python中的generator, iterator, iterabel

先来看看如果遇到一个对象，如何判断其是否是这三种类型：

 from types import GeneratorType
 from collectiuons import Iterable, Iterator

 isinstance( xx, GeneratorType )
 isinstance( xx, Iterable )
 isinstance( xx, Iterator )

生成器对象：

　　生成器是一个通过yield关键字构建的函数，其返回一个generator对象，同时其又是一个iterator对象，因为其实现了__iter__与next方法

In[4]: def gene(k):
...     for i in xrange(0, k):
...         yield i
...
In[5]: ge = gene(6)
In[6]: type(ge)
Out[6]: generator
In[8]: dir(ge)
Out[8]: [ ...,'__iter__', 'next', ... ]
In[9]: isinstance(ge, collections.Iterator)
Out[9]: True

　　生成器的一个特点是只能用一次

In[11]: for i in ge:
...     print i
...
0
1
2
3
4
5
In[12]: ge.next()
Traceback (most recent call last):
  File "/usr/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2820, in run_code
    exec code_obj in self.user_global_ns, self.user_ns
  File "<ipython-input-12-b9172cd6050f>", line 1, in <module>
    ge.next()
StopIteration

迭代器对象：

　　实现了__iter__与__next__方法的对象。

　　__iter__返回一个实例作为最终使用的iterator对象--for...in...语句初始化时使用，next方法是后面每次迭代iterator对象时调用的方法

class Counter(object):
    def __init__(self, low, high):
        self.current = low
        self.high = high

    def __iter__(self):
        # 'Returns itself as an iterator object'
        return self

    def next(self):
        # 'Returns the next value till current is lower than high'
        if self.current > self.high:
            raise StopIteration
        else:
            self.current += 1
            return self.current - 1

>>> c = Counter(5,10)
>>> for i in c:
...   print(i, end=' ')
...
5 6 7 8 9 10
>>> for i in c:
...　　pritn i
...
# 无输出
>>> c.next()

Traceback (most recent call last):
  File "<ipython-input-12-b9172cd6050f>"
    c.next()
StopIteration

可迭代对象：

　　可迭代对象就是用于for...in...循环的

　　不同于上面两种，其需要可以多次for...in...使用

　　通过generator写可迭代对象：

　　将__iter__写成生成器函数。注意for...in...时初始化时调用__iter__函数使得counter为low, 而后执行的都是yield所影响区域的了^【1】，除非下次再执行for...in...语句才会调用到counter初始化那句，这样也就实现了复用。但是有个问题是此时Counter的实例就既不是generator也不是iterator对象了。故其也没法调用next方法

class Counter(object):
    def __init__(self, low, high):
        self.low = low
        self.high = high

    def __iter__(self):
        counter = self.low
        while self.high >= counter:
            yield counter
            counter += 1

obj = Counter(5, 10)
print isinstance(obj, Iterator)
print isinstance(obj, GeneratorType)
print type(obj)
for i in obj:
    print i
obj.next()

False
False
<class '__main__.Counter'>
5
6
7
8
9
10

Traceback (most recent call last):
File "/home/pd/..."
obj.next()
AttributeError: 'Counter' object has no attribute 'next'

注释【1】：

In [1]: def gener(k):
   ...:     print "====initial===="
   ...:     for i in range(0, k):
   ...:         print "before yield"
   ...:         yield i
   ...:         print "after yield"
   ...:     print "*****end******"
   ...:                                                                          

In [2]: g = gener(3)
In [3]: for i in g:
   ...:     print g
   ...:
====initial====
before yield
<generator object gener at 0x7fbc8d15e870>
after yield
before yield
<generator object gener at 0x7fbc8d15e870>
after yield
before yield
<generator object gener at 0x7fbc8d15e870>
after yield
*****end****** 

补充：

　　关于generator的yield与send：

　　总的来说：yield返回的是个generator对象，send是向generator输送值

 In [35]: def gen():
     ...:     while True:
     ...:         print("before x_yield")
     ...:         x=yield
     ...:         print("after x_yield:", x)
     ...:         yield x*2
     ...:         print("after yield")
     ...:
     ...:       

 In [36]: g = gen()

 In [37]: g.send(10)
 ---------------------------------------------------------------------------
 TypeError                                 Traceback (most recent call last)
 <ipython-input-37-98b613a2ec82> in <module>()
 ----> 1 g.send(10)

 TypeError: can't send non-None value to a just-started generator

 In [38]: g.__next__(10)
 ---------------------------------------------------------------------------
 TypeError                                 Traceback (most recent call last)
 <ipython-input-38-bc5eb41f1cb6> in <module>()
 ----> 1 g.__next__(10)

 TypeError: expected 0 arguments, got 1

 In [39]: g.__next__()
 before x_yield
 # 由上可知， “x=yield”中的yield也会成为__next__()调用的终点，也就是说如果上面要两个__next__()才能走完。 
31 # 通过实验发现，其实x=yield的执行并不是同时的，比如send（10），此时相当于到达了x=yield中的yield，而此时再执行send（11）才会执行x=yield这个赋值操作
31 # 所以输出是22而不是第一次就能传入的20【见43，44的输出】

 In [40]: g.send(10)
 after x_yield: 10
 Out[40]: 20                         # 进行到yield x*2

 In [41]: g.__next__()
 after yield
 before x_yield

 In [42]: g.send(10)
 after x_yield: 10
 Out[42]: 20

 In [43]: g.send(10)              #
 after yield
 before x_yield

 In [44]: g.send(11)
 after x_yield: 11
 Out[44]: 22

补充：关于send与__next__()

 In [71]: def gen():
     ...:     print("enhen")
     ...:     while True:
     ...:         print("before yield")
     ...:         yield "pd the handsome"
     ...:         print("afer yield")
     ...:         

 In [72]: g=gen()

 In [73]: g.send(10)
 ---------------------------------------------------------------------------
 TypeError                                 Traceback (most recent call last)
 <ipython-input-73-98b613a2ec82> in <module>()
 ----> 1 g.send(10)

 TypeError: can't send non-None value to a just-started generator

 In [74]: g.__next__()
 enhen
 before yield
 Out[74]: 'pd the handsome'
 # 由上可见，send(xx)并不能用于初始化调用generator, 但是通过 send(None)其实可以，纯粹的相当于74的调用__next__（）
 # 可见，send方法实际也调用了__next__()从而执行到了下一次的yield
 In [75]: g.send(10)
 afer yield
 before yield
 Out[75]: 'pd the handsome'

 In [76]: g.send(20)
 afer yield
 before yield
 Out[76]: 'pd the handsome'

补充：用send实现协程【来源：寥雪峰】

 def consumer():
     r = ''
     while True:
         n = yield r
         if not n:
             return
         print('[CONSUMER] Consuming %s...' % n)
         r = '200 OK'

 def produce(c):
     c.send(None)
     n = 0
     while n < 5:
         n = n + 1
         print('[PRODUCER] Producing %s...' % n)
         r = c.send(n)        // 执行一次c
         print('[PRODUCER] Consumer return: %s' % r)
     c.close()

 c = consumer()
 produce(c)

 执行结果：

 [PRODUCER] Producing 1...
 [CONSUMER] Consuming 1...
 [PRODUCER] Consumer return: 200 OK
 [PRODUCER] Producing 2...
 [CONSUMER] Consuming 2...
 [PRODUCER] Consumer return: 200 OK
 [PRODUCER] Producing 3...
 [CONSUMER] Consuming 3...
 [PRODUCER] Consumer return: 200 OK
 [PRODUCER] Producing 4...
 [CONSUMER] Consuming 4...
 [PRODUCER] Consumer return: 200 OK
 [PRODUCER] Producing 5...
 [CONSUMER] Consuming 5...
 [PRODUCER] Consumer return: 200 OK

挺叼，传入个generator做操作！

补充：关于yield from :http://simeonvisser.com/posts/python-3-using-yield-from-in-generators-part-1.html

参考：

　　http://pymbook.readthedocs.io/en/latest/igd.html

一篇关于yield的好文：

　　http://stackoverflow.com/questions/231767/what-does-the-yield-keyword-do?rq=1