裝飾器（Decorator）

Python 的裝飾器是任何可調用對象（callable object），用于修改函數（Function）或類（Class）。按照用途可分為：

函數裝飾器

類裝飾器

裝飾器的接口定義可概括為：

接收某個函數或類的引用作為參數；

修改該函數或類并返回。

簡單函數裝飾器示例

理解裝飾器

def my_decorator(func):

def wrapped_func(arg):

print("Before calling " + func.__name__)

func(arg)

print("After calling " + func.__name__)

return wrapped_func

def foo(arg):

print("Hi, foo has been called with " + str(arg) )

print("We call foo BEFORE decoration:")

foo("no decoration"); print()

print("We NOW decorate foo with my_decorator... ")

foo = my_decorator(foo)

print("We call foo AFTER decoration:")

foo("decoration")

程序對應的輸出為：

We call foo BEFORE decoration:

Hi, foo has been called with no decoration

We NOW decorate foo with my_decorator...

We call foo AFTER decoration:

Before calling foo

Hi, foo has been called with decoration

After calling foo

上述例子中的用法在實際開發中并不常用，我們更傾向于下面的寫法。

語法糖寫法

Python 提供一種更簡潔、直觀的裝飾器寫法。例如我們可以把上述例子寫成更簡便的形式：

def my_decorator(func):

def wrapped_func(arg):

print("Before calling " + func.__name__)

func(arg)

print("After calling " + func.__name__)

return wrapped_func

@my_decorator

def foo(arg):

print("Hi, foo has been called with " + str(arg) )

foo("decoration")

函數裝飾器應用示例

統計函數調用次數

def call_counter(func):

def func_with_counts(arg):

func_with_counts.calls += 1

return func(arg)

func_with_counts.calls = 0

return wrapped_func

@call_counter

def foo(arg):

return "foo: " + str(arg)

print("foo has been called {} time(s)".format(foo.calls))

for i in range(0, 51, 10):

foo(i)

print("foo has been called {} time(s)".format(foo.calls))

程序對應的輸出結果是：

foo has been calld 0 time(s)

foo: 0

foo: 10

foo: 20

foo: 30

foo: 40

foo: 50

foo has been calld 6 time(s)

用記憶表（Memoization1）優化 Fibonacci 數列算法

def memoize(func):

memo = {}

def memoized_func(arg):

if arg not in memo:

memo[arg] = func(arg)

return memo

return memoized_func

@memoize

def fib(n):

if n == 0:

return 0

elif n = 1:

return 1

else:

return fib(n-1) + fib(n-2)

for i in range(20):

print(fib(i), end=", ")

print(fib(20))

程序對應的輸出結果是：

0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181, 6765

類裝飾器

首先需要明確，Python 的裝飾器是任何可調用對象而不僅限于函數。我們可以定義一個類并使其對象可調用。例如我們可以定義一個帶緩存功能的類計算 Fibonacci：

class Fibonacci:

def __init__(self):

self.cache = {}

def __call__(self, n):

if n not in self.cache:

if n == 0:

self.cache[0] = 0

elif n == 1:

self.cache[1] = 1

else:

self.cache[n] = self.cache[n-1] + self.cache[n-2]

return cache[n]

fib = Fibonacci()

for i in range(20):

print(fib(i), end=", ")

print(fib(20))

程序對應的輸出結果是：

0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181, 6765

因此，我們可以構建一個可調用對象并令其作為裝飾器。

在下面的例子中，我們用類裝飾器統計函數調用次數：

class CallCounter:

def __init__(self, func):

self.calls = 0

self.func = func

def __call__(self, arg):

self.calls += 1

return self.func(arg)

@CallCounter

def foo(arg):

return "foo: " + str(arg)

print("foo has been called {} time(s)".format(foo.calls))

for i in range(0, 51, 10):

foo(i)

print("foo has been called {} time(s)".format(foo.calls))

注意 Memoization 是專業術語，不是 Memorization。?

原文地址：https://www.cnblogs.com/LexLuc/p/10259110.html

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