Python decorators are essentially function wrappers, used to modify functions or class behaviors without changing the source code. 1. A decorator is a function that receives a function or class as an argument, returning the wrapped version, for example, using the @decorator syntax is equivalent to func = decorator(func); 2. The wrapper function should use args and *kwargs to receive any parameters, and return the original function execution result to retain the return value; 3. Multi-layer decorator is executed in the order from bottom to top, that is, the decorator closest to the function is run first; 4. Classes can also be used as decorators, and the call method needs to be implemented, suitable for complex scenarios where states need to be saved. After understanding these mechanisms, the decorator will become intuitive and practical.
Python's decorator syntax and usage seem a bit confusing, but after understanding the mechanism, you will find that it is very practical. Its core role is to modify the behavior of functions or classes without modifying their source code. This is especially useful when writing frameworks, tool functions, or uniformly handling certain logic.
The essence of a decorator: function wrapping
A decorator is essentially a function that wraps another function or class. You can think of it as adding an extra layer of functionality to it without changing the original function.
For example, the following simple example:
def my_decorator(func):
def wrapper():
print("Before function call")
func()
print("After function call")
Return wrapper
@my_decorator
def says_hello():
print("Hello")
say_hello() In this code, @my_decorator is how to use the decorator. It is equivalent to:
say_hello = my_decorator(say_hello)
That is, pass the say_hello function to my_decorator , and then return a new function and assign it to say_hello . This way, the packaged version is executed when calling.
How to deal with decorators with parameters?
If the decorated function has parameters, the wrapper function in the decorator must also be able to receive these parameters. The easiest way is to use *args and **kwargs to wildly assign all parameters.
For example:
def decorator_with_args(func):
def wrapper(*args, **kwargs):
print("Arguments:", args, kwargs)
return func(*args, **kwargs)
Return wrapper
@decorator_with_args
def greet(name, age):
print(f"Hi {name}, you are {age}")
greet("Alice", 25)At this time the wrapper function can handle any parameters. A few points to remember:
- The wrapper function needs to return the result of func(...) , otherwise the return value of the original function will be discarded
- If the original function has a return value, don't forget to return from the wrapper
- The parameters can be diverse, but using
*argsand**kwargsis the most common method.
The order of multi-layer decorators
You can overlay multiple decorators on a function, but be aware that their execution order is run from bottom to top (or from inside to outside).
For example:
def deco1(func):
def wrapper(*args, **kwargs):
print("deco1 before")
result = func(*args, **kwargs)
print("deco1 after")
return result
Return wrapper
def deco2(func):
def wrapper(*args, **kwargs):
print("deco2 before")
result = func(*args, **kwargs)
print("deco2 after")
return result
Return wrapper
@deco1
@deco2
def says_hi():
print("Hi")
say_hi()The output order is:
deco1 before deco2 before Hi deco2 after deco1 after
So the order of the decorators will affect the final behavior. If you want to execute a certain logic first, pay attention to the order in which the decorator is written.
Classes can also be used as decorators
In addition to functions, you can also use classes to implement decorators. This practice is usually used in situations where state is required.
class MyDecorator:
def __init__(self, func):
self.func = func
def __call__(self, *args, **kwargs):
print("Class decorator before")
result = self.func(*args, **kwargs)
print("Class decorator after")
return result
@MyDecorator
def do_something():
print("Doing something")
do_something() The key point here is to let the class implement the __call__ method so that the instance can be called like a function. This method is suitable for more complex scenarios, such as if you want to record the number of calls, cache the results, etc.
Basically that's it. Decorators look fancy, but essentially function wrapping and replacement. As long as you understand this mechanism and add some exercises, you can use it flexibly.
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