simple_module_background_tasks
Celery + Redis background-task module for simple_module apps. Provides a pre-configured Celery instance, a task registration hook, and an admin UI for monitoring + retrying failed/stuck tasks.
Install
pip install simple_module_background_tasks
Requires a Redis broker. The broker / result-backend URLs are module settings (broker_url, default redis://localhost:6379/0; result_backend, default redis://localhost:6379/1) configured from the DB settings store via the admin UI — they are not read from environment variables at runtime. These fields are requires_restart (changing them needs a worker/web restart).
What it provides
- Zero-config task discovery — any installed module that ships a
tasks.pyhas its tasks autodiscovered (celery.autodiscover_tasksimports<package>.tasksfor every installed module). No per-module registration hook. - Admin UI at
/admin/background-tasks— list recent runs, retry failed, inspect tracebacks (gated by thebackground_tasks.viewpermission). build_celery(settings)factory inbackground_tasks.celery_app, plusbind_task_context/get_log_context/install_log_filterexported from the package root (import namebackground_tasks, distribution namesimple_module_background_tasks).enqueue_after_commit(db, task, *args, **kwargs)— publish a task only once the session's transaction commits, never on rollback.heartbeat()— called from a long task body, keeps the stuck sweep from flagging it;@shared_task(stuck_after=seconds)sets a per-task stuck threshold. See the module docs for both.
Usage
Declare a task in a module's tasks.py with Celery's @shared_task — it's autodiscovered, no registration hook needed:
# modules/reports/reports/tasks.py
from celery import shared_task
@shared_task(name="reports.generate")
def generate_report(report_id: int) -> None: ...
Declaring background_tasks as a depends_on ensures the Celery app is built before your tasks run:
class ReportsModule(ModuleBase):
meta = ModuleMeta(name="reports", depends_on=["background_tasks"])
Enqueue from an endpoint:
generate_report.delay(report_id=42)
Run a worker locally (the scaffolded host ships a scripts/run_worker.py that builds the app via build_celery):
uv run celery -A scripts.run_worker:celery worker -l info
uv run celery -A scripts.run_worker:celery beat -l info
Routing, tuning and per-worker module subsets
A module can ship a light task_config.py (TASK_ROUTES, QUEUES, optional
BEAT_SCHEDULE) that is read without importing tasks.py. The
task_routes_override setting re-routes tasks at runtime, and the Workers page
lists the effective routes. Tuning settings (visibility_timeout_seconds,
worker_max_tasks_per_child, task_time_limit, worker_concurrency, ...) and a
raw SM_BG_TASKS_CELERY_OVERRIDES (env only, unsafe keys refused) default to Celery's own defaults.
SM_BG_TASKS_WORKER_QUEUES=gpu,default make worker consumes only those queues
and imports only the modules whose QUEUES overlap (see SM_BG_TASKS_INCLUDE_MODULES /
SM_BG_TASKS_EXCLUDE_MODULES; env only, not DB settings). Full details in docs/modules/background_tasks.md.
Durable events
This module is the transport behind bus.publish_durable(event, db): the event
is written to an outbox table in the caller's transaction and delivered by a
worker to every bus.subscribe_durable(...) handler, at least once, with
backoff, after the commit. Writes a handler makes through ctx.db land exactly
once. Undelivered and dead rows are on /admin/background-tasks/outbox. Full
details in docs/modules/background_tasks.md § Durable events.
Worker log context
Every worker log line automatically carries the Celery task identifiers
that fired it. A LogContextFilter is attached when the Celery app is
built (build_celery) and the task_prerun / task_postrun signals
bind task_id + task_name into contextvars for the task's duration:
{"level": "INFO", "logger": "reports.tasks", "message": "ingest done",
"task_id": "9c2a…", "task_name": "reports.generate"}
Use bind_task_context(...) to attach app-level identifiers (the
domain job_id that named a Celery task is the canonical example):
from background_tasks import bind_task_context
from celery import shared_task
@shared_task
def process_dataset(job_id: int) -> None:
with bind_task_context(job_id=job_id):
logger.info("starting ingest") # now carries job_id too
Bindings nest cleanly and restore on exit. structlog users can mount the
same contextvars directly via structlog.contextvars.merge_contextvars.
Depends on
simple_module_core,simple_module_db,simple_module_hosting,simple_module_settingscelery[redis]>=5.4,redis>=5
License
MIT — see LICENSE.
1 maintainer
Metadata
1 maintainer
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