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celery python

Celery is an open-source distributed task queue system written in Python. It is commonly used for handling background tasks, such as sending emails, processing data, and running periodic tasks in web applications. Celery allows you to distribute the execution of tasks across multiple workers, making it suitable for handling tasks that are time-consuming or need to run asynchronously.

Here are the basic steps to use Celery in a Python application:

  1. Install Celery: You can install Celery using pip:Copy codepip install celery
  2. Create a Celery Application: Create a Python script (usually named or something similar) where you configure your Celery application. This includes setting up the broker (message broker like RabbitMQ or Redis) and creating an instance of the Celery application. Here’s an example:pythonCopy codefrom celery import Celery app = Celery('myapp', broker='pyamqp://guest@localhost//')
  3. Define Tasks: Define the tasks you want to execute using Celery. Tasks are just Python functions that are decorated with the @app.task decorator. Here’s an example:pythonCopy code@app.task def add(x, y): return x + y
  4. Run Workers: Celery tasks are executed by worker processes. You can start worker processes using the celery command:cssCopy codecelery -A myapp worker --loglevel=info Replace myapp with the name of your Celery application.
  5. Enqueue Tasks: In your application code, you can enqueue tasks by calling them as if they were regular Python functions:pythonCopy coderesult = add.delay(3, 4) The delay method schedules the task for execution asynchronously.
  6. Retrieve Task Results: You can retrieve the result of a task using the result.get() method or by setting up a callback to handle the result when the task is complete.
  7. Monitor and Administer: Celery provides tools for monitoring and administering your task queue, including a web-based admin interface and tools for task retries, error handling, and more.
  8. Configure Celery: You can configure Celery with various options to fit your application’s needs, such as specifying the result backend, setting concurrency levels, and defining task time limits.

Celery is a powerful tool for handling background tasks in Python applications. It’s widely used in web development to offload time-consuming tasks from the main application thread, ensuring responsiveness and scalability

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