Decorators in Python can also be used to add metadata to functions or classes. Metadata is additional information about the function or class that can be used by other parts of the program.
Here's an example of a decorator that adds metadata to a function:
def metadata_decorator(meta): def decorator(func): func.meta = meta return func return decorator |
This decorator takes a metadata argument and returns a new decorator that adds the metadata to the function. When the new decorator is applied to a function, it adds the metadata to the function as an attribute.
To use this decorator to add metadata to a function, simply apply it to the function:
@metadata_decorator({'author': 'John Doe', 'description': 'This function does something'})def my_function(): # Code here pass |
In this example, the @metadata_decorator syntax applies the metadata_decorator decorator to the my_function() function. The metadata is specified as a dictionary with the keys author and description. When the function is defined, the decorator adds the metadata to the function as an attribute.
The metadata can then be accessed from other parts of the program using the function's attribute:
print(my_function.meta['author'])print(my_function.meta['description']) |
In this example, the metadata is accessed using the meta attribute of the my_function() function.
Using decorators to add metadata to functions or classes can be useful for documentation, testing, and other purposes. It allows you to add additional information about the function or class that can be used by other parts of the program.