feat(scheduler): a channel's "get full history" backfill is a recorded run, and a row knows its last three runs
The one-channel deep backfill ran as a FastAPI BackgroundTask: what it fetched, what it spent and how it failed reached only the log. It is now a one-shot run on the scheduler (`channel_backfill`, trigger ad_hoc, actor = the user, target = the channel) with its quota tagged to the run. Its per-channel exclusion with the scheduled backfill and the two-run cap are unchanged, and a run they turn away says why in its result instead of returning nothing. A failure is no longer swallowed: the run records it. The scheduler snapshot carries each job's last three runs (one windowed query), so the page can show an interrupted or skipped run instead of the latest outcome alone.
This commit is contained in:
+14
-4
@@ -82,14 +82,24 @@ def interrupt_leftovers() -> int:
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return res.rowcount if isinstance(res, CursorResult) else 0
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def last_runs(db: Session) -> dict[str, JobRun]:
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"""Each job's most recent run (any trigger), by job id."""
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def recent_runs(db: Session, per_job: int) -> dict[str, list[JobRun]]:
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"""Each job's last `per_job` runs, newest first, by job id — one query (a window per job)."""
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ranked = select(
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JobRun.id,
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func.row_number()
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.over(partition_by=JobRun.job, order_by=(JobRun.started_at.desc(), JobRun.id.desc()))
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.label("rank"),
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).subquery()
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rows = db.execute(
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select(JobRun)
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.distinct(JobRun.job)
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.join(ranked, ranked.c.id == JobRun.id)
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.where(ranked.c.rank <= per_job)
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.order_by(JobRun.job, JobRun.started_at.desc(), JobRun.id.desc())
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).scalars()
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return {r.job: r for r in rows}
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out: dict[str, list[JobRun]] = {}
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for r in rows:
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out.setdefault(r.job, []).append(r)
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return out
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def gc(db: Session, retention_days: int) -> int:
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@@ -3,15 +3,16 @@ hidden, tags) and per-channel sync state. Local reads/writes plus YouTube-side w
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(subscribe / unsubscribe) that require the optional write scope."""
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from datetime import datetime, timezone
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from functools import partial
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from fastapi import APIRouter, BackgroundTasks, Depends
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from fastapi import APIRouter, Depends
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from pydantic import BaseModel
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from sqlalchemy import Select, func, select, update
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from sqlalchemy.orm import Session
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from app.collation import collated, sorted_words
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from app.mailtext import lang_for_user
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from app import logs, quota
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from app import logs, quota, scheduler
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from app.auth import admin_user, current_user, require_write_scope
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from app.db import get_db
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from app.models import (
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@@ -481,7 +482,6 @@ class ChannelUpdateIn(BaseModel):
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def update_channel(
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channel_id: str,
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body: ChannelUpdateIn,
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background: BackgroundTasks,
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user: User = Depends(current_user),
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db: Session = Depends(get_db),
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) -> dict:
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@@ -508,12 +508,17 @@ def update_channel(
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with quota.attribute(user.id, quota.QuotaAction.VIDEOS_BACKFILL_RECENT):
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run_recent_backfill(db, [channel], max_channels=1)
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# …and kick the FULL deep backfill for this one channel immediately in the background, so the
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# whole catalogue lands in seconds instead of over the scheduler's paced 10-minute ticks. The
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# request returns right away; the channel page's live poll shows the count climb. The scheduler
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# still finishes a very large channel's tail on its normal runs (deep_requested stays set).
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# …and kick the FULL deep backfill for this one channel immediately, as a recorded run of its own,
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# so the whole catalogue lands in seconds instead of over the scheduler's paced 10-minute ticks.
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# The request returns right away; the channel page's live poll shows the count climb. The
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# scheduler still finishes a very large channel's tail on its normal runs (deep_requested stays set).
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if deep_turned_on:
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background.add_task(backfill_channel_now, channel_id, user.id)
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scheduler.run_ad_hoc(
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scheduler.CHANNEL_BACKFILL,
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partial(backfill_channel_now, channel_id, user.id),
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actor_id=user.id,
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target=channel_id,
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)
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return {
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"ok": True,
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+81
-13
@@ -174,26 +174,35 @@ def _run(db, name: str, fn, run_id: int, actor_id: int | None) -> None:
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return
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with progress.bind(sink):
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result = fn(db)
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summary = _summarize(result)
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data = _result_data(result)
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log.info("job %s -> %s", name, result)
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jobruns.finish(run_id, RunStatus.OK, summary=summary, result=data)
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summary, data = _finish_ok(name, run_id, result)
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if actor_id is not None:
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_notify_done(db, actor_id, name, "ok", summary, data)
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except Exception as exc:
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db.rollback()
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log.exception("job %s failed", name, extra=logs.event("scheduler.job.failed", job=name))
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err = str(exc) or exc.__class__.__name__
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# A failure the job named (progress.JobFailed) rides along as data, as a result does, so the
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# client says it in the reader's language; `err` stays the English line.
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failure = (
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{"failure": exc.reason, **exc.params} if isinstance(exc, progress.JobFailed) else None
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)
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jobruns.finish(run_id, RunStatus.ERROR, error=err, failure=failure)
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err, failure = _finish_error(run_id, exc)
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if actor_id is not None:
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_notify_done(db, actor_id, name, "error", err, failure)
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def _finish_ok(name: str, run_id: int, result) -> tuple[str | None, dict | None]:
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"""Close a run that returned: its result on the row, as data and as the English one-liner."""
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summary = _summarize(result)
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data = _result_data(result)
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log.info("job %s -> %s", name, result)
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jobruns.finish(run_id, RunStatus.OK, summary=summary, result=data)
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return summary, data
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def _finish_error(run_id: int, exc: Exception) -> tuple[str, dict | None]:
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"""Close a run that raised. A failure the job named (progress.JobFailed) rides along as data, as
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a result does, so the client says it in the reader's language; the error stays the English line."""
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err = str(exc) or exc.__class__.__name__
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failure = {"failure": exc.reason, **exc.params} if isinstance(exc, progress.JobFailed) else None
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jobruns.finish(run_id, RunStatus.ERROR, error=err, failure=failure)
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return err, failure
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# A skipped run's result, in the same shape as a job's own `{"skipped": …}`.
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_PAUSED = {"skipped": "sync paused"}
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@@ -240,11 +249,12 @@ def scheduler_snapshot(db) -> dict:
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live_intervals[job.id] = round(iv.total_seconds() / 60)
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with _activity_lock:
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acts = {k: dict(v) for k, v in _activity.items()}
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last = jobruns.last_runs(db)
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recent = jobruns.recent_runs(db, RECENT_RUNS)
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jobs = []
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for job_id, default_interval in JOB_INTERVALS.items():
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a = acts.get(job_id, {})
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run = last.get(job_id)
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runs = recent.get(job_id, [])
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run = runs[0] if runs else None
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# A run still going has no outcome yet: only an ended run says how it went.
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ended = run if run is not None and run.status != RunStatus.RUNNING else None
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jobs.append(
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@@ -264,11 +274,27 @@ def scheduler_snapshot(db) -> dict:
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"last_run_id": run.id if run else None,
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"quota_units": ended.quota_units if ended else None,
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"progress": a.get("progress"),
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# The last few runs, newest first, for the row's history dots.
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"recent": [_run_brief(r) for r in runs],
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}
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)
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return {"running_here": running_here, "enabled": settings.scheduler_enabled, "jobs": jobs}
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# How many past runs a Scheduler row shows as dots; the full history is the run list.
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RECENT_RUNS = 3
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def _run_brief(run) -> dict:
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return {
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"id": run.id,
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"status": run.status,
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"trigger": run.trigger,
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"started_at": _iso(run.started_at),
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"finished_at": _iso(run.finished_at),
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}
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def _outcome_data(run) -> dict | None:
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if run is None:
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return None
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@@ -509,6 +535,48 @@ def trigger_all(actor_id: int | None = None) -> list[str]:
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return started
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# Work a user starts on one target outside the job list — today the "get full history" backfill of
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# one channel. It runs on the same scheduler as a recorded run (trigger `ad_hoc`), so what it did and
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# spent is in `job_runs` like any job's, not a background task only the log ever heard of.
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CHANNEL_BACKFILL = "channel_backfill"
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def run_ad_hoc(job: str, fn: Callable[[], dict], *, actor_id: int, target: str) -> None:
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"""Run `fn` now as `actor_id`'s run of `job` on `target`, a one-shot job on the scheduler. Its
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own exclusion (if any) lives in `fn`, which says so in its result; one id per job and target, so
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a second request before the first has even started is that same run."""
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sched = _scheduler
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if sched is None:
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# Only between shutdown and exit: start_scheduler runs at every API startup.
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raise RuntimeError("the scheduler is not running")
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try:
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sched.add_job(
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_ad_hoc,
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"date",
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args=(job, fn, actor_id, target),
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id=f"{job}@{target}",
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misfire_grace_time=None,
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)
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# silent-ok: not a failure — the run for this target is already queued, and it does this work.
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except ConflictingIdError:
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log.info("ad-hoc %s for %s already queued", job, target)
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def _ad_hoc(job: str, fn: Callable[[], dict], actor_id: int, target: str) -> None:
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try:
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run_id = jobruns.start(job, RunTrigger.AD_HOC, actor_id, target)
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except Exception:
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# No row to tell it in: the database is what failed. The log is the record.
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log.exception("ad-hoc %s for %s not started: its run could not be recorded", job, target)
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return
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with logs.bind(run_id=run_id):
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try:
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_finish_ok(job, run_id, fn())
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except Exception as exc:
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log.exception("job %s failed", job, extra=logs.event("scheduler.job.failed", job=job))
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_finish_error(run_id, exc)
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# Room for every job at once (a "run all") beside a few ad-hoc runs: APScheduler's default pool of
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# 10 would queue a scheduled fire behind long manual runs.
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_POOL_SIZE = len(JOB_FUNCS) + 8
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+22
-21
@@ -437,7 +437,7 @@ def run_deep_backfill(db: Session, max_channels: int = 10, max_pages: int = 5) -
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# Channels being deep-backfilled RIGHT NOW by EITHER path — the interactive backfill_channel_now (a
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# FastAPI BackgroundTasks threadpool thread) OR the scheduler's run_deep_backfill (its own thread).
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# one-shot run on the scheduler's pool, see scheduler.run_ad_hoc) OR the scheduler's run_deep_backfill.
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# BOTH register the channel they're paging (under the lock) so the other skips it: no two runs page
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# the same channel's `backfill_cursor` concurrently, whichever started first. `_immediate_running`
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# counts only the interactive path, capped so one user's burst can't drain the shared budget (the
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@@ -448,9 +448,9 @@ _backfill_lock = threading.Lock()
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_MAX_CONCURRENT_IMMEDIATE = 2
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def backfill_channel_now(channel_id: str, user_id: int, max_pages: int = 400) -> None:
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"""User-initiated "get full history": deep-backfill ONE channel to completion right now, in a
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background task with its OWN session, so the full catalogue lands in seconds instead of over the
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def backfill_channel_now(channel_id: str, user_id: int, max_pages: int = 400) -> dict:
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"""User-initiated "get full history": deep-backfill ONE channel to completion right now, as its
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own recorded run with its OWN session, so the full catalogue lands in seconds instead of over the
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paced scheduler's 10-minute ticks (max_pages=5/channel/tick). max_pages is high enough to finish
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any realistic channel in a single run (400 pages = 20 000 videos; e.g. BBC Earth's ~3400 = 69
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pages — the old 60-page cap stopped one page short of large channels, so their tail dribbled in
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@@ -459,34 +459,35 @@ def backfill_channel_now(channel_id: str, user_id: int, max_pages: int = 400) ->
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Quota-guarded, capped to _MAX_CONCURRENT_IMMEDIATE interactive runs so one user can't drain the
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shared backfill budget by opting many channels in at once (the overflow, and any channel too large
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to finish under the reserve, is finished by the scheduler since deep_requested stays set), and
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mutually excluded per-channel with the scheduler via _backfill_in_progress. Best-effort — logs and
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swallows failures."""
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mutually excluded per-channel with the scheduler via _backfill_in_progress.
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Returns what the run did, as a job result: the counts, or `{"skipped": <why>}` when it left the
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channel to the scheduler. A failure raises — the run that wraps this records it."""
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global _immediate_running
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with _backfill_lock:
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if channel_id in _backfill_in_progress or _immediate_running >= _MAX_CONCURRENT_IMMEDIATE:
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return # already backfilling this channel, or too many interactive runs — leave it to the scheduler
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if channel_id in _backfill_in_progress:
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return {"skipped": "channel busy"}
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if _immediate_running >= _MAX_CONCURRENT_IMMEDIATE:
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return {"skipped": "at capacity"}
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_backfill_in_progress.add(channel_id)
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_immediate_running += 1
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try:
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with SessionLocal() as db:
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user = get_service_user(db)
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if user is None:
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return
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return {"skipped": "no service user"}
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channel = db.get(Channel, channel_id)
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if channel is None or channel.backfill_done or not channel.uploads_playlist_id:
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return
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return {"skipped": "nothing to do"}
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if quota.backfill_reserve_reached():
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return
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try:
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# Attribute the spend to the requesting user under the full-backfill action, so it
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# shows up correctly in the usage breakdown (not the default OTHER/system bucket).
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with quota.attribute(user_id, quota.QuotaAction.VIDEOS_BACKFILL_FULL):
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with YouTubeClient(db, user) as yt:
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backfill_channel_deep(db, yt, channel, max_pages)
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reconcile_full_history(db)
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except Exception:
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db.rollback()
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log.exception("Immediate backfill failed for channel %s", channel_id)
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return {"skipped": "low quota"}
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# Attribute the spend to the requesting user under the full-backfill action, so it
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# shows up correctly in the usage breakdown (not the default OTHER/system bucket).
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with quota.attribute(user_id, quota.QuotaAction.VIDEOS_BACKFILL_FULL):
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with YouTubeClient(db, user) as yt:
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added = backfill_channel_deep(db, yt, channel, max_pages)
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reconciled = reconcile_full_history(db)
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return {"videos_added": added, "reconciled_full": reconciled}
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finally:
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with _backfill_lock:
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_backfill_in_progress.discard(channel_id)
|
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|
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@@ -107,22 +107,32 @@ def _setup_channel_and_sub(db, *, email):
|
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|
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|
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def _patch_deep_requested(db, monkeypatch, override_dep, user):
|
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submitted: list[tuple] = []
|
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calls: list[tuple] = []
|
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# background.add_task runs after the response in TestClient; record what would be scheduled.
|
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# Record the run the route submits, and what its work would call, instead of running it.
|
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monkeypatch.setattr(
|
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channels_route.scheduler,
|
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"run_ad_hoc",
|
||||
lambda job, fn, **kw: submitted.append((job, kw)) or fn(),
|
||||
)
|
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monkeypatch.setattr(channels_route, "backfill_channel_now", lambda *a, **k: calls.append(a))
|
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monkeypatch.setattr(state, "_configured_cache", True)
|
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override_dep(get_db, db.info["request"])
|
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override_dep(current_user, lambda: user)
|
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resp = TestClient(app).patch("/api/channels/UC_wire", json={"deep_requested": True})
|
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return resp, calls
|
||||
return resp, submitted, calls
|
||||
|
||||
|
||||
def test_deep_request_schedules_immediate_backfill(db, monkeypatch, override_dep):
|
||||
def test_deep_request_starts_the_backfill_as_the_users_run_of_that_channel(
|
||||
db, monkeypatch, override_dep
|
||||
):
|
||||
"""It was a BackgroundTask: what it did, spent or failed with reached only the log."""
|
||||
ch, me = _setup_channel_and_sub(db, email="wire@example.com")
|
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resp, calls = _patch_deep_requested(db, monkeypatch, override_dep, me)
|
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resp, submitted, calls = _patch_deep_requested(db, monkeypatch, override_dep, me)
|
||||
assert resp.status_code == 200, resp.text
|
||||
assert resp.json()["deep_requested"] is True
|
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# scheduled exactly once, with (channel_id, user_id) — the args backfill_channel_now needs.
|
||||
assert submitted == [("channel_backfill", {"actor_id": me.id, "target": ch.id})]
|
||||
# its work runs exactly once, with (channel_id, user_id) — the args backfill_channel_now needs.
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assert calls == [(ch.id, me.id)]
|
||||
|
||||
|
||||
@@ -148,15 +158,49 @@ class TestImmediateBackfillGuard:
|
||||
def test_a_second_call_for_an_in_flight_channel_is_a_noop(self, monkeypatch):
|
||||
runner._backfill_in_progress.add("UC_busy")
|
||||
monkeypatch.setattr(runner, "SessionLocal", self._boom_session)
|
||||
runner.backfill_channel_now("UC_busy", 1) # returns immediately; _boom_session never runs
|
||||
# returns at once — _boom_session never runs — and the run says why it did nothing.
|
||||
assert runner.backfill_channel_now("UC_busy", 1) == {"skipped": "channel busy"}
|
||||
assert runner._backfill_in_progress == {"UC_busy"} # the in-flight entry is untouched
|
||||
|
||||
def test_over_the_concurrency_cap_falls_back_to_the_scheduler(self, monkeypatch):
|
||||
runner._immediate_running = runner._MAX_CONCURRENT_IMMEDIATE
|
||||
monkeypatch.setattr(runner, "SessionLocal", self._boom_session)
|
||||
runner.backfill_channel_now("UC_new", 1) # over the cap → no-op, scheduler will handle it
|
||||
# over the cap → no-op, the scheduler will handle it
|
||||
assert runner.backfill_channel_now("UC_new", 1) == {"skipped": "at capacity"}
|
||||
assert "UC_new" not in runner._backfill_in_progress
|
||||
|
||||
@staticmethod
|
||||
def _one_channel(db, monkeypatch, cid):
|
||||
ch = Channel(id=cid, title=cid, uploads_playlist_id="UU" + cid, backfill_done=False)
|
||||
me = User(email=f"{cid}@example.com")
|
||||
db.add_all([ch, me])
|
||||
db.commit()
|
||||
monkeypatch.setattr(runner, "get_service_user", lambda _db: me)
|
||||
monkeypatch.setattr(runner.quota, "backfill_reserve_reached", lambda: False)
|
||||
monkeypatch.setattr(runner, "YouTubeClient", lambda *a, **k: _NullYt())
|
||||
return ch, me
|
||||
|
||||
def test_a_failure_reaches_its_run_and_still_frees_the_channel(self, db, monkeypatch):
|
||||
"""The failure was logged and swallowed, so the run that now wraps it would read "ok"."""
|
||||
ch, me = self._one_channel(db, monkeypatch, "UC_fail")
|
||||
|
||||
def boom(*_a):
|
||||
raise RuntimeError("playlistItems 500")
|
||||
|
||||
monkeypatch.setattr(runner, "backfill_channel_deep", boom)
|
||||
with pytest.raises(RuntimeError, match="playlistItems 500"):
|
||||
runner.backfill_channel_now(ch.id, me.id)
|
||||
assert runner._backfill_in_progress == set() and runner._immediate_running == 0
|
||||
|
||||
def test_a_finished_backfill_says_what_it_added(self, db, monkeypatch):
|
||||
ch, me = self._one_channel(db, monkeypatch, "UC_ok")
|
||||
monkeypatch.setattr(runner, "backfill_channel_deep", lambda *_a: 7)
|
||||
monkeypatch.setattr(runner, "reconcile_full_history", lambda _db: 1)
|
||||
assert runner.backfill_channel_now(ch.id, me.id) == {
|
||||
"videos_added": 7,
|
||||
"reconciled_full": 1,
|
||||
}
|
||||
|
||||
def test_scheduler_deep_pass_skips_an_in_flight_channel(self, db, monkeypatch):
|
||||
# A channel the scheduler's query WOULD pick (deep-requested, recent-synced, not done)…
|
||||
ch = Channel(
|
||||
|
||||
@@ -146,6 +146,28 @@ def test_the_last_run_survives_a_restart(db):
|
||||
assert plex["last_finished"] is not None
|
||||
|
||||
|
||||
def test_a_row_shows_its_last_three_runs_newest_first_an_interrupted_one_included(db):
|
||||
"""The row said only how the LAST run went; an interrupted run read as "no run recorded"."""
|
||||
oldest = jobruns.start("shorts", RunTrigger.SCHEDULED, None)
|
||||
jobruns.interrupt_leftovers()
|
||||
scheduler._job("shorts", lambda _db: {"probed": 1})
|
||||
scheduler._job("shorts", lambda _db: {"probed": 2})
|
||||
scheduler._job("shorts", lambda _db: 1 / 0)
|
||||
scheduler._job("rss_poll", lambda _db: {"new": 0}) # another job's run stays on its own row
|
||||
|
||||
recent = _snapshot_job(db, "shorts")["recent"]
|
||||
assert [r["status"] for r in recent] == ["error", "ok", "ok"]
|
||||
assert oldest not in [r["id"] for r in recent] # the fourth-newest is not shown
|
||||
assert recent[0]["trigger"] == "scheduled" and recent[0]["finished_at"] is not None
|
||||
assert [r["status"] for r in _snapshot_job(db, "rss_poll")["recent"]] == ["ok"]
|
||||
|
||||
jobruns.start("shorts", RunTrigger.SCHEDULED, None)
|
||||
jobruns.interrupt_leftovers()
|
||||
shorts = _snapshot_job(db, "shorts")
|
||||
assert shorts["status"] == "interrupted"
|
||||
assert [r["status"] for r in shorts["recent"]] == ["interrupted", "error", "ok"]
|
||||
|
||||
|
||||
def test_a_paused_sync_is_a_skipped_run(db):
|
||||
state.set_sync_paused(db, True)
|
||||
db.commit()
|
||||
@@ -286,6 +308,51 @@ def test_run_now_goes_through_the_scheduler_even_with_interval_jobs_off(
|
||||
assert (run.trigger, run.actor_id, run.result) == ("manual", admin.id, {"probed": 3})
|
||||
|
||||
|
||||
def test_an_ad_hoc_run_is_the_users_run_of_its_target_with_its_spend_and_failure(
|
||||
db, make_user, live_scheduler
|
||||
):
|
||||
"""The one-channel deep backfill ran as a BackgroundTask nothing recorded: its spend counted as
|
||||
nobody's run and a failure lived only in the log."""
|
||||
user = make_user("adhoc@example.com")
|
||||
|
||||
def work():
|
||||
quota.record_usage(3)
|
||||
return {"videos_added": 50}
|
||||
|
||||
scheduler.run_ad_hoc(scheduler.CHANNEL_BACKFILL, work, actor_id=user.id, target="UC_a")
|
||||
run = _wait_finished(db, "channel_backfill")
|
||||
assert (run.trigger, run.actor_id, run.target) == ("ad_hoc", user.id, "UC_a")
|
||||
assert (run.status, run.result, run.quota_units) == ("ok", {"videos_added": 50}, 3)
|
||||
|
||||
def fail():
|
||||
raise RuntimeError("quota exceeded")
|
||||
|
||||
scheduler.run_ad_hoc(scheduler.CHANNEL_BACKFILL, fail, actor_id=user.id, target="UC_b")
|
||||
deadline = time.monotonic() + 10
|
||||
while time.monotonic() < deadline and len(_finished(db, "channel_backfill")) < 2:
|
||||
time.sleep(0.05)
|
||||
failed = next(r for r in _runs(db, "channel_backfill") if r.target == "UC_b")
|
||||
assert (failed.status, failed.error) == ("error", "quota exceeded")
|
||||
|
||||
|
||||
def _finished(db, job) -> list[JobRun]:
|
||||
return [r for r in _runs(db, job) if r.status != "running"]
|
||||
|
||||
|
||||
def test_a_second_ad_hoc_request_before_the_first_starts_is_that_same_run(
|
||||
db, make_user, live_scheduler
|
||||
):
|
||||
user = make_user("twice@example.com")
|
||||
live_scheduler.pause() # hold the one-shots so the second request finds the first pending
|
||||
for target in ("UC_x", "UC_x", "UC_y"):
|
||||
scheduler.run_ad_hoc(scheduler.CHANNEL_BACKFILL, dict, actor_id=user.id, target=target)
|
||||
assert sorted(j.id for j in live_scheduler.get_jobs()) == [
|
||||
"channel_backfill@UC_x",
|
||||
"channel_backfill@UC_y",
|
||||
]
|
||||
live_scheduler.remove_all_jobs() # never run: a run finishing after the test would land in the next
|
||||
|
||||
|
||||
def test_a_manual_run_leaves_no_actor_behind_on_its_thread(db, make_user):
|
||||
"""The scheduler's pool threads are reused: an actor a manual run left set made the next
|
||||
scheduled run on that thread an admin's "manual" run, with a notice in their inbox."""
|
||||
|
||||
Reference in New Issue
Block a user