Effective Decorators—Avoiding Common Mistakes

Learn how to avoid common side effects when using decorators.

We'll cover the following

Preserving data about the original wrapped object

While decorators are a great feature in Python, they are not exempt from issues if used incorrectly. Let's look at some common issues to avoid in order to create effective decorators.

Preserving data about the original wrapped object

One of the most common problems when applying a decorator to a function is that some of the properties or attributes of the original function are not maintained, leading to undesired, and hard-to-track, side effects.

To illustrate this, let's look at a decorator that is in charge of logging when the function is about to run:

Get hands-on with 1400+ tech skills courses.

Preface

Introduction to Clean Code, Code Formatting, and Tools

Pythonic Code

General Traits of Good Code

The SOLID Principles

Using Decorators to Improve Our Code

Getting More Out of Our Objects with Descriptors

Generators, Iterators, and Asynchronous Programming

Unit Testing and Refactoring

Common Design Patterns

Clean Architecture

Conclusion

Effective Decorators—Avoiding Common Mistakes

Preserving data about the original wrapped object