python迭代器与生成器详解 python迭代器与生成器详解

def add(s, x):
 return s + x

def gen():
 for i in range(4):
  yield i

base = gen()
for n in [1, 10]:
 base = (add(i, n) for i in base)

print list(base)

In [3]: s = 'hi'

In [4]: s.__getitem__
Out[4]: <method-wrapper '__getitem__' of str object at 0x7f9457eed580>

In [5]: s.next # 没有next方法
---------------------------------------------------------------------------
AttributeError       Traceback (most recent call last)
<ipython-input-5-136d3c11be25> in <module>()
----> 1 s.next

AttributeError: 'str' object has no attribute 'next'

In [6]: l = [1,2] # 同理

In [7]: l.__iter__
Out[7]: <method-wrapper '__iter__' of list object at 0x7f945328c320>

In [8]: l.next
---------------------------------------------------------------------------
AttributeError       Traceback (most recent call last)
<ipython-input-8-c6f8fb94c4cd> in <module>()
----> 1 l.next

AttributeError: 'list' object has no attribute 'next'
In [9]: iter(s) is s #iter() 没有返回本身
Out[9]: False
In [10]: iter(l) is l #同理
Out[10]: False

In [13]: si = iter(s)

In [14]: si
Out[14]: <iterator at 0x7f9453279dd0>

In [15]: si.__iter__ # 有__iter__
Out[15]: <method-wrapper '__iter__' of iterator object at 0x7f9453279dd0>

In [16]: si.next #拥有next
Out[16]: <method-wrapper 'next' of iterator object at 0x7f9453279dd0>

In [20]: si.__iter__() is si #__iter__返回自己
Out[20]: True

In [1]: %paste
class DataIter(object):

 def __init__(self, *args):
  self.data = list(args)
  self.ind = 0

 def __iter__(self): #返回自身
  return self

 def next(self): #　返回数据
  if self.ind == len(self.data):
   raise StopIteration
  else:
   data = self.data[self.ind]
   self.ind += 1
   return data
## -- End pasted text --

In [9]: d = DataIter(1,2)

In [10]: for x in d: #　开始迭代
 ....:  print x
 ....:
1
2

In [13]: d.next() #　只能迭代一次,再次使用则会抛异常
---------------------------------------------------------------------------
StopIteration        Traceback (most recent call last)
----> 1 d.next()
<ipython-input-1-c44abc1904d8> in next(self)
  10  def next(self):
  11   if self.ind == len(self.data):
---> 12    raise StopIteration
  13   else:
  14    data = self.data[self.ind]

class Data(object): # 只是iterable:可迭代对象而不iterator:迭代器

 def __init__(self, *args):
  self.data = list(args)

 def __iter__(self): # 并没有返回自身
  return DataIterator(self)


class DataIterator(object): # iterator: 迭代器

 def __init__(self, data):
  self.data = data.data
  self.ind = 0

 def __iter__(self):
  return self

 def next(self):
  if self.ind == len(self.data):
   raise StopIteration
  else:
   data = self.data[self.ind]
   self.ind += 1
   return data

if __name__ == '__main__':
 d = Data(1, 2, 3)
 for x in d:
  print x,
 for x in d:
  print x,

In [8]: sys.getsizeof(range(1000000))
Out[8]: 8000072

In [9]: sys.getsizeof(xrange(1000000))
Out[9]: 40

def gen():
 print 'begin: generator'
 i = 0
 while True:
  print 'before return ', i
  yield i
  i += 1
  print 'after return ', i

a = gen()

In [10]: a #只是返回一个对象
Out[10]: <generator object gen at 0x7f40c33adfa0>

In [11]: a.next() #开始执行
begin: generator
before return 0
Out[11]: 0

In [12]: a.next()
after return 1
before return 1
Out[12]: 1

In [15]: def func():
 ....:  print 'begin'
 ....:  for i in range(4):
 ....:   yield i

In [16]: a = func()

In [17]: list(a) #检索数据，开始执行
begin
Out[17]: [0, 1, 2, 3]

In [18]: a = ( i for i in range(4))

In [19]: a
Out[19]: <generator object <genexpr> at 0x7f40c2cfe410>

In [20]: a.next()
Out[20]: 0

def multipliers():
 return (lambda x : i * x for i in range(4)) #修改成生成器
print [m(2) for m in multipliers()]

for n in [1, 10]:
 base = (add(i, n) for i in base)