Retry Celery tasks with exponential back off

Retry Celery tasks with exponential back off

To implement retrying Celery tasks with exponential backoff, you can use Celery's built-in retry functionality in combination with a custom retry delay strategy. Celery allows you to set the retry argument in the task decorator to specify the number of times the task should be retried and the retry_backoff argument to specify the backoff delay between retries.

Here's how you can define a task with exponential backoff retry:

from celery import Celery import time app = Celery('myapp', broker='pyamqp://guest@localhost//') @app.task(bind=True, max_retries=5) def my_task(self, arg1, arg2): try: # Your task logic here result = arg1 / arg2 return result except Exception as e: print(f"Task failed: {e}") # Calculate the exponential backoff delay in seconds delay = 2 ** self.request.retries print(f"Retrying in {delay} seconds...") time.sleep(delay) raise self.retry(exc=e)

In this example:

  1. We import Celery and create a Celery app.

  2. We define a task called my_task using the @app.task decorator. We set max_retries to 5, which means the task will be retried up to 5 times (total of 6 attempts).

  3. Inside the task, we have some logic that may raise an exception. If an exception occurs, we catch it, print an error message, calculate the exponential backoff delay using 2 ** self.request.retries, and sleep for that duration.

  4. We then raise self.retry(exc=e) to signal Celery to retry the task. The exc=e argument passes the original exception to the retry.

With this setup, the task will be retried with an exponential backoff delay, starting from 2 seconds and doubling with each retry, up to the specified max_retries. You can adjust the max_retries value and the backoff calculation to suit your specific requirements.

Examples

  1. "Celery retry tasks with exponential backoff"

    • This query is about implementing a retry mechanism for Celery tasks with exponential backoff, allowing tasks to be retried at increasing intervals after failures.
    from celery import Task from celery.exceptions import Retry class ExponentialBackoffTask(Task): def on_failure(self, exc, task_id, args, kwargs, einfo): retries = kwargs.get('retries', 0) delay = 2 ** retries kwargs['retries'] = retries + 1 self.retry(exc=exc, countdown=delay, max_retries=5, kwargs=kwargs)

  2. "How to retry Celery tasks with exponential backoff in Django"

    • This query focuses on implementing the exponential backoff pattern in a Django project with Celery.
    # Django settings.py CELERY_TASK_ROUTES = { 'myapp.tasks.my_retry_task': {'queue': 'retry_queue'}, } from celery import shared_task from celery.exceptions import Retry @shared_task(bind=True, base=ExponentialBackoffTask, max_retries=5) def my_retry_task(self, data, retries=0): try: # Perform some task pass except Exception as exc: self.retry(exc=exc, countdown=2**retries)

  3. "Celery retry task on failure with exponential backoff"

    • This query examines retrying a Celery task with exponential backoff after encountering an error or failure.
    from celery import shared_task from celery.exceptions import Retry @shared_task(bind=True, max_retries=5, base=ExponentialBackoffTask) def retry_on_failure(self, data): try: # Code that may fail pass except Exception as exc: # Retry with exponential backoff retries = self.request.retries self.retry(exc=exc, countdown=2**retries)

  4. "Configuring exponential backoff retries for Celery tasks"

    • This query is for configuring Celery to use exponential backoff for retrying tasks in general.
    from celery import Celery from celery import Task from celery.exceptions import Retry app = Celery('myapp') class ExponentialBackoffTask(Task): def on_failure(self, exc, task_id, args, kwargs, einfo): retries = self.request.retries countdown = 2 ** retries self.retry(exc=exc, countdown=countdown, max_retries=5)

  5. "Celery exponential backoff with max retries"

    • This query explores setting a limit on the number of retries for a Celery task with exponential backoff.
    from celery import shared_task from celery.exceptions import Retry @shared_task(bind=True, max_retries=3) def limited_retry_task(self, data): try: # Task code that might fail pass except Exception as exc: # Retry with exponential backoff and a limit retries = self.request.retries if retries < 3: self.retry(exc=exc, countdown=2**retries) else: raise exc # If max retries are reached, do not retry

  6. "Celery retry strategy with custom exponential backoff"

    • This query targets customizing the exponential backoff strategy for Celery tasks, allowing for different growth rates.
    from celery import Task from celery.exceptions import Retry class CustomExponentialBackoffTask(Task): def on_failure(self, exc, task_id, args, kwargs, einfo): retries = self.request.retries growth_rate = 3 # Custom exponential growth rate countdown = growth_rate ** retries self.retry(exc=exc, countdown=countdown, max_retries=5)

  7. "Implementing exponential backoff retry logic in Celery"

    • This query aims to implement the logic for retrying Celery tasks with an exponential backoff pattern.
    from celery import shared_task from celery.exceptions import Retry @shared_task(bind=True, max_retries=4) def exponential_backoff_task(self, data): try: # Task code that might fail pass except Exception as exc: retries = self.request.retries self.retry(exc=exc, countdown=2**retries)

  8. "Logging Celery retries with exponential backoff"

    • This query addresses logging retries for Celery tasks that use exponential backoff, useful for monitoring and debugging.
    import logging from celery import shared_task from celery.exceptions import Retry logger = logging.getLogger(__name__) @shared_task(bind=True, max_retries=5) def retry_with_logging(self, data): try: # Potentially failing task logic pass except Exception as exc: retries = self.request.retries logger.warning(f"Retrying task, attempt {retries + 1}") self.retry(exc=exc, countdown=2**retries)

  9. "Celery retry with exponential backoff and custom exceptions"

    • This query demonstrates how to use custom exceptions with Celery retries and exponential backoff.
    class CustomTaskException(Exception): pass from celery import shared_task from celery.exceptions import Retry @shared_task(bind=True, max_retries=3) def custom_retry_task(self, data): try: # Task logic that might raise a custom exception pass except CustomTaskException as exc: retries = self.request.retries self.retry(exc=exc, countdown=2**retries)

  10. "Celery retry with exponential backoff and failure notification"

    • This query discusses how to implement notifications when Celery tasks with exponential backoff fail after all retries.
    import smtplib from email.mime.text import MIMEText from celery import shared_task from celery.exceptions import Retry def send_failure_email(subject, message): # Sending a failure notification via email smtp = smtplib.SMTP('smtp.example.com') msg = MIMEText(message) msg['Subject'] = subject msg['From'] = 'noreply@example.com' msg['To'] = 'admin@example.com' smtp.sendmail('noreply@example.com', ['admin@example.com'], msg.as_string()) @shared_task(bind=True, max_retries=3) def retry_with_notification(self, data): try: # Task logic that might fail pass except Exception as exc: retries = self.request.retries if retries < 3: self.retry(exc=exc, countdown=2**retries) else: send_failure_email("Task failed after retries", f"Task {self.request.id} failed after maximum retries.")

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