Making long running operations asynchronous
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"""Lightweight in-process tracking for long-running admin operations.
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Jobs live in a module-level dict, so this only works correctly for a single
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OS process (the app's current deployment: one uvicorn worker, no multi-process
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or multi-replica setup — see ``entrypoint.sh`` / ``docker-compose.yml``). If
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the app is ever scaled to multiple workers/replicas, this needs to move to
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shared storage (a DB table, Redis) so a poll request landing on a different
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process can still see the job.
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"""
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from __future__ import annotations
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import asyncio
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import uuid
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from collections.abc import Awaitable, Callable
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from dataclasses import dataclass, field
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from datetime import UTC, datetime
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_MAX_FINISHED_AGE_SECONDS = 3600
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@dataclass
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class Job:
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id: str
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kind: str
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status: str = "running" # running | done | error
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message: str = "Working…"
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result: object | None = None
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created_at: datetime = field(default_factory=lambda: datetime.now(UTC))
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finished_at: datetime | None = None
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_jobs: dict[str, Job] = {}
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def get(job_id: str) -> Job | None:
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return _jobs.get(job_id)
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def _evict_stale() -> None:
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now = datetime.now(UTC)
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stale = [
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job_id
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for job_id, job in _jobs.items()
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if job.finished_at
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and (now - job.finished_at).total_seconds() > _MAX_FINISHED_AGE_SECONDS
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]
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for job_id in stale:
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del _jobs[job_id]
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def start(kind: str, run: Callable[[Job], Awaitable[None]]) -> Job:
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"""Create a job, launch ``run(job)`` in the background, and return it immediately.
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``run`` is responsible for updating ``job.status``/``job.message``/``job.result``
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to reflect the outcome, including catching its own errors. Any exception that
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escapes anyway is caught here as a last resort so the job doesn't hang forever
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in "running" state.
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"""
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_evict_stale()
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job = Job(id=uuid.uuid4().hex, kind=kind)
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_jobs[job.id] = job
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async def _runner() -> None:
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try:
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await run(job)
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except Exception as exc:
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job.status = "error"
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job.message = f"{kind} failed: {exc}"
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finally:
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job.finished_at = datetime.now(UTC)
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asyncio.create_task(_runner())
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return job
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