Day 12 装饰器，迭代器，生成器

一 装饰器 Decorator

A decorator is a design pattern in Python that allows a user to add new functionality to an existing object without modifying its structure. Decorators are usually called before the definition of a function you want to decorate.

作用 Usage

Python's decorators allow you to extend and modify the behavior of a callable (functions, methods, and classes) without permanently modifying the callable itself. Any sufficiently generic functionality you can “tack on” to an existing class or function's behavior makes a great use case for decoration

简单的装饰器 Simple Decorators

def my_decorator(func):
    def wrapper():
        print("Something is happening before the function is called.")
        func()
        print("Something is happening after the function is called.")
    return wrapper
​
def say_whee():
    print("Whee!")
​
say_whee = my_decorator(say_whee)

 

语法糖 Syntactic Sugar

The way you decorated say_whee() above is a little clunky. First of all, you end up typing the name say_whee three times. In addition, the decoration gets a bit hidden away below the definition of the function.

Instead, Python allows you to use decorators in a simpler way with the @ symbol, sometimes called the “pie” syntax.

def my_decorator(func):
    def wrapper():
        print("Something is happening before the function is called.")
        func()
        print("Something is happening after the function is called.")
    return wrapper
​
@my_decorator
def say_whee():
    print("Whee!")

有参装饰器Decorating Functions With Arguments

（Remain to be improved）

二 迭代器 Iterator

An iterator is an object that contains a countable number of values.

An iterator is an object that can be iterated upon, meaning that you can traverse/'trævɜːs/遍历 through all the values.

Technically, in Python, an iterator is an object which implements the iterator protocol/ˈprəʊtəkɒl/ 协议, which consist of the methods _iter_() and _next_().

Iterator vs Iterable 迭代器与可迭代对象

Lists, tuples, dictionaries, and sets are all iterable objects. They are iterable containers which you can get an iterator from.

All these objects have a iter() method which is used to get an iterator:

Looping Through an Iterator

We can also use a for loop to iterate through an iterable object:

The for loop actually creates an iterator object and executes the next() method for each loop.

三 生成器 Generator

Generator functions allow you to declare a function that behaves like an iterator, i.e. it can be used in a for loop.

the yield keyword

yield is a keyword in Python that is used to return from a function without destroying the states of its local variable and when the function is called, the execution starts from the last yield statement. Any function that contains a yield keyword is termed as generator. Hence, yield is what makes a generator. yield keyword in Python is less known off but has a greater utility which one can think of.

Example:

def first_n(n):
    '''Build and return a list'''
​
    num, nums = 0, []
    while num < n:
        nums.append(num)
        num += 1
    return nums
sum_of_first_n = sum(first_n(1000))
print(sum_of_first_n)
​

and use the generator to imporve it:

def firstn(n):
    num = 0
    while num < n:
        yield num
        num += 1
​
​
sum_of_first_n = sum(firstn(1000000))
​
print(sum_of_first_n)