1.经典迭代器
import re
RE_WORD = re.compile('\w+')
class Sentence:
def __init__(self, text):
self.text = text
self.words = RE_WORD.findall(text)
def __iter__(self): # <1>
return SentenceIterator(self.words) # <2>
class SentenceIterator:
def __init__(self, words):
self.words = words # <3>
self.index = 0 # <4>
def __next__(self):
try:
word = self.words[self.index] # <5>
except IndexError:
raise StopIteration() # <6>
self.index += 1 # <7>
return word # <8>
def __iter__(self): # <9>
return self
def main():
s = Sentence('hello all')
for word in s: #隐式调用iter(s),加入s存在__iter__则调用返回迭代器，否则若s存在__getitem__，则默认生成迭代器，调用__getitem__生成元素
print(word)
if __name__ == '__main__':
main() 
2.将Sentence中的__iter__改成生成器函数
def __iter__(self):
for word in self.words:
yield word #yield为生成器关键字改成生成器后用法不变，但更加简洁。
3.惰性实现
当列表比较大，占内存较大时，我们可以采用惰性实现，每次只读取一个元素到内存。
def __iter__(self):
for match in RE_WORD.finditer(self.text):
yield match.group()
或者使用更简洁的生成器表达式
def __iter__(self):
return (match.group() for match in RE_WORD.finditer(self.text))4.yield from
itertools模块含有大量生成器函数可供利用
def chain(*iterables):
for it in iterables:
for i in it:
yield i等价于
def chain(*iterables):
for it in iterables:
yield from it
