How to preserve Function Metadata while using Decorators?
Last Updated :
04 Aug, 2022
Decorators are a very powerful and useful tool in Python since it allows programmers to modify the behavior of function or class. Decorators allow us to wrap another function in order to extend the behavior of the wrapped function, without permanently modifying it.
Note: For more information, refer Decorators in Python
How to preserve Metadata?
This can be done using the wraps() method of the functools. It updates the wrapper function to look like wrapped function by copying attributes such as __name__, __doc__ (the docstring), etc.
Example:
Python3
import time
from functools import wraps
def timethis(func):
@wraps (func)
def wrapper( * args, * * kwargs):
start = time.time()
result = func( * args, * * kwargs)
end = time.time()
print (func.__name__, end - start)
return result
return wrapper
@timethis
def countdown(n: int ):
while n > 0 :
n - = 1
countdown( 100000 )
print (countdown.__name__)
print (countdown.__doc__)
print (countdown.__annotations__)
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Output:
countdown 0.00827932357788086
countdown
Counts down
{'n': <class 'int'>}
Advantages of using wraps():
- Copying decorator metadata is an important part of writing decorators. If you forget to use @wraps, you’ll find that the decorated function loses all sorts of useful information. For example, if omitted, the output of the last example would look like this:
countdown 0.030733823776245117
wrapper
None
{}
- An important feature of the @wraps decorator is that it makes the wrapped function available to you in the __wrapped__ attribute. For example, if you want to access the wrapped function directly, you could do this:
countdown.__wrapped__(100000)
- The presence of the __wrapped__ attribute also makes decorated functions properly expose the underlying signature of the wrapped function. For example:
Python3
from inspect import signature
print (signature(countdown))
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(n:int)
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