had no way to actually populate them from TMDb -- the
biggest remaining gap in Core 0.1's television scope.

- normalize_series/normalize_season in the metadata normalizer,
  including two TMDb quirks that would otherwise silently produce
  empty data: /tv nests keywords and alternative_titles under
  "results" (not "keywords"/"titles" like /movie), and series-level
  creators come from a separate created_by array, not the credits
  cast/crew lists.
- ingest_series upserts the Series row plus season *stubs* (number,
  title, air date, poster -- everything TMDb inlines on /tv/{id});
  ingest_season fetches and upserts one season's full episode list,
  and requires the series to already exist (TMDb has no single
  endpoint for a whole series' episodes, so this has to be a separate
  per-season call).
- Wired through the same job-lifecycle path as movie/person ingestion
  (runner.py, arq tasks, admin endpoints), with the shared boilerplate
  between them factored into runner._run_ingestion and
  admin.py:_enqueue rather than copy-pasted a third and fourth time.
- Unit tests for both normalizers (runnable without a DB) and
  integration tests for the full ingest_series -> ingest_season flow,
  including the series-must-exist-first error and idempotency on
  re-ingestion.

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-09-04 19:43:56 -05:00

141 lines
4.9 KiB
Python

"""Orchestrates one ingestion job end-to-end: create/track the `IngestionJob`
row, run the provider fetch + normalize + upsert pipeline, and record
success/failure. Used by both the admin trigger endpoint (section 17) and
the arq worker task (section 15) so every entry point shares identical
job-lifecycle and idempotency behavior.
"""
from __future__ import annotations
import uuid
from collections.abc import Awaitable, Callable
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.database import session_scope
from app.core.logging import get_logger
from app.models.provider import IngestionJob
from app.providers.base import MetadataProvider
from app.providers.tmdb import TMDbProvider
from app.repositories.provider_repository import (
create_ingestion_job,
get_ingestion_job,
get_or_create_provider,
mark_job_failed,
mark_job_running,
mark_job_succeeded,
)
from app.services.ingestion.movie_ingestion import ingest_movie
from app.services.ingestion.person_ingestion import ingest_person
from app.services.ingestion.series_ingestion import ingest_season, ingest_series
logger = get_logger(__name__)
async def _require_job(session: AsyncSession, job_id: uuid.UUID) -> IngestionJob:
job = await get_ingestion_job(session, job_id)
if job is None:
# Only possible if the row was deleted out-of-band; the job was
# created moments earlier in this same call chain.
raise RuntimeError(f"ingestion job {job_id} vanished mid-run")
return job
async def get_or_create_ingestion_job(job_type: str, entity_type: str, external_id: str) -> uuid.UUID:
"""Create the DB-tracked `IngestionJob` row (or return the existing one
for this provider+entity+external_id, keyed by `idempotency_key`)
without running the pipeline.
Called synchronously from the admin endpoint, *before* enqueuing to arq,
specifically so the HTTP response can return a `job_id` that
`GET /admin/ingest/jobs/{job_id}` can immediately resolve — arq's own
queue-internal job id is a different, unrelated identifier and was
never valid here.
"""
idempotency_key = f"tmdb:{entity_type}:{external_id}"
async with session_scope() as session:
provider_row = await get_or_create_provider(session, "tmdb", "The Movie Database (TMDb)")
job = await create_ingestion_job(
session,
provider_id=provider_row.id,
job_type=job_type,
idempotency_key=idempotency_key,
entity_type=entity_type,
external_id=external_id,
)
return job.id
async def _run_ingestion(
job_id: uuid.UUID,
label: str,
work: Callable[[AsyncSession, MetadataProvider], Awaitable[uuid.UUID]],
) -> uuid.UUID:
"""Shared job-lifecycle wrapper: mark running, run `work` in its own
session/transaction, mark succeeded/failed. `work` does the actual
fetch+normalize+upsert and returns the resulting Aurora entity id."""
async with session_scope() as session:
job = await _require_job(session, job_id)
await mark_job_running(session, job)
provider = TMDbProvider()
try:
async with session_scope() as session:
result_id = await work(session, provider)
async with session_scope() as session:
job = await _require_job(session, job_id)
await mark_job_succeeded(session, job, result_id)
return result_id
except Exception as exc:
logger.error(f"{label}_failed", job_id=str(job_id), error=str(exc))
async with session_scope() as session:
job = await _require_job(session, job_id)
await mark_job_failed(session, job, str(exc))
raise
finally:
await provider.aclose()
async def run_movie_ingestion(job_id: uuid.UUID, external_id: str) -> uuid.UUID:
return await _run_ingestion(
job_id,
"movie_ingestion",
lambda session, provider: ingest_movie(
session, provider, external_id, ingestion_job_id=job_id
),
)
async def run_person_ingestion(job_id: uuid.UUID, external_id: str) -> uuid.UUID:
return await _run_ingestion(
job_id,
"person_ingestion",
lambda session, provider: ingest_person(
session, provider, external_id, ingestion_job_id=job_id
),
)
async def run_series_ingestion(job_id: uuid.UUID, external_id: str) -> uuid.UUID:
return await _run_ingestion(
job_id,
"series_ingestion",
lambda session, provider: ingest_series(
session, provider, external_id, ingestion_job_id=job_id
),
)
async def run_season_ingestion(
job_id: uuid.UUID, series_external_id: str, season_number: int
) -> uuid.UUID:
return await _run_ingestion(
job_id,
"season_ingestion",
lambda session, provider: ingest_season(
session, provider, series_external_id, season_number, ingestion_job_id=job_id
),
)