Python decorators are a powerful tool for adding functionality to functions or methods. However, when decorating functions, it’s crucial to preserve their metadata, such as docstrings, function name, and module name. If you’ve ever struggled with losing metadata when using decorators, you’re not alone.
In this article, we’ll dive into the concept of preserving metadata with decorators, providing clear explanations and practical examples to help you maintain metadata integrity in your Python code.
Understanding Metadata Preservation
Metadata, in the context of Python functions, refers to information associated with functions, such as their name, docstring, and module name.
When decorating functions, it’s important to ensure that this metadata is preserved, as it contributes to the readability and maintainability of the codebase.
How Decorators Impact Metadata
By default, decorating a function with another function replaces the original function’s metadata with that of the decorator function. This can lead to the loss of…
