vintasoftware/django-ai-plugins

django-celery-expert

Expert Django Celery guidance for asynchronous task processing. Use when designing background tasks, configuring Celery workers, handling task retries and errors, optimizing Celery performance, implementing periodic tasks with Celery Beat, or setting up production monitoring for Celery. Do not use for general Django questions unrelated to Celery, non-Celery task systems (Django Q, Huey, RQ), ML/data pipeline orchestration (Airflow, Prefect), or frontend and API-only concerns. Follows Vinta's Dj…

Trending #8393 First seen Jan 21, 2026

Installation

$ npx skills add vintasoftware/django-ai-plugins --skill django-celery-expert

Summary

  • Expert Django Celery guidance for asynchronous task processing.
  • Use when designing background tasks, configuring Celery workers, handling task retries and errors, optimizing Celery performance, implementing periodic tasks with Celery Beat, or setting up production monitoring for Celery.
  • Do not use for general Django questions unrelated to Celery, non-Celery task systems (Django Q, Huey, RQ), ML/data pipeline orchestration (Airflow, Prefect), or frontend and API-only concerns.
  • Follows Vinta's Django Celery best practices.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 137
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,656 B
  • docs SUMMARY.md 3,738 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 980 installs

SKILL.md

Django Celery Expert

Instructions

Step 1: Classify the Request

Identify the task category from the request:

  • Django integration — transaction safety, ORM patterns, testing, request correlation → read references/django-integration.md
  • Task design — new tasks, calling patterns, chains/groups/chords, idempotency → read references/task-design-patterns.md
  • Configuration — broker setup, result backend, worker settings, queue routing → read references/configuration-guide.md
  • Error handling — retries, backoff, dead letter queues, timeouts → read references/error-handling.md
  • Periodic tasks — Celery Beat, crontab schedules, dynamic schedules, timezone handling → read references/periodic-tasks.md
  • Monitoring — Flower, Prometheus, logging, debugging stuck tasks → read references/monitoring-observability.md
  • Production deployment — scaling, supervision, containers, health checks → read references/production-deployment.md

If the request spans multiple categories, read all relevant reference files before continuing.

Step 2: Read the Reference File(s)

Read each reference file identified in Step 1. Do not proceed to implementation without reading the relevant reference.

Step 3: Implement

Apply the patterns from the reference file. Before presenting the solution, verify:

  • Task arguments are serializable (pass IDs, not model instances)
  • Tasks with retries enabled are idempotent
  • Errors are logged with context
  • Long-running tasks have timeouts configured

Examples

Basic Background Task

Request: "Send welcome emails in the background after user registration"

# tasks.py
from celery import shared_task
from django.core.mail import send_mail

@shared_task(bind=True, max_retries=3)
def send_welcome_email(self, user_id):
    from users.models import User

    try:
        user = User.objects.get(id=user_id)
        send_mail(
            subject="Welcome!",
            message=f"Hi {user.name}, welcome to our platform!",
            from_email="[email protected]",
            recipient_list=[user.email],
        )
    except User.DoesNotExist:
        pass
    except Exception as exc:
        raise self.retry(exc=exc, countdown=60 * (2 ** self.request.retries))


# views.py — queue only after the transaction commits
from django.db import transaction

def register(request):
    user = User.objects.create(...)
    transaction.on_commit(lambda: send_welcome_email.delay(user.id))
    return redirect("dashboard")

Task with Progress Tracking

Request: "Process a large CSV import with progress updates"

@shared_task(bind=True)
def import_csv(self, file_path, total_rows):
    from myapp.models import Record

    with open(file_path) as f:
        reader = csv.DictReader(f)
        for i, row in enumerate(reader):
            Record.objects.create(**row)
            if i % 100 == 0:
                self.update_state(
                    state="PROGRESS",
                    meta={"current": i, "total": total_rows},
                )

    return {"status": "complete", "processed": total_rows}


# Poll progress
result = import_csv.AsyncResult(task_id)
if result.state == "PROGRESS":
    progress = result.info.get("current", 0) / result.info.get("total", 1)

Workflow with Chains

Request: "Process an order: validate inventory, charge payment, then send confirmation"

from celery import chain

@shared_task
def validate_inventory(order_id):
    order = Order.objects.get(id=order_id)
    if not order.items_in_stock():
        raise ValueError("Items out of stock")
    return order_id

@shared_task
def charge_payment(order_id):
    order = Order.objects.get(id=order_id)
    order.charge()
    return order_id

@shared_task
def send_confirmation(order_id):
    Order.objects.get(id=order_id).send_confirmation_email()

def process_order(order_id):
    chain(
        validate_inventory.s(order_id),
        charge_payment.s(),
        send_confirmation.s(),
    ).delay()