迭代器的性能优势？ [英] Performance Advantages to Iterators?

问题描述

使用迭代器可以提供什么（如果有的话）性能优势。它似乎是解决许多问题的正确方法，但它是否会创建更快/更具记忆意识的代码？我在Python中专门思考，但不限制答案。

What (if any) performance advantages are offered by using iterators. It seems like the 'Right Way' to solve many problems, but does it create faster/more memory-conscious code? I'm thinking specifically in Python, but don't restrict answers to just that.

推荐答案

python邮件列表上有一个非常好的邮件：迭代器与列表。它有点过时（从2003年开始），但据我所知，它仍然有效。

There's actually a very good mail on the python mailing list about this: Iterators vs Lists. It's a bit dated (from 2003), but as far as I know, it's still valid.

以下是摘要：

对于小型数据集，迭代器和基于列表的方法具有类似的
性能。
对于较大的数据集，迭代器可以节省时间和空间。

For small datasets, iterator and list based approaches have similar performance. For larger datasets, iterators save both time and space.

我将从中得出的是：迭代器是如果可能的话，首选将数据加载到列表中。但除非你有一个大的数据集，否则不要扭曲你的代码来制作一个适合列表的东西来处理迭代器。

What I would draw from it is this: iterators are to be preferred over loading data into a list if possible. But unless you have a big dataset, don't contort your code to make something that should fit in a list to work with an iterator.

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