生成器,可迭代對象,迭代器之間到底是什麼關係?
用一幅圖來歸納:spa
1.生成器
定義生成器
方式一:3d
//區別於列表生成式 gen = [x*x for x in range(5)] gen = (x*x for x in range(5)) print(gen) //Out:<generator object <genexpr> at 0x00000258DC5CD8E0>
方式二:code
def fib(): prev, curr = 0, 1 while True: yield curr prev, curr = curr, curr + prev f = fib() print(f) //Out:<generator object fib at 0x00000258DC5CD150>
定義成功後,咱們能夠利用next()訪問生成器下一個元素對象
print(next(gen)) //0 print(next(gen)) //1 ... print(next(gen)) //16 print(next(gen)) //StopIteration
但通常用for循環遍歷圖片
for n in gen: print(n) //0 1 4 9 16
2.迭代器
任何實現了__iter__和__next__()方法的對象都是迭代器。__iter__返回迭代器自身,__next__返回容器中的下一個值。因此生成器是特殊的迭代器,她內部具備這兩種方法。
一個自定義的迭代器以下:generator
class Fib: def __init__(self): self.prev = 0 self.curr = 1 def __iter__(self): return self def __next__(self): value = self.curr self.curr += self.prev self.prev = value return value f = Fib() count = 1 for n in f: print(n) count = count+1 if count>=10: break //Out:1 1 2 3 5 8 13 21 34
3.可迭代對象
像list,tuple,set,dict,str等能夠直接做用於for循環的對象,稱爲可迭代對象。可迭代對象實現了__iter__方法,用於返回迭代器。it
demo = [1,2,3,4] print(isinstance(demo, Iterable)) //True iter_object = iter(demo) print(iter_object) //<list_iterator object at 0x00000258DC5EF748>