如何有效地过滤Python列表推导中的计算值? [英] How do I efficiently filter computed values within a Python list comprehension?

问题描述

Python列表理解语法可轻松过滤理解中的值.例如:

The Python list comprehension syntax makes it easy to filter values within a comprehension. For example:

result = [x**2 for x in mylist if type(x) is int]

将返回mylist中整数平方的列表.但是，如果测试涉及某些(昂贵的)计算并且您想要对结果进行过滤该怎么办?一种选择是:

Will return a list of the squares of integers in mylist. However, what if the test involves some (costly) computation and you want to filter on the result? One option is:

result = [expensive(x) for x in mylist if expensive(x)]

这将导致生成一个非"false"的昂贵(x)值列表，但是对于每个x都会调用一次昂贵()两次.是否有一种理解语法可以让您执行此测试，而每个x仅调用一次昂贵的调用?

This will result in a list of non-"false" expensive(x) values, however expensive() is called twice for each x. Is there a comprehension syntax that allows you to do this test while only calling expensive once per x?

推荐答案

如果计算已经很好地捆绑到函数中，那么如何使用filter和map?

If the calculations are already nicely bundled into functions, how about using filter and map?

result = filter (None, map (expensive, mylist))

如果列表很大，可以使用itertools.imap.

You can use itertools.imap if the list is very large.

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