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(Thanks to Mark Lavin for significant contributions to this post.) In a previous post, we introduced using Celery to schedule tasks. In this post, we address things you might need to consider when planning how to deploy Celery in production. At Caktus, we've made use of Celery in a number of projects ranging from simple tasks to send emails or create image thumbnails out of band to complex workflo
Amazon's Simple Queue Service (SQS) is a relatively new offering in the family of Amazon Web Services (AWS). It's also an appealing one, because it proposes to quickly and easily replace a common component of the stack in a typical web application, thereby obviating the need to run a separate queue server like RabbitMQ. While RabbitMQ — the typical favorite for Celery users — is not necessarily di
from django.views.generic.base import TemplateView class MyViewClass(TemplateView): template_name = "index.html" def get(self, request, *args, **kwargs): context = # compute what you want to pass to the template return self.render_to_response(context) This will render your template index.html with the context you computed and return it as the content of an HttpResponse. Introduction to class-based
I recently found a way to speed up a large data import far more than I expected. The task was to read data from a text file and create data records in Django, and the naive implementation was managing to import about 55 records per second, which was going to take far too long given the amount of data that needed to be imported. My co-worker Karen Tracey suggested changing to bulk inserts. Instead
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