python中的迭代器,生成器与装饰器详解

# 对list进行for循环本质上是调用了list的迭代器
list = [1,2,3,4]

# for 循环调用
for elem in list:
    print(elem)

# 迭代器调用
list_iter = list.__iter__()
while True:
   try:
    print(next(list_iter)) 
   except StopIteration:
       break

# 可迭代对象类
class CountDown(object):
    def __init__(self,num):
        self.num = num
    def __iter__(self):
        return MyIterator(self.num)

# 迭代类
class MyIterator(object):
    def __init__(self,num):
        self.NUM= num
        self.FINAL = 0
        self.now = num
        
    def __iter__(self):
        return self
    
    def __next__(self):
        step = 1 if self.NUM<self.FINAL else -1
        while self.now != self.FINAL:
            self.now += step
            return self.now - step
        raise StopIteration
        
cd_pos = CountDown(5)
cd_neg = CountDown(-5)
for i,j in zip(cd_pos,cd_neg):
    print(f'pos:{i}\tneg:{j}')

from  collections import Iterable
def f():
    pass
# 含有yield指令的函数可以称为生成器
def g():
    yield()
print(type(f()),isinstance(f(),Iterable))
print(type(g()),isinstance(g(),Iterable))

import os
# 生成器是迭代器的一种，让函数对象内部进行迭代
# 可以实现让函数内部暂停，实现了程序的异步功能，同时也实现了解耦。

def my_input():
    global str    
    str = input('input a line')
    pass

def my_write():
    with open('workfile.txt','w') as f:
        while(str):
            f.write(str+'\n')
            yield()
        return 


mw = my_write()
while(True):
    my_input()
    try:
        next(mw)
    except StopIteration:
        pass
    if not str:
        break   

# 不带参数的装饰器
from functools import wraps
# 装饰器封装一个函数，并且用这样或者那样的方式来修改它的行为。
def mydecorator(a_func):
    @wraps(a_func)  #声明这个注解就可以不重写传入的函数，只是调用的时候wrap一下。不加的话，a_func函数可以看作被重写为wrapTheFunction.
    def wrapTheFunction():
        print(f"function in {id(a_func)} starts...")
        a_func()
        print(f"function in {id(a_func)} ends...")
    return wrapTheFunction

# 在函数定义前加入此注解就可以将函数传入装饰器并包装
@mydecorator
def f():
    print('hi')
    pass

f()
print(f.__name__)

# 带参数的装饰器(实现输出到自定义的日志文件)
from functools import wraps

def logit(logfile='out.log'):
    def mydecorator2(a_func):
        @wraps(a_func)
        def wrapTheFunction(*args, **kwargs):   # 这个保证了函数可以含有任意形参
            log_string = a_func.__name__ + " was called"
            print(log_string)
            # 打开logfile，并写入内容
            with open(logfile, 'a') as opened_file:
                # 现在将日志打到指定的logfile
                opened_file.write(log_string + '\n')
                return a_func(*args, **kwargs)
        return wrapTheFunction
    return mydecorator2

# func group1 
@ logit('out1.log')
def func1(str):
    print(str)
    pass
@ logit('out2.log')
def func2(): pass
            
func1('I have a foul smell')
func2()        

# 带参数的装饰器(实现输出到自定义的日志文件)
from functools import wraps

def logit(logfile='out.log'):
    def mydecorator2(a_func):
        @wraps(a_func)
        def wrapTheFunction(*args, **kwargs):   # 这个保证了函数可以含有任意形参
            log_string = a_func.__name__ + " was called"
            print(log_string)
            # 打开logfile，并写入内容
            with open(logfile, 'a') as opened_file:
                # 现在将日志打到指定的logfile
                opened_file.write(log_string + '\n')
                return a_func(*args, **kwargs)
        return wrapTheFunction
    return mydecorator2

# func group1 
@ logit('out1.log')
def func1(str):
    print(str)
    pass
@ logit('out2.log')
def func2(): pass
            
func1('I have a foul smell')
func2()