When using Celery’s `shared_task` decorator in a class method, you cannot directly call other methods of the class because the `shared_task` decorator binds the method to the Celery task system, not to the instance of the class. This results in the method being treated as a standalone function, losing access to the class’s instance (`self`) and its other methods. Let’s break it down and explore why this happens and how to address it.

Why This Happens

1. Loss of Instance Context:

— The shared_task decorator from Celery is designed to create tasks that can be called independently of any class instance. When you apply @shared_task to a method, Celery treats it as a standalone function, not as an instance method. As a result, the method does not receive the `self` parameter, which is necessary to access other instance methods or attributes of the class.

— When the task is executed by Celery, it runs in a separate process or worker, which does not have access to the instance of the class where the task was defined.

2. Serialization and Task Execution:

— Celery serializes task arguments and sends them to a worker process, which runs the task in a different Python process. The worker does not have access to the class instance or its state unless explicitly passed as part of the task’s arguments.

— Since self is not automatically passed to a @shared_task -decorated method, you cannot call other instance methods (e.g., self.other_method()) because self is undefined in the task’s context.

3. Method Binding Issue:

— Normally, Python instance methods automatically receive self as the first argument when called on an instance (e.g., `instance.method()`). However, Celery’s task system does not bind the method to the instance, so the method behaves like a static function, lacking access to the instance’s context.