Using classes as decorators is more flexible and suitable for saving state or complex logic. Its core lies in: 1. Init initialization parameters of the class; 2. Call handles function calls; 3. Supports parameter decoration, and needs to be packaged with another layer; 4. It can record status, extension functions, and multi-layer encapsulation; 5. Meta information is not retained by default, and can be repaired by functools.wraps.
Using Python classes as decorators is actually a little more complicated than function decorators, but after understanding them, you will find that it is more flexible, especially suitable for scenarios where state or logic is complex.
Why use classes as decorators?
A decorator is essentially a thing that "accepts a function and returns a new function". Usually we use functions to write decorators, but sometimes you hope that the decorator itself can remember some states, or multiple methods work together, so using classes is more advantageous.
For example, if you want to record how many times a function has been called, or if you want to pass parameters and keep them in state during decoration, the use of classes will be clearer. The __init__ method of the class can initialize parameters, while the __call__ method is used to handle calls to decorated functions.
How to write a class decorator?
The most basic structure is as follows: define a class and implement __init__ and __call__ methods.
class MyDecorator:
def __init__(self, func):
self.func = func
def __call__(self, *args, **kwargs):
print("Decorator Pre-Operation")
result = self.func(*args, **kwargs)
print("Decorator Post-Operation")
return result
@MyDecorator
def says_hello():
print("Hello")
say_hello() If written in this way, the decorator can only be used for functions and cannot take parameters. If you want to pass parameters like @decorator(arg1=value) , you have to include another layer:
class MyParamDecorator:
def __init__(self, param=None):
self.param = param
def __call__(self, func):
def wrapped(*args, **kwargs):
print(f"Decorator Parameters: {self.param}")
return func(*args, **kwargs)
Return wrapped
@MyParamDecorator(param="test")
def do_something():
print("Execution")
do_something() The key to this writing is: when you use a decorator with parameters, Python first calls the class __init__ , and then uses the returned instance as the decorator and then calls __call__ .
Common uses and suggestions
- Record status : For example, count how many times a function has been called.
- Extended function : Add logs, permission checks, etc. without modifying the original function.
- Multi-layer encapsulation : Classes can have multiple methods to facilitate organizational logic.
If you just make some simple wrappers, function decorators are enough; but once state management or complex logic is involved, the advantages of decorator-like decorator will be reflected.
In addition, it is important to note:
- Decorators written by class decorators do not retain the meta information of the original function by default (such as
__name__), and can be fixed withfunctools.wraps. - If you are not familiar with the role of
__call__, you can start with the function decorator and slowly transition to class writing.
Ending
In general, although the class-writing decorator in Python seems a little bit in a bit at the beginning, it has a clear structure and strong scalability, especially when facing scenarios where states need to be maintained. After mastering this technique, you will find that many advanced Curry decorator logics are easier to understand.
Basically that's it.
The above is the detailed content of Python class decorator usage. For more information, please follow other related articles on the PHP Chinese website!
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