Django Celery Mastery: Python Asynchronous Task Processing

Django Celery Mastery: Python Asynchronous Task Processing
Published 7/2023
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz

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 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

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 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