48 lines
1.8 KiB
Python
48 lines
1.8 KiB
Python
"""
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Now that we have covered the basics of a function and variables, we will quickly cover decorators.
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Decorators are extremely useful and are used to wrap existing functions in another function, you can use this
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for many different things, a good example is permission checks.
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Key Concepts:
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**wrappers** are used to nest functions in another generalized function, this can be used for various things e.g (logging info)
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**args** we use the "*args* paramater to capture all positional based arguements, these come before keyword arguements.
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it sounds more complicated than it is, e.g
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myfunction(arg1, arg2, arg3)
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**kwargs** are arguements defined by a key rather than their position. e.g
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myfunction(keyword1="foo", keyword2="bar")
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**__name__** is just another magic/dunder method that returns the function's name.
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"""
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import time
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# Initial function takes in another function as a arguement
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def timed(function: any) -> any:
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# The wrapper, takes in the arguements and keyword arguements from the function
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def wrapper(*args: any, **kwargs: any) -> any:
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before = time.time()
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output = function(*args, **kwargs)
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after = time.time()
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print(f"{function.__name__} with output of {output} took {after-before}s to execute.")
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# Ensure the output of the function is passed back
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return output
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return wrapper
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# This is how we call a decorator in python.
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@timed
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# O(n^2) time complexity due to nested loops
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def exponential_function(n: int) -> int:
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output = 0
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for i in range(n):
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for j in range(i):
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output += j
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return output
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# Test the decorated function
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# This will take some time to compute
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exponential_function(1000)
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# This will take noticeably more time to compute
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exponential_function(10000)
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