問題描述

迭代器和生成器有什么區(qū)別?關(guān)于何時(shí)使用每種情況的一些示例會(huì)很有幫助.

What is the difference between iterators and generators? Some examples for when you would use each case would be helpful.

推薦答案

iterator 是一個(gè)更籠統(tǒng)的概念:任何類具有 __next__ 方法(Python 2 中的 next) 和一個(gè) __iter__ 方法，該方法執(zhí)行 return self.

iterator is a more general concept: any object whose class has a __next__ method (next in Python 2) and an __iter__ method that does return self.

每個(gè)生成器都是一個(gè)迭代器，但反之則不然.生成器是通過調(diào)用具有一個(gè)或多個(gè) yield 表達(dá)式(yield 語句，在 Python 2.5 及更早版本中)的函數(shù)來構(gòu)建的，并且是滿足上一段定義的對(duì)象迭代器.

Every generator is an iterator, but not vice versa. A generator is built by calling a function that has one or more yield expressions (yield statements, in Python 2.5 and earlier), and is an object that meets the previous paragraph's definition of an iterator.

當(dāng)您需要一個(gè)具有某種復(fù)雜的狀態(tài)維護(hù)行為的類，或者想要公開除 __next__ (和 __iter__ 和 __init__).大多數(shù)情況下，一個(gè)生成器(有時(shí)，對(duì)于足夠簡單的需求，一個(gè)生成器表達(dá)式)就足夠了，而且它更容易編碼，因?yàn)闋顟B(tài)維護(hù)(在合理的范圍內(nèi))基本上是為你完成"的.由框架暫停和恢復(fù).

You may want to use a custom iterator, rather than a generator, when you need a class with somewhat complex state-maintaining behavior, or want to expose other methods besides __next__ (and __iter__ and __init__). Most often, a generator (sometimes, for sufficiently simple needs, a generator expression) is sufficient, and it's simpler to code because state maintenance (within reasonable limits) is basically "done for you" by the frame getting suspended and resumed.

例如生成器如:

def squares(start, stop):
    for i in range(start, stop):
        yield i * i

generator = squares(a, b)

或等效的生成器表達(dá)式(genexp)

or the equivalent generator expression (genexp)

generator = (i*i for i in range(a, b))

需要更多代碼來構(gòu)建自定義迭代器:

would take more code to build as a custom iterator:

class Squares(object):
    def __init__(self, start, stop):
       self.start = start
       self.stop = stop
    def __iter__(self): return self
    def __next__(self): # next in Python 2
       if self.start >= self.stop:
           raise StopIteration
       current = self.start * self.start
       self.start += 1
       return current

iterator = Squares(a, b)

但是，當(dāng)然，使用類 Squares 您可以輕松地提供額外的方法，即

But, of course, with class Squares you could easily offer extra methods, i.e.

    def current(self):
       return self.start

如果您對(duì)應(yīng)用程序中的此類額外功能有任何實(shí)際需求.

if you have any actual need for such extra functionality in your application.

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