How to use iterators and list comprehensions in Python?

Iterator: Preliminary Study

As mentioned in the previous chapter, in fact, the for loop can be used on any iterable object. In fact, this is true for all iteration tools in Python that scan objects from left to right, including for loops, list comprehensions, in membership tests, and the map built-in function.

The concept of "iterable objects" is quite new in Python. Basically, this is a generalization of the sequence concept: if the object is an actual saved sequence, or it can be used to generate one result at a time in the iteration tool environment Object is considered an iterable.

>>File iterator
As a built-in data type, files are also iterable. It has a method named __next__. Each time it is called, Returns the next line in the file. When the end of the file is reached, __next__ raises the built-in StopIteration exception instead of returning an empty string.

This interface is the so-called iteration protocol in Python: an object with a __next__ method will advance to the next result, and at the end of a series of results, StopIteration will be triggered. Any such object is considered iterable. Any such object can also be iterated over with a for loop or other iteration tool, because all iteration tools internally work by calling __next__ on each iteration and catching the StopIteratin exception to determine when to leave.

Python iterators and list analysis

1)Iterator

 一种特殊的数据结构，以对象形式存在
        >>> i1 = l1.__iter__()
        >>> i1 = iter(l1)
        可迭代对象：
            序列：      list、str、tuple
            非序列:     dict、file
            自定义类：  __iter__()、 __getitem__()
   注意：
         若要实现迭代器，需要在类中定义next()方法
         要使迭代器指向下一个对象，则使用成员函数 next() 
             i1.next()
         当没有元素时，会引发StopIteration异常
         for循环可用于任何可迭代对象
         
         例：   >>> l1 = ['Sun','Mon','Tue','Wed','Thu','Fri','Sat']
                >>> i1 = l1.__iter__()
                >>> il.next()
                'Sun' 
                >>> il.next()
                'Mon'

2)List analysis[ ]

根据已有列表，高效生产新列表的方式。 常用于实现创建新的列表，因此要放置于 [ ] 中
语法：
    [ expression for iter_var in iterable ]
    [ expression for iter_var in iterable if cond_expr ]

    os模块中  listdir() 能够列出所有文件
    例：事先定义l1 l2        l1 = [ 1,2,3,4,5 ]     l2=[ ]                
           >>>  for i in l1:
                   l2.append(i**2)                     l2列表内各项为l1的平方
           >>>  print l2
           [1, 4, 9, 16, 25]

            >>> l3 = [ i**2 for i in l1 ]               l3列表内各项为l1的平方
            [1, 4, 9, 16, 25]
          
            >>> l4 = [ i**2 for i in l1 if i>=3 ]       l3列表内各项为l1中 >= 3的平方
            [9, 16, 25]
            
     例题：  l1 = ['x','y','z']     l2 = [1,2,3]  应用列表解析方法使其各项相乘
            
            >>> l3 = [ (i,j) for  i in l1 for j in l2 ]     for循环内部嵌套一个for循环实现各项乘
            [('x', 1), ('x', 2), ('x', 3), ('y', 1), ('y', 2), ('y', 3), ('z', 1), ('z', 2), ('z', 3)]

3) Generator( )

    惰性计算、延迟求值
    生成器表达式并不真正创建数字列表，而是返回一个生成器对象，此对象在每次计算出一个条目后，把这个条目产生出来（一次返回一个值）
    语法：
        ( expr for iter_var in iterable )
        ( expr for iter_var in iterable  if cond_expr )
    
     例：  >>> l1 = ( i**2 for i in range(2,11,2))
           >>> l1.next()
           2
           >>> l1 = ( i**2 for i in range(2,11) if i%2==0 )
           >>> l1.next()
           2
     注意：
        序列过长，并且每次只获取一个元素时，应当考虑使用生成器表达式而不是列表解析
        列表解析与生成器的关系相当于range()与xrange()

4) produces offset and element

    enumerate
    同时偏移缩印和偏移元素，使用enumerate()函数
    此内置函数返回一个生成器对象
    >>> S = 'Hello,world'
    >>> a = enumerate(S)
    >>> a.next()
    (0,'H')
    >>> a.next()
    (1,'e')

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