为什么我不能在python中反转列表列表 [英] why i can't reverse a list of list in python

问题描述

我想做这样的事情，但是这段代码返回None的列表(我认为是因为list.reverse()正在将列表反转到位):

i wanted to do something like this but this code return list of None (i think it's because list.reverse() is reversing the list in place):

map(lambda row: row.reverse(), figure)

我尝试过这个，但是反向返回一个迭代器:

i tried this one, but the reversed return an iterator :

map(reversed, figure)

最后，我做了这样的事情，它对我有用，但是我不知道这是否是正确的解决方案:

finally i did something like this , which work for me , but i don't know if it's the right solution:

def reverse(row):
    """func that reverse a list not in place"""
    row.reverse()
    return row

map(reverse, figure)

如果有人有我不知道的更好的解决方案，请告诉我

if someone has a better solution that i'm not aware of please let me know

亲切的问候，

推荐答案

Python可变容器的 mutator 方法(例如列表的.reverse方法)几乎总是返回None －一些返回一个有用的值，例如.pop方法返回popped元素，但是要保留的关键概念是，这些变异器均未返回变异容器:相反，容器会原位变异 和mutator方法的返回值不是那个容器. (这是 CQS 设计原则的应用-不像它那么狂热，例如，在埃菲尔(Eiffel)中，贝特朗·迈耶(Bertrand Meyer)发明了该语言，他也发明了CQS，但这仅仅是因为在Python中实用性胜过纯度，cfr import this;-).

The mutator methods of Python's mutable containers (such as the .reverse method of lists) almost invariably return None -- a few return one useful value, e.g. the .pop method returns the popped element, but the key concept to retain is that none of those mutators returns the mutated container: rather, the container mutates in-place and the return value of the mutator method is not that container. (This is an application of the CQS principle of design -- not quite as fanatical as, say, in Eiffel, the language devised by Bertrand Meyer, who also invented CQS, but that's just because in Python "practicality beats purity, cfr import this;-).

构建列表通常比仅构建迭代器更为昂贵，因为在绝大多数情况下，您要做的就是对结果进行 loop .因此，诸如reversed(以及itertools模块中所有出色的构建基块)之类的内置函数会返回迭代器，而不是 列表.

Building a list is often costlier than just building an iterator, for the overwhelmingly common case where all you want to do is loop on the result; therefore, built-ins such as reversed (and all the wonderful building blocks in the itertools module) return iterators, not lists.

但是，如果您因此拥有一个迭代器x但确实确实需要等效的 list y怎么办?小菜一碟-只需y = list(x).要创建类型为list的新实例，您可以 call 类型为list-这是Python的一般概念，与我在本文中指出的重要内容相比，保留它甚至更加重要.前两段！-)

But what if you therefore have an iterator x but really truly need the equivalent list y? Piece of cake -- just do y = list(x). To make a new instance of type list, you call type list -- this is such a general Python idea that it's even more crucial to retain than the pretty-important stuff I pointed out in the first two paragraphs!-)

因此，根据前面几段中的关键概念，针对您特定问题的代码非常容易组合在一起:

So, the code for your specific problem is really very easy to put together based on the crucial notions in the previous paragraphs:

[list(reversed(row)) for row in figure]

请注意，我使用的是列表理解，不是 map:根据经验，map仅应在存在时用作最后的优化不需要lambda来构建它(如果涉及到lambda，则listcomp以及往常一样清晰，无论如何也趋于更快！-).

Note that I'm using a list comprehension, not map: as a rule of thumb, map should only be used as a last-ditch optimization when there is no need for a lambda to build it (if a lambda is involved then a listcomp, as well as being clearer as usual, also tends to be faster anyway!-).

一旦您是"Python的过去的高手"，如果您的分析告诉您此代码是瓶颈，那么您就可以知道尝试其他替代方法，例如

Once you're a "past master of Python", if your profiling tells you that this code is a bottleneck, you can then know to try alternatives such as

[row[::-1] for row in figure]

应用负步切片(又称"Martian Smiley")制作行的反向副本，因为它通常比list(reversed(row))方法更快.但是-除非您的代码仅由您自己或至少由Python熟练的人来维护，否则使用最简单的第一原则的代码"方法是一种可取的立场，除非剖析告诉您踩踏板. (我个人认为，"Martian Smiley"非常重要，可以避免将这种良好的通用哲学应用于这种特定的用例，但是，嘿，有理性的人可能在这个非常特定的方面有所不同！！).

applying a negative-step slicing (aka "Martian Smiley") to make reversed copies of the rows, knowing it's usually faster than the list(reversed(row)) approach. But -- unless your code is meant to be maintained only by yourself or somebody at least as skilled at Python -- it's a defensible position to use the simplest "code from first principles" approach except where profiling tells you to push down on the pedal. (Personally I think the "Martian Smiley" is important enough to avoid applying this good general philosophy to this specific use case, but, hey, reasonable people could differ on this very specific point!-).

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