Python Metaprogramming

Developed with
Trivera

Contents

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Introduction
1
Introduction
PREVIEW30s
Meta
2
MetaProgramming
PREVIEW23m 29s
Review
3

The course is part of this learning path

Introduction
Overview
Difficulty
Beginner
Duration
25m
Students
1337
Ratings
3.6/5
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Description

This training course provides you with a deep dive into how to use metaprogramming to dynamically alter the behavior of Python scripts at runtime, using techniques such as monkey patching.

Learning Objectives

  • Understand what metaprogramming is and what it can be used for
  • Review how to access local and global variables by name
  • Know how to inspect the details of any object at runtime
  • Know how to manipulate the behavior of an object runtime through the use of monkey patching
  • And finally, understand how to create and use decorators for classes and functions

Prerequisites

  • A basic understanding of the Python programming language
  • A basic understanding of software development
  • A basic understanding of the software development life cycle

Intended Audience

  • Software developers interested in learning how to write Python code in a Pythonic way
  • Python junior-level developers interested in advancing their Python skills 
  • Anyone with an interest in Python and how to use Python to write concise and elegant scripts for general purpose tasks
Transcript

Okay, welcome back. In this course, we're going to review metaprogramming and the metaprogramming capabilities within the Python language. The learning objectives for this course will be to learn what metaprogramming means, to understand how to access local and global variables by name, how we can inspect the details of any object, using attribute functions to manipulate an object, and understanding how to create decorators for classes and functions.

Lectures

About the Author
Avatar
Jeremy Cook
Content Lead Architect
Students
70615
Labs
44
Courses
105
Learning Paths
52

Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.

He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, GCP, Azure), Security, Kubernetes, and Machine Learning.

Jeremy holds professional certifications for AWS, GCP, and Kubernetes.

Covered Topics