Background Tasks and Job Queues
Learn to offload slow work from request handlers using FastAPI background tasks and distributed job queues like Celery.
Background Tasks and Job Queues is a free FastAPI Backend Development Bootcamp lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the FastAPI Backend Development Bootcamp learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Why Offload Work?
Some work, like sending email, generating reports, or processing images, is too slow to do inside a request.
Making the user wait hurts latency. Instead, respond fast and do the heavy work in the background.
FastAPI BackgroundTasks
FastAPI ships a lightweight BackgroundTasks tool for work that should run after the response is sent.
from fastapi import BackgroundTasks
def write_log(msg: str):
with open("log.txt", "a") as f:
f.write(msg)
@app.post("/signup")
def signup(bg: BackgroundTasks):
bg.add_task(write_log, "new user")
return {"ok": True}Limits of BackgroundTasks
BackgroundTasks runs in the same process. If the server restarts, the work is lost, and it cannot scale across machines.
For durable, distributed work you need a real job queue.
What is a Job Queue?
A job queue stores tasks in a broker such as Redis or RabbitMQ. Separate worker processes pull tasks and execute them, independent of the web server.
Defining a Celery Task
Celery is the most common Python job queue. You decorate a function as a task.
from celery import Celery
celery_app = Celery("tasks", broker="redis://localhost:6379/0")
@celery_app.task
def send_email(to: str):
# slow work here
return "sent to " + toEnqueuing from FastAPI
Trigger the task with .delay(); it returns immediately while a worker runs it later.
@app.post("/notify")
def notify(email: str):
send_email.delay(email)
return {"queued": True}Running Workers
Workers are separate processes you scale independently of the web tier.
celery -A tasks worker --loglevel=info --concurrency=4Tracking Task Results
With a result backend, you can store and query task status and outcomes.
result = send_email.delay("a@b.com")
print(result.id, result.status)Retries and Reliability
Job queues can automatically retry failed tasks with backoff, something in-process tasks cannot do.
@celery_app.task(bind=True, max_retries=3)
def process(self, item):
try:
do_work(item)
except Exception as exc:
raise self.retry(exc=exc, countdown=10)Scheduling Periodic Jobs
Celery Beat runs tasks on a schedule, like nightly cleanups or hourly syncs.
celery_app.conf.beat_schedule = {
"cleanup": {"task": "tasks.cleanup", "schedule": 3600.0}
}Idempotent Tasks
Because a queued task may be retried, design tasks to be idempotent so running them twice causes no harm, for example by checking if the email was already sent.
Quick Check
Test your background work knowledge.
Recap
You learned to keep request handlers fast:
- BackgroundTasks handles simple in-process after-response work
- Job queues like Celery give durable, distributed, retryable tasks
- Scale workers independently and schedule periodic jobs
Offloading slow work keeps your API responsive under load.
Frequently asked questions
Is the “Background Tasks and Job Queues” lesson free?
Yes — the full text of “Background Tasks and Job Queues” is free to read here on the web, and the FastAPI Backend Development Bootcamp course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the FastAPI Backend Development Bootcamp course, upgrade to CoddyKit PRO.
What will I learn in “Background Tasks and Job Queues”?
Learn to offload slow work from request handlers using FastAPI background tasks and distributed job queues like Celery. You practise FastAPI Backend Development Bootcamp with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start FastAPI Backend Development Bootcamp?
No prior experience is required. FastAPI Backend Development Bootcamp on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Background Tasks and Job Queues” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this FastAPI Backend Development Bootcamp lesson?
Yes. Every FastAPI Backend Development Bootcamp lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Caching Strategies with Redis
- Asynchronous Database Access
- Load Balancing & Monitoring
- Background Tasks and Job Queues