python 装饰器模式
python 装饰器模式
前言
用python学设计模式学的还是学语法居多的感觉，具体的设计模式思想的学习与训练还是看回《Head First：Design Pattern》。
装饰器模式
import time
def log_calls(func):
def wrapper(*args, **kwargs):
now = time.time()
print(
"Calling {0} with {1} and {2}".format(
func.__name__, args, kwargs
)
)
return_value = func(*args, **kwargs)
print(
"Executed {0} in {1}ms".format(
func.__name__, time.time() - now
)
)
return return_value
return wrapper
def test1(a, b, c):
print("\ttest1 called")
def test2(a, b):
print("\ttest2 called")
def test3(a, b):
print("\ttest3 called")
time.sleep(1)
@log_calls
def test4(a, b):
print("\ttest4 called")
test1 = log_calls(test1)
test2 = log_calls(test2)
test3 = log_calls(test3)
test1(1, 2, 3)
test2(4, b=5) # 测试 **kwargs
test3(6, 7) #用
test4(6,b = 7) # @decorator synax
The Decorator Pattern is also known as Wrapper.
Advantage of Decorator Pattern：
-
It provides greater flexibility than static inheritance.
-
It enhances the extensibility of the object, because changes are made by coding new classes.
-
It simplifies the coding by allowing you to develop a series of functionality from targeted classes instead of coding all of the behavior into the object.
用mokey-patching可以达到同样的效果
来看下面这个实例：
class A:
def func(self):
print("func() is being called")
def monkey_f(self):
print("monkey_f() is being called")
if __name__ == "__main__":
# replacing address of "func" with "monkey_f"
A.func = monkey_f
obj = A()
# calling function "func" whose address got replaced
# with function "monkey_f()"
obj.func()
# func() is being called
Monkey patching is a technique to add, modify, or suppress the default behavior of a piece of code at runtime without changing its original source code.
