Task retry and error handling in Django - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ component_behavior

intermediate

What happens when a Celery task raises an exception without retry?

Consider a Django project using Celery for background tasks. If a task raises an exception and does not explicitly retry, what will be the outcome?

Django

from celery import shared_task

@shared_task
def send_email(user_id):
    user = User.objects.get(id=user_id)
    if not user.email:
        raise ValueError('No email found')
    # send email logic here
    return 'Email sent'

A The task will automatically retry 3 times before failing.

B The task will fail and be marked as failed in Celery without retrying.

C The task will silently ignore the exception and mark as successful.

D The task will be retried indefinitely until it succeeds.

💡 Hint

Think about default Celery behavior when no retry is specified.

By default, if a Celery task raises an exception and no retry logic is implemented, the task fails immediately and is marked as failed. Celery does not retry automatically unless configured.

📝 Syntax

intermediate

Which option correctly retries a Celery task on failure with exponential backoff?

You want a Celery task to retry up to 3 times with exponential backoff starting at 10 seconds. Which code snippet correctly implements this?

Django

from celery import shared_task
from celery.exceptions import MaxRetriesExceededError

@shared_task(bind=True)
def fetch_data(self):
    try:
        # code that might fail
        pass
    except Exception as exc:
        # retry logic here
        pass

A self.retry(exc=exc, countdown=3, max_retries=10)

B self.retry(exc=exc, countdown=10 * self.request.retries, max_retries=3)

C self.retry(exc=exc, countdown=10 ** self.request.retries, max_retries=3)

D self.retry(exc=exc, countdown=10, max_retries=3)

💡 Hint

Exponential backoff means the wait time grows exponentially with retries.

Using countdown=10 ** self.request.retries causes the delay to grow exponentially (10, 100, 1000 seconds). The max_retries limits retries to 3.

🔧 Debug

advanced

Why does this Celery task retry not work as expected?

This task is supposed to retry on failure but never retries. What is the cause?

Django

from celery import shared_task

@shared_task(bind=True)
def process_order(self, order_id):
    try:
        order = Order.objects.get(id=order_id)
        # process order
    except Order.DoesNotExist as e:
        self.retry(exc=e, countdown=5, max_retries=2)
        raise

A The task is missing the bind=True decorator, so self.retry is undefined.

B The max_retries parameter is invalid and causes retry to be ignored.

C The countdown value must be a string, not an integer.

D The retry is called inside except but the exception is not re-raised or returned, so task ends successfully.

💡 Hint

Check what happens after calling self.retry inside except block.

Calling self.retry() raises a special exception to retry the task. If the exception is caught or the function returns normally, retry does not happen. Here, the retry call is not followed by a raise or return, so the task ends without retry.

❓ state_output

advanced

What is the state of a Celery task after max retries are exceeded?

A Celery task is configured to retry 2 times on failure. After the third failure, what is the task state in the backend?

Django

from celery import shared_task

@shared_task(bind=True, max_retries=2)
def unreliable_task(self):
    raise RuntimeError('Fail')

A The task state is 'FAILURE' and the exception info is stored.

B The task state is 'RETRY' indefinitely.

C The task state is 'SUCCESS' despite failures.

D The task state is 'PENDING' waiting for manual retry.

💡 Hint

What happens when retries are exhausted in Celery?

When max retries are exceeded, Celery marks the task as FAILURE and stores the exception details. It does not retry further.

🧠 Conceptual

expert

How to implement custom error handling and retry logic in Django with Celery?

You want to retry a Celery task only for network-related errors but fail immediately for others. Which approach correctly implements this selective retry?

Django

from celery import shared_task
import requests

@shared_task(bind=True, max_retries=5)
def fetch_api(self, url):
    try:
        response = requests.get(url)
        response.raise_for_status()
        return response.json()
    except Exception as exc:
        # retry only for network errors
        pass

A Check if exc is requests.exceptions.RequestException, then call self.retry(exc=exc), else raise exc.

B Always call self.retry(exc=exc) regardless of exception type.

C Use a try-except with a generic except and ignore all exceptions silently.

D Catch only requests.exceptions.HTTPError and retry, raise others.

💡 Hint

Selective retry means retry only for specific exception types.

To retry selectively, check the exception type. Retry only for network-related exceptions like requests.exceptions.RequestException. For others, raise immediately to fail the task.

Practice

1. What is the main purpose of using task retry in Django background tasks?

easy

A. To automatically try the task again if it fails temporarily

B. To stop the task immediately when an error occurs

C. To speed up the task execution by running it multiple times

D. To log the task output without retrying

Solution

1. Step 1: Understand task retry concept

   Task retry is used to handle temporary failures by trying the task again later.

2. Step 2: Identify the purpose in Django tasks

   It helps tasks recover from temporary errors without manual intervention.

3. Final Answer:

   To automatically try the task again if it fails temporarily -> Option A

4. Quick Check:

   Task retry = automatic retry on failure [OK]

Hint: Retry means try again automatically after failure [OK]

Common Mistakes:

• Thinking retry stops the task immediately
• Confusing retry with speeding up tasks
• Assuming retry only logs errors

2. Which of the following is the correct way to enable retry inside a Django task using Celery?

easy

A. @app.task(bind=True)\ndef my_task(self): self.retry(countdown=10)

B. def my_task(self): retry()

C. @app.task()\ndef my_task(): retry(countdown=10)

D. def my_task(): self.retry(countdown=10)

Solution

1. Step 1: Recognize the need for bind=True

   To use self.retry(), the task must be bound with bind=True.

2. Step 2: Check correct syntax for retry call

   The retry method is called on self inside the bound task function.

3. Final Answer:

   @app.task(bind=True)\ndef my_task(self): self.retry(countdown=10) -> Option A

4. Quick Check:

   bind=True + self.retry() = correct retry syntax [OK]

Hint: Use bind=True to access self.retry inside task [OK]

Common Mistakes:

• Not using bind=True and calling self.retry
• Calling retry without self or decorator
• Missing parentheses or wrong function signature

3. Given this task code snippet, what will happen if the task raises an exception on the first run?

@app.task(bind=True, max_retries=3)
def fetch_data(self):
    try:
        # code that may fail
        raise ValueError('Temporary error')
    except Exception as exc:
        raise self.retry(exc=exc, countdown=5)

medium

A. The task retries once and then stops

B. The task fails immediately without retrying

C. The task retries infinitely every 5 seconds

D. The task retries up to 3 times with 5 seconds delay between tries

Solution

1. Step 1: Analyze max_retries parameter

   max_retries=3 means the task will retry up to 3 times after failure.

2. Step 2: Understand retry call with countdown

   self.retry is called with countdown=5, so retries wait 5 seconds before next try.

3. Final Answer:

   The task retries up to 3 times with 5 seconds delay between tries -> Option D

4. Quick Check:

   max_retries=3 + countdown=5 = 3 retries with 5s delay [OK]

Hint: max_retries limits retries; countdown sets delay [OK]

Common Mistakes:

• Assuming infinite retries without max_retries
• Thinking retry happens immediately without delay
• Confusing max_retries with number of total runs

4. Identify the error in this Django Celery task code that tries to retry on failure:

@app.task(bind=True)
def process_data():
    try:
        # risky operation
        pass
    except Exception as e:
        self.retry(exc=e, countdown=10)

medium

A. retry method called outside except block

B. No max_retries set, so retry won't work

C. Missing self parameter in task function definition

D. Incorrect exception handling syntax

Solution

1. Step 1: Check function signature for bound task

   With bind=True, the task function must accept self as first parameter.

2. Step 2: Verify usage of self.retry

   self.retry is called, but self is undefined because function lacks self parameter.

3. Final Answer:

   Missing self parameter in task function definition -> Option C

4. Quick Check:

   bind=True requires self parameter [OK]

Hint: bind=True means add self parameter to task function [OK]

Common Mistakes:

• Forgetting self parameter with bind=True
• Calling retry outside except block
• Assuming max_retries is mandatory for retry

5. You want a Django Celery task to retry only on network errors but fail immediately on other exceptions. Which approach correctly implements this behavior?

hard

A. Set max_retries=0 and catch all exceptions to call self.retry

B. Use try-except to catch network errors and call self.retry; re-raise other exceptions

C. Call self.retry unconditionally in except block for all exceptions

D. Use a decorator to retry on all exceptions automatically

Solution

1. Step 1: Differentiate exception types in except block

   Catch only network-related exceptions to retry, others should raise immediately.

2. Step 2: Use self.retry only for network errors

   Call self.retry inside except for network errors; re-raise other exceptions to fail fast.

3. Final Answer:

   Use try-except to catch network errors and call self.retry; re-raise other exceptions -> Option B

4. Quick Check:

   Retry selectively by exception type using try-except [OK]

Hint: Retry only inside except for specific exceptions [OK]

Common Mistakes:

• Retrying on all exceptions without filtering
• Setting max_retries=0 disables retries
• Using decorators without exception control