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Use Cloud Tasks to easily defer functions executions

Project description

Async Cloud Tasks

Use Cloud Tasks to easily defer functions executions in your web applications 🍯

Inspired by django-cloud-tasks, thanks to GeorgeLubaretsi 👏🏻👏🏻👏🏻

Integrate Google Cloud Tasks with web applications without the need to create an exclusive endpoint to handle tasks. The package provides easy to use decorator to create task handlers. App looks for tasks in cloud_tasks.py files in your installed applications and auto-registers them.

Prerequisites

  • Python 3.7+

Dependencies

Support

  • IMPORTANT: Now it is only giving support for Django framework.

Installation

Install the package from PyPi

pip install async-cloud-tasks

Add async_cloud_tasks to INSTALLED_APPS:

INSTALLED_APPS = (
    # ...
    'async_cloud_tasks',
    # ...
)

Add configuration to your settings

ASYNC_CLOUD_TASKS={
    'gcp_location': '<GCP TASK QUEUE LOCATION>',
    'gcp_project_name': '<GCP TASK QUEUE PROJECT NAME>',
    'task_handler_root_url': '_tasks/',
    'service_url': '<BASE SERVICE URL>',
    'handler_secret': '<SECRET KEY TO BE USED FOR TASK HANDLER AUTHENTICATION>'
}

# This setting allows you to debug your cloud tasks by running actual task handler function locally
# instead of sending them to the task queue. Default: False
ASYNC_CLOUD_TASKS_EXECUTE_LOCALLY = False

Add cloud task views to your urls.py (must resolve to the same url as task_handler_root_url)

# urls.py
# ...
from django.urls import path, include
from async_cloud_tasks import urls as dct_urls

urlpatterns = [
    # ...
    path('_tasks/', include(dct_urls)),
]

Quick start (only for Django)

Simply import the task decorator and define the task inside cloud_tasks.py in your app. First parameter should always be request which is populated after task is executed by Cloud Task service.

You can get actual request coming from Cloud Task service by accessing request.request in your task body and additional attributes such as: request.task_id, request.request_headers

# cloud_tasks.py
# ...
from async_cloud_tasks.decorators import task

@task(queue='default')
def example_task(request, p1, p2):
    print(p1, p2)
    print(request.task_id)

Pushing the task to the queue:

from my_app.cloud_tasks import example_task

example_task(p1='1', p2='2').defer()

It is also possible to run an actual function using run method of CloudTaskWrapper object instance that is returned after task is called (this can be useful for debugging):

task = example_task(p1=i, p2=i)
task.run()

References

Project details


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