Django Celery Mastery: Python Asynchronous Task Processing

Unlocking the Power of Asynchronous Task Processing with Python Celery

What you'll learn

Module 1: You will learn how to set up a working environment for Django Celery by building Docker containers for Django, Redis, and Celery workers.

Module 2: You will learn to create and register tasks within a Django application, start and manage Celery.

Module 3: You will learn to identify common exceptions and errors in Celery tasks and implement error control.

Module 4: You will learn to schedule tasks at specific times or intervals, customize periodic tasks, and utilize crontab schedules.

By the end of the course, you will have a solid understanding of Django Celery and be equipped to leverage its power.

Requirements

Prior knowledge of Django concepts is advantageous.

Prior knowledge of basic Python programming lexicon and concepts is adcentageous

Description

In today's fast-paced web development landscape, efficiently handling time-consuming and resource-intensive tasks is crucial for building high-performance applications. Django Celery, a powerful asynchronous task-processing library, provides the perfect solution to address this challenge. This comprehensive course, "Django Celery Mastery: Python Asynchronous Task Processing," is designed to empower you with the knowledge and skills necessary to harness the full potential of Django Celery and elevate your Python web applications to new heights of scalability and responsiveness.Course Description: The course begins by guiding you through the process of setting up a fully functional Django Celery working environment. You'll learn the essentials of Django Celery, explore task producers and consumers, and gain hands-on experience building Docker containers for Django, Redis (the message broker), and Celery workers. Additionally, you'll understand the role of a results backend and create a Redis Docker container to facilitate effective task communication.Moving forward, you'll dive deep into defining and executing Celery tasks within a Django application. You'll discover how to create and register tasks, start and manage Celery workers, and configure task routing for optimized task distribution. Advanced concepts such as task prioritization, task grouping, task chaining, task rate limits, and passing arguments and returning results from Celery tasks will be thoroughly covered. You'll also explore both synchronous and asynchronous task execution approaches and leverage the Flower monitoring tool to track and monitor Celery workers and tasks.Handling task failures and retries is a critical aspect of asynchronous task processing, and this course provides comprehensive introduction of this topic. You'll gain insights into common types of exceptions and errors in Celery tasks and explore various error handling strategies. You'll implement automatic retries, handle errors in task groups and chains, and discover techniques for handling failed tasks and task timeouts. Additionally, you'll learn how to gracefully shut down tasks, clean up failed tasks, and leverage error tracking and monitoring tools such as Sentry.Task scheduling and periodic tasks play a vital role in managing recurring tasks efficiently. In this course, you'll understand the fundamentals of task scheduling, including scheduling tasks to run at specific times or intervals. You'll explore the customization of periodic tasks, implement crontab schedules, and ensure schedule persistence in a Django application. Furthermore, you'll learn how to schedule Django custom commands using Celery Beat and monitor service status using custom event tracking and alerting mechanisms.Throughout the course, hands-on exercises, practical examples, and real-world scenarios will enhance your learning experience and enable you to apply the concepts directly in your own projects. By the end of this course, you'll have gained mastery over Django Celery and be equipped with the skills to implement efficient asynchronous task processing in Python applications, ensuring scalability, responsiveness, and optimal resource utilization.Whether you are a Python developer, Django developer, web application developer, software engineer, backend developer, or a technical lead/architect, this course will empower you to unlock the full potential of Django Celery and revolutionize your approach to asynchronous task processing. Don't miss this opportunity to level up your skills and supercharge your applications with the power of Celery. Enroll now and take the first step towards mastering asynchronous task processing in Python!

Overview

Section 1: Source Code

Lecture 1 Introduction

Lecture 2 Code Examples

Section 2: Setup Guides

Lecture 3 [Windows] Installing Python

Lecture 4 [Windows] Visual Studio Code Induction

Lecture 5 [Windows] Creating Virtual Environments

Lecture 6 [macOS] Visual Studio Code Induction

Lecture 7 [macOS] Installing Python

Lecture 8 [macOS] Creating Virtual Environments

Lecture 9 Docker Installation

Section 3: Preparing a Django Celery Working Environment

Lecture 10 Introducing Django Celery

Lecture 11 Introducing Task Producers

Lecture 12 Building a Django Docker Container

Lecture 13 Building a Redis Docker Container

Lecture 14 Introducing Task consumers (Workers)

Lecture 15 Building a Celery Worker Docker Container

Lecture 16 Introducing Results Backend

Section 4: Defining and Executing Celery Tasks

Lecture 17 Creating and Registering Celery Tasks in Django

Lecture 18 Starting the Celery Worker

Lecture 19 Initiating a Celery Task

Lecture 20 Creating a new standalone Celery Worker

Lecture 21 Introducing Tasks Routing

Lecture 22 Configuring Task Routing

Lecture 23 Introducing Celery Task Prioritization

Lecture 24 Configuring Task Prioritization (Redis)

Lecture 25 The Primitives - Task Grouping

Lecture 26 The Primitives - Task Chaining

Lecture 27 Task Rate limits

Lecture 28 Configuring Task Prioritization (RabbitMQ)

Lecture 29 Passing arguments and returning results from Celery tasks

Lecture 30 Executing tasks synchronously and asynchronously

Lecture 31 Monitoring Celery Workers and Tasks with Flower

Section 5: Handling Task Failures and Retries

Lecture 32 Common Types of Exceptions and Errors in Celery Tasks

Lecture 33 Dynamic Task Discovery in Celery: Auto-discovering Tasks in a Directory

Lecture 34 Error Handling: Try Except Blocks

Lecture 35 Handling Errors in Celery Tasks with Custom Task Classes

Lecture 36 Implementing Automatic Retries

Lecture 37 Error Handling in Groups

Lecture 38 Towards Error Handling in Task Chains

Lecture 39 Towards Dead-letter Queues: Handling Failed Tasks

Lecture 40 Task Timeouts and Task Revoking (Using task time limits and timeouts)

Lecture 41 Handling Errors in Task Result Callbacks

Lecture 42 Task Signals Graceful Shutdown and Cleanup of Failed Tasks

Lecture 43 Error Tracking and Monitoring with Sentry

Section 6: Task Scheduling and Periodic Tasks

Lecture 44 Introduction to Task Scheduling

Lecture 45 Scheduling Tasks to Run at Specific Times or Intervals

Lecture 46 Implementing Periodic Tasks Customization

Lecture 47 Crontab Schedules

Lecture 48 Implement Schedule Persistence for Celery in a Django Application

Lecture 49 Schedule a Django Custom Command with Celery Beat

Lecture 50 Monitoring Service Status Including Custom Event Tracking and Alerting

Python Developers: Developers who are already familiar with the Python programming language and want to expand their knowledge and skills in asynchronous task processing using Django Celery.,Django Developers: Developers who are experienced in Django web development and want to incorporate asynchronous task processing into their Django applications to enhance performance and scalability.,Web Application Developers: Professionals involved in web application development who want to learn how to leverage Django Celery for handling time-consuming and resource-intensive tasks asynchronously, such as sending emails, generating reports, or processing large datasets.,Software Engineers: Software engineers interested in learning about task queues and asynchronous processing in Python and Django.,Backend Developers: Backend developers who want to improve the efficiency of their applications by offloading time-consuming tasks to background workers using Django Celery.,Technical Leads and Architects: Technical leads and architects responsible for designing and implementing scalable and performant systems who want to explore asynchronous task processing techniques using Django Celery.,Anyone who is interested and keen to learn Python Celery