Getting Started with Celery: A Beginner’s Guide.

Introduction.

What is Celery?

Setting up a Celery Project.

Install Celery:

• Start by installing Celery and a message broker (e.g., RabbitMQ or Redis) using pip:

pip install celery

 Create a Celery Instance:

• In your Python project, create a new file (e.g., tasks.py) and initialize a Celery instance:

from celery import Celery app = Celery('tasks', broker='amqp://guest:guest@localhost:5672//')

• In this example, we're using RabbitMQ as the message broker, but you can replace the broker URL with the appropriate connection string for your chosen broker.

Define Tasks:

• In the same tasks.py file, define your tasks using the @app.task decorator:
• This defines a task named add that takes two arguments, x and y, and returns their sum.

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

Start the Celery Worker:

• • Open a terminal or command prompt and navigate to your project directory. Start the Celery worker by running:

celery -A tasks worker --beat --scheduler django --loglevel=info

• This command starts the Celery worker, enabling it to listen for and process tasks from the task queue.

Execute Tasks:

• •  In your main application code (e.g., a Django view or Flask route), import the task and execute it asynchronously:

from tasks import add

result = add.delay(4, 4)

• The delay method sends the task to the task queue, and Celery will process it as soon as a worker is available.

Retrieve Results:

• • You can retrieve the result of a task using the AsyncResult object:

result.get(timeout=1)  # Wait for up to 1 second for the result

• If the task completes within the specified timeout, the result will be returned. Otherwise, an exception will be raised.

Monitoring and Management:

• Flower: A web-based monitoring tool that allows you to view task progress, revoke tasks, and monitor worker status.Refer to the documentation:https://flower.readthedocs.io/

• Celery Beat: A scheduler that enables you to run tasks periodically or at specific times. Refer to the documentation:https://docs.celeryq.dev/en/stable/userguide/periodic-tasks.html

• Celery Events: A real-time monitoring system that sends event notifications about task progress and worker status.Refer to the documentation:https://docs.celeryq.dev/en/stable/reference/celery.events.html

Conclusion.