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Django in Production

Django in Production

By : Arghya Saha
4.7 (9)
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Django in Production

Django in Production

4.7 (9)
By: Arghya Saha

Overview of this book

You may have got your first Django developer job after a six-week bootcamp or online course, and that’s great, but what’s next? In small companies, mentorship can be hard to come by and gaining the traits of a senior developer without that can take a long time. This is precisely where Django in Production comes into play. This book will first delve into the true meaning of "good practice" and help you understand the rationale behind industry professionals building websites in specific ways to develop a solid foundation for your Django projects. Next, you will uncover hidden Django secrets through hands-on exploration, leveraging the power of Docker and version control to your advantage. You will gain insights into mastering Git hooks for efficient code maintenance, establishing a robust CI pipeline, and harnessing the capabilities of AWS Beanstalk. These tools will empower you to develop highly scalable products—an essential skill set for aspiring developers transitioning from junior to senior roles. Later, you will understand the significance of monitoring and be introduced to industry-standard tools utilized by professionals for effective monitoring practices. By the end of this book, you will have set yourself apart from the crowd, equipped with the knowledge and expertise to thrive as a seasoned Django developer.
Table of Contents (21 chapters)
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1
Part 1 – Using Django and DRF to Build Modern Web Application
7
Part 2 – Using the Advanced Concepts of Django
13
Part 3 – Dockerizing and Setting Up a CI Pipeline for Django Application
16
Part 4 – Deploying and Monitoring Django Applications in Production

Using celery beat with Django

Periodic tasks are one of the most common use cases for Celery. For example, say you want to send periodic emails to your users every week, or create certain summary reports every week. For such repetitive tasks, Celery provides celery beat, which is a scheduler that keeps checking for any scheduled task to be executed at the given time and then runs it. The celery beat worker would create tasks in place of the Django application and put them in the Redis task queue, from where tasks are then picked up by the Celery workers and executed.

Let us learn how to integrate celery beat into our Django project:

  1. There are multiple ways to create periodic tasks, such as adding a crontab configuration in the settings file, or plugging a beat schedule into the app.conf.beat_schedule object. They work perfectly, but lack ease of use. One option that truly stands out is using the on_after_finalize.connect signal.

    In the following example, we create a periodic...

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