Python中的enumerate是惰性的吗?
我想知道当我把一个生成器函数的结果传给Python的enumerate()时,会发生什么。比如:
def veryBigHello():
i = 0
while i < 10000000:
i += 1
yield "hello"
numbered = enumerate(veryBigHello())
for i, word in numbered:
print i, word
这个enumerate是懒惰地迭代,还是会先把所有东西都装进<enumerate object>
里?我99.999%确定是懒惰的,所以我可以像对待生成器函数一样对待它吗,还是说我需要注意什么?
4 个回答
15
因为你可以在不出现内存溢出错误的情况下调用这个函数,所以它肯定是懒惰的。
def veryBigHello():
i = 0
while i < 1000000000000000000000000000:
yield "hello"
numbered = enumerate(veryBigHello())
for i, word in numbered:
print i, word
56
其实比之前的建议还要简单:
$ python
Python 2.5.5 (r255:77872, Mar 15 2010, 00:43:13)
[GCC 4.3.4 20090804 (release) 1] on cygwin
Type "help", "copyright", "credits" or "license" for more information.
>>> abc = (letter for letter in 'abc')
>>> abc
<generator object at 0x7ff29d8c>
>>> numbered = enumerate(abc)
>>> numbered
<enumerate object at 0x7ff29e2c>
如果 enumerate 不是懒惰求值的话,它会返回 [(0,'a'), (1,'b'), (2,'c')]
或者一些(几乎)相同的结果。
当然,enumerate 实际上只是一个很酷的生成器:
def myenumerate(iterable):
count = 0
for _ in iterable:
yield (count, _)
count += 1
for i, val in myenumerate((letter for letter in 'abc')):
print i, val
132
这很懒惰。其实很容易证明这一点:
>>> def abc():
... letters = ['a','b','c']
... for letter in letters:
... print letter
... yield letter
...
>>> numbered = enumerate(abc())
>>> for i, word in numbered:
... print i, word
...
a
0 a
b
1 b
c
2 c