How to run an async job from backend?

In the ShipFast, asynchronous jobs are represented as tasks. These tasks are defined as classes that inherit from a Task class provided by the ShipFast. The Task class provides a framework for defining tasks that can be executed asynchronously.

When a task is executed, it is passed to an AWS Lambda function as an event. The AWS Lambda function then processes the event and executes the task asynchronously.

info

If you're not familiar with AWS Lambda, here's the official documentation: "What is AWS Lambda?"

Invoking tasks

Running asynchronous tasks from the backend is made easy with the Task class. The Task class is a utility class that allows you to define and run asynchronous tasks in a clean and organized way.

import importlib
from django.conf import settings

module_name, package = settings.TASKS_BASE_HANDLER.rsplit(".", maxsplit=1)
Task = getattr(importlib.import_module(module_name), package)


class ExampleTask(Task):
    def __init__(self):
        super().__init__(name="example_task", source='backend.example_task')

info

Task uses the boto3 library to interact with the Amazon EventBridge service. When a particular task is invoked, it generates an event entry that is sent to the EventBridge service using the put_events method of the boto3 client. Learn more about Amazon EventBridge.

The importlib module provides tools for dynamically importing Python modules at runtime. The code then uses the imported modules to dynamically import a task handler module specified in the Django project's settings. The TASKS_BASE_HANDLER setting is a string that specifies the module and class name of the base task handler. The getattr() function is used to get the Task class from the dynamically imported module.

The ExampleTask class is then defined as a subclass of Task. The __init__ method of ExampleTask is used to set up the task. It sets up the basic properties of the task, such as its name and source. The name and source parameters can be used to identify the task to run within the serverless application.

tip

Make sure to check "How to create a new workers module?" to learn how to register and configure your task handlers.

Next, to invoke this task you can simply do:

data = {
    # ...
}
task = ExampleTask()
task.apply(data=data)

The apply() method is responsible for executing the task. It takes the data parameter and performs the necessary actions to complete the task.

Invoking tasks​

Invoking tasks