Python 3.x列表理解VS元组生成器 [英] Python 3.x list comprehension VS tuple generator

问题描述

是否有任何我想使用的内存，速度或其他原因:

tuple(i for i in range(5000))

代替:

[i for i in range(5000)]

如果我不介意元组的不变性

解决方案

基本上，列表理解比生成器表达式快，原因是其迭代在C中执行(请阅读@Veedrac的评论原因).但是，在元组中使用生成器表达式的唯一原因是，您想要对项目执行一些操作和/或过滤它们，更重要的是，您想要元组(因为不可变性及其对可变对象的好处).

毕竟，您始终可以timeit您的代码:

In [10]: %timeit tuple(i for i in range(5000))
1000 loops, best of 3: 325 µs per loop

In [11]: %timeit [i for i in range(5000)]
1000 loops, best of 3: 199 µs per loop

还要注意，正如我提到的那样，如果您想使用理解力，则必须对项目执行操作，否则可以直接在迭代器上调用该函数，这会更快:

In [12]: %timeit list(range(5000))
10000 loops, best of 3: 98.3 µs per loop

Is there any reason for memory, speed or whatever, that I would want to use:

tuple(i for i in range(5000))

instead of:

[i for i in range(5000)]

If I didn't mind the immutability of tuples

解决方案

Basically a list comprehension is faster than a generator expression and as the reason is that its iteration performs in C (Read the @Veedrac's comment for the reason). But the only reason that should use a generator expression within tuple is that you want to perform some operations on your items and/or filter them and more importantly you want a tuple (because of the immutability and its benefits against mutable objects).

After all you can always timeit your code:

In [10]: %timeit tuple(i for i in range(5000))
1000 loops, best of 3: 325 µs per loop

In [11]: %timeit [i for i in range(5000)]
1000 loops, best of 3: 199 µs per loop

Also note that as I mentioned, if you want to use comprehensions you must needed to perform an operation on your items otherwise you can call the function directly on your iterator, which is faster:

In [12]: %timeit list(range(5000))
10000 loops, best of 3: 98.3 µs per loop

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