Celery integration overview in Flask - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ component_behavior

intermediate

What happens when a Celery task is called with .delay() in Flask?

Consider a Flask app using Celery for background tasks. When you call a task with .delay(), what is the immediate behavior?

Flask

from celery import Celery

celery_app = Celery('tasks', broker='redis://localhost:6379/0')

@celery_app.task
def add(x, y):
    return x + y

result = add.delay(4, 6)

A The task is sent to the Celery worker queue and returns an AsyncResult immediately without blocking.

B The task raises an error because .delay() is not a valid method for Celery tasks.

C The task runs in a new thread inside the Flask app and blocks until completion.

D The task runs immediately in the current Flask process and returns the result synchronously.

💡 Hint

Think about how Celery handles tasks asynchronously.

Calling .delay() sends the task to the Celery worker queue and returns immediately with an AsyncResult object. The task runs asynchronously in a separate worker process, not blocking the Flask app.

📝 Syntax

intermediate

Which Celery configuration option sets the message broker URL in Flask?

In a Flask app integrating Celery, you need to configure the broker URL. Which option correctly sets the broker URL?

A celery_app.conf.broker_url = 'redis://localhost:6379/0'

B celery_app.config['BROKER'] = 'redis://localhost:6379/0'

C celery_app.broker = 'redis://localhost:6379/0'

D celery_app.set_broker('redis://localhost:6379/0')

💡 Hint

Look for the official Celery configuration attribute for the broker URL.

The correct way to set the broker URL in Celery is by assigning the URL string to celery_app.conf.broker_url. Other options are invalid or do not exist.

❓ state_output

advanced

What is the value of result.ready() immediately after calling a Celery task with .delay()?

Given the code below, what does result.ready() return immediately after add.delay(2, 3) is called?

Flask

from celery import Celery

celery_app = Celery('tasks', broker='redis://localhost:6379/0')

@celery_app.task
def add(x, y):
    return x + y

result = add.delay(2, 3)
ready_state = result.ready()

A None, because the task result is not available until .get() is called.

B True, because the task completes instantly in the same process.

C Raises an AttributeError because .ready() is not a valid method.

D False, because the task is queued and not completed immediately.

💡 Hint

Think about asynchronous task execution and when results become ready.

The result.ready() method returns False immediately after .delay() because the task is still queued or running asynchronously. It only returns True once the task finishes.

🔧 Debug

advanced

Why does this Flask app with Celery fail to execute tasks?

Examine the code below. Why will the Celery tasks never run?

Flask

from flask import Flask
from celery import Celery

app = Flask(__name__)
celery = Celery(app.name, broker='redis://localhost:6379/0')

@celery.task
def multiply(x, y):
    return x * y

@app.route('/start')
def start_task():
    multiply.delay(5, 6)
    return 'Task started'

A The Flask app must call celery.start() to run tasks, which is missing.

B The Celery worker process is not running, so tasks are never executed.

C The broker URL is incorrect and causes connection failure.

D The task function multiply is not decorated properly with @app.task.

💡 Hint

Think about what runs Celery tasks in the background.

Celery tasks require a separate worker process running to consume and execute tasks from the broker queue. Without starting the Celery worker, tasks remain queued and never run.

🧠 Conceptual

expert

How does Celery ensure task results are accessible after asynchronous execution in Flask?

In a Flask app using Celery, how are task results stored and retrieved after the task completes?

A Results are returned directly to the Flask route that called the task without any backend storage.

B Task results are stored in Flask's session object automatically after task completion.

C Celery stores results in a backend like Redis or a database configured as the result backend, accessible via AsyncResult.

D Celery writes results to local files on the worker machine, which Flask reads later.

💡 Hint

Consider how asynchronous systems keep track of results separately from the main app.

Celery uses a result backend like Redis, a database, or other supported stores to save task results. The Flask app can retrieve results asynchronously using the AsyncResult object linked to the task ID.