When Celery Beat sends the same task twice to the worker on every interval, it's likely due to a misconfiguration or issue with the Celery and Celery Beat setup. Here are some common causes and solutions to address this problem:

  1. Celery Beat Schedule Overlapping: Check if you have accidentally scheduled the same task twice in your Celery Beat configuration. Double-check your Celery Beat schedule settings to ensure that the task is not duplicated.

  2. Multiple Celery Beat Instances: Ensure that you are running only one instance of Celery Beat. Running multiple Celery Beat instances can lead to tasks being scheduled multiple times.

    To avoid this, make sure you run Celery Beat with a single process, for example:

    bash
    celery -A your_project_name beat --scheduler django_celery_beat.schedulers:DatabaseScheduler --detach
  3. Check Celery Version Compatibility: Make sure that you are using compatible versions of Celery and Celery Beat. Check the documentation and the compatibility matrix to ensure they work together without issues.

  4. Worker Connection Issues: Verify that there are no network or connection issues between the Celery Beat scheduler and the Celery worker. Check the logs for any error messages related to communication between the scheduler and the worker.

  5. Check Timezone Settings: Ensure that your Celery Beat schedule is using the correct timezone. Celery Beat schedules tasks based on the timezone specified in your configuration. If the timezone is incorrect, it may cause tasks to be triggered multiple times.

  6. Inspect Task IDs: Check if the task IDs of the duplicated tasks are the same or different. If they are the same, it might indicate that the task is being requeued or restarted multiple times for some reason. Look into the task result backend settings to ensure that tasks are not being duplicated due to requeuing.

  7. Duplicate Worker Registration: Make sure that your Celery worker is not registered more than once in your application. Multiple worker registrations can lead to the same task being processed multiple times.

  8. Check for Long Running Tasks: Long-running tasks that are not completing before the next Celery Beat schedule interval may cause tasks to be duplicated. Ensure that your tasks complete within a reasonable time frame.

  9. Avoid Time Skew: If there are time discrepancies between the Celery Beat scheduler and the Celery worker, it could cause tasks to be triggered multiple times. Ensure that the clocks on both machines are synchronized.

By checking and addressing the above common issues, you should be able to prevent the duplication of tasks sent by Celery Beat to the worker. If the issue persists, consider providing more details about your Celery and Celery Beat configuration and the task implementation so that we can offer more targeted assistance.

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