现在是一些更优雅的东西(pythonic)

-只要碰一下

有很多实现，虽然有些已经接近，但没有一个能完全捕获现代python所提供的优雅。

使用python测试(3.5.1) 包含了一个额外的列表，以演示当 数字在字符串中间 没有测试，但是，我假设如果您的列表是相当大的，那么事先编译正则表达式会更有效 如果这是一个错误的假设，我相信有人会纠正我

罢工

from re import compile, split    
dre = compile(r'(\d+)')
mylist.sort(key=lambda l: [int(s) if s.isdigit() else s.lower() for s in split(dre, l)])

完整代码

#!/usr/bin/python3
# coding=utf-8
"""
Natural-Sort Test
"""

from re import compile, split

dre = compile(r'(\d+)')
mylist = ['elm0', 'elm1', 'Elm2', 'elm9', 'elm10', 'Elm11', 'Elm12', 'elm13', 'elm']
mylist2 = ['e0lm', 'e1lm', 'E2lm', 'e9lm', 'e10lm', 'E12lm', 'e13lm', 'elm', 'e01lm']

mylist.sort(key=lambda l: [int(s) if s.isdigit() else s.lower() for s in split(dre, l)])
mylist2.sort(key=lambda l: [int(s) if s.isdigit() else s.lower() for s in split(dre, l)])

print(mylist)  
  # ['elm', 'elm0', 'elm1', 'Elm2', 'elm9', 'elm10', 'Elm11', 'Elm12', 'elm13']
print(mylist2)  
  # ['e0lm', 'e1lm', 'e01lm', 'E2lm', 'e9lm', 'e10lm', 'E12lm', 'e13lm', 'elm']

使用时注意

从操作系统。路径导入分割 您需要区分导入

灵感来自

Python文档-如何排序 人类排序:自然排序顺序 人的分类 这篇文章的贡献者/评论员和引用帖子

基于这里的答案，我写了一个natural_sorted函数，它的行为类似于内置函数的排序:

# Copyright (C) 2018, Benjamin Drung <bdrung@posteo.de>
#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
# OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.

import re

def natural_sorted(iterable, key=None, reverse=False):
    """Return a new naturally sorted list from the items in *iterable*.

    The returned list is in natural sort order. The string is ordered
    lexicographically (using the Unicode code point number to order individual
    characters), except that multi-digit numbers are ordered as a single
    character.

    Has two optional arguments which must be specified as keyword arguments.

    *key* specifies a function of one argument that is used to extract a
    comparison key from each list element: ``key=str.lower``.  The default value
    is ``None`` (compare the elements directly).

    *reverse* is a boolean value.  If set to ``True``, then the list elements are
    sorted as if each comparison were reversed.

    The :func:`natural_sorted` function is guaranteed to be stable. A sort is
    stable if it guarantees not to change the relative order of elements that
    compare equal --- this is helpful for sorting in multiple passes (for
    example, sort by department, then by salary grade).
    """
    prog = re.compile(r"(\d+)")

    def alphanum_key(element):
        """Split given key in list of strings and digits"""
        return [int(c) if c.isdigit() else c for c in prog.split(key(element)
                if key else element)]

    return sorted(iterable, key=alphanum_key, reverse=reverse)

源代码也可以在我的GitHub片段存储库: https://github.com/bdrung/snippets/blob/master/natural_sorted.py

让我就这一需求提出自己的看法:

from typing import Tuple, Union, Optional, Generator


StrOrInt = Union[str, int]


# On Python 3.6, string concatenation is REALLY fast
# Tested myself, and this fella also tested:
# https://blog.ganssle.io/articles/2019/11/string-concat.html
def griter(s: str) -> Generator[StrOrInt, None, None]:
    last_was_digit: Optional[bool] = None
    cluster: str = ""
    for c in s:
        if last_was_digit is None:
            last_was_digit = c.isdigit()
            cluster += c
            continue
        if c.isdigit() != last_was_digit:
            if last_was_digit:
                yield int(cluster)
            else:
                yield cluster
            last_was_digit = c.isdigit()
            cluster = ""
        cluster += c
    if last_was_digit:
        yield int(cluster)
    else:
        yield cluster
    return


def grouper(s: str) -> Tuple[StrOrInt, ...]:
    return tuple(griter(s))

现在如果我们有这样的列表:

filelist = [
    'File3', 'File007', 'File3a', 'File10', 'File11', 'File1', 'File4', 'File5',
    'File9', 'File8', 'File8b1', 'File8b2', 'File8b11', 'File6'
]

我们可以简单地使用key= kwarg来进行自然排序:

>>> sorted(filelist, key=grouper)
['File1', 'File3', 'File3a', 'File4', 'File5', 'File6', 'File007', 'File8', 
'File8b1', 'File8b2', 'File8b11', 'File9', 'File10', 'File11']

当然，这里的缺点是，就像现在一样，该函数将对大写字母在小写字母之前进行排序。

我将把不区分大小写的grouper的实现留给读者:-)

很可能functools.cmp_to_key()与python的sort的底层实现密切相关。此外，cmp参数是遗留的。现代的方法是将输入项转换为支持所需的丰富比较操作的对象。

在CPython 2下。X，即使没有实现各自的富比较操作符，也可以对不同类型的对象排序。在CPython 3下。X，不同类型的对象必须显式地支持比较。参见Python如何比较字符串和int?链接到官方文件。大多数答案都依赖于这种隐含的顺序。切换到Python 3。X将需要一个新的类型来实现和统一数字和字符串之间的比较。

Python 2.7.12 (default, Sep 29 2016, 13:30:34) 
>>> (0,"foo") < ("foo",0)
True  

Python 3.5.2 (default, Oct 14 2016, 12:54:53) 
>>> (0,"foo") < ("foo",0)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  TypeError: unorderable types: int() < str()

有三种不同的方法。第一种使用嵌套类来利用Python的Iterable比较算法。第二个函数将这个嵌套展开到单个类中。第三种方法放弃了str的子类化，专注于性能。所有都是有时间的;第二辆快了一倍，第三辆快了近六倍。对str进行子类化并不是必需的，而且首先可能是一个坏主意，但它确实带来了某些便利。

排序字符被复制以强制按大小写排序，并交换大小写以强制小写字母优先排序;这就是“自然排序”的典型定义。我无法决定分组的类型;有些人可能更喜欢以下选项，这也会带来显著的性能优势:

d = lambda s: s.lower()+s.swapcase()

在使用的地方，比较运算符被设置为object的运算符，这样它们就不会被functools. total_orders忽略。

import functools
import itertools


@functools.total_ordering
class NaturalStringA(str):
    def __repr__(self):
        return "{}({})".format\
            ( type(self).__name__
            , super().__repr__()
            )
    d = lambda c, s: [ c.NaturalStringPart("".join(v))
                        for k,v in
                       itertools.groupby(s, c.isdigit)
                     ]
    d = classmethod(d)
    @functools.total_ordering
    class NaturalStringPart(str):
        d = lambda s: "".join(c.lower()+c.swapcase() for c in s)
        d = staticmethod(d)
        def __lt__(self, other):
            if not isinstance(self, type(other)):
                return NotImplemented
            try:
                return int(self) < int(other)
            except ValueError:
                if self.isdigit():
                    return True
                elif other.isdigit():
                    return False
                else:
                    return self.d(self) < self.d(other)
        def __eq__(self, other):
            if not isinstance(self, type(other)):
                return NotImplemented
            try:
                return int(self) == int(other)
            except ValueError:
                if self.isdigit() or other.isdigit():
                    return False
                else:
                    return self.d(self) == self.d(other)
        __le__ = object.__le__
        __ne__ = object.__ne__
        __gt__ = object.__gt__
        __ge__ = object.__ge__
    def __lt__(self, other):
        return self.d(self) < self.d(other)
    def __eq__(self, other):
        return self.d(self) == self.d(other)
    __le__ = object.__le__
    __ne__ = object.__ne__
    __gt__ = object.__gt__
    __ge__ = object.__ge__

import functools
import itertools


@functools.total_ordering
class NaturalStringB(str):
    def __repr__(self):
        return "{}({})".format\
            ( type(self).__name__
            , super().__repr__()
            )
    d = lambda s: "".join(c.lower()+c.swapcase() for c in s)
    d = staticmethod(d)
    def __lt__(self, other):
        if not isinstance(self, type(other)):
            return NotImplemented
        groups = map(lambda i: itertools.groupby(i, type(self).isdigit), (self, other))
        zipped = itertools.zip_longest(*groups)
        for s,o in zipped:
            if s is None:
                return True
            if o is None:
                return False
            s_k, s_v = s[0], "".join(s[1])
            o_k, o_v = o[0], "".join(o[1])
            if s_k and o_k:
                s_v, o_v = int(s_v), int(o_v)
                if s_v == o_v:
                    continue
                return s_v < o_v
            elif s_k:
                return True
            elif o_k:
                return False
            else:
                s_v, o_v = self.d(s_v), self.d(o_v)
                if s_v == o_v:
                    continue
                return s_v < o_v
        return False
    def __eq__(self, other):
        if not isinstance(self, type(other)):
            return NotImplemented
        groups = map(lambda i: itertools.groupby(i, type(self).isdigit), (self, other))
        zipped = itertools.zip_longest(*groups)
        for s,o in zipped:
            if s is None or o is None:
                return False
            s_k, s_v = s[0], "".join(s[1])
            o_k, o_v = o[0], "".join(o[1])
            if s_k and o_k:
                s_v, o_v = int(s_v), int(o_v)
                if s_v == o_v:
                    continue
                return False
            elif s_k or o_k:
                return False
            else:
                s_v, o_v = self.d(s_v), self.d(o_v)
                if s_v == o_v:
                    continue
                return False
        return True
    __le__ = object.__le__
    __ne__ = object.__ne__
    __gt__ = object.__gt__
    __ge__ = object.__ge__

import functools
import itertools
import enum


class OrderingType(enum.Enum):
    PerWordSwapCase         = lambda s: s.lower()+s.swapcase()
    PerCharacterSwapCase    = lambda s: "".join(c.lower()+c.swapcase() for c in s)


class NaturalOrdering:
    @classmethod
    def by(cls, ordering):
        def wrapper(string):
            return cls(string, ordering)
        return wrapper
    def __init__(self, string, ordering=OrderingType.PerCharacterSwapCase):
        self.string = string
        self.groups = [ (k,int("".join(v)))
                            if k else
                        (k,ordering("".join(v)))
                            for k,v in
                        itertools.groupby(string, str.isdigit)
                      ]
    def __repr__(self):
        return "{}({})".format\
            ( type(self).__name__
            , self.string
            )
    def __lesser(self, other, default):
        if not isinstance(self, type(other)):
            return NotImplemented
        for s,o in itertools.zip_longest(self.groups, other.groups):
            if s is None:
                return True
            if o is None:
                return False
            s_k, s_v = s
            o_k, o_v = o
            if s_k and o_k:
                if s_v == o_v:
                    continue
                return s_v < o_v
            elif s_k:
                return True
            elif o_k:
                return False
            else:
                if s_v == o_v:
                    continue
                return s_v < o_v
        return default
    def __lt__(self, other):
        return self.__lesser(other, default=False)
    def __le__(self, other):
        return self.__lesser(other, default=True)
    def __eq__(self, other):
        if not isinstance(self, type(other)):
            return NotImplemented
        for s,o in itertools.zip_longest(self.groups, other.groups):
            if s is None or o is None:
                return False
            s_k, s_v = s
            o_k, o_v = o
            if s_k and o_k:
                if s_v == o_v:
                    continue
                return False
            elif s_k or o_k:
                return False
            else:
                if s_v == o_v:
                    continue
                return False
        return True
    # functools.total_ordering doesn't create single-call wrappers if both
    # __le__ and __lt__ exist, so do it manually.
    def __gt__(self, other):
        op_result = self.__le__(other)
        if op_result is NotImplemented:
            return op_result
        return not op_result
    def __ge__(self, other):
        op_result = self.__lt__(other)
        if op_result is NotImplemented:
            return op_result
        return not op_result
    # __ne__ is the only implied ordering relationship, it automatically
    # delegates to __eq__

>>> import natsort
>>> import timeit
>>> l1 = ['Apple', 'corn', 'apPlE', 'arbour', 'Corn', 'Banana', 'apple', 'banana']
>>> l2 = list(map(str, range(30)))
>>> l3 = ["{} {}".format(x,y) for x in l1 for y in l2]
>>> print(timeit.timeit('sorted(l3+["0"], key=NaturalStringA)', number=10000, globals=globals()))
362.4729259099986
>>> print(timeit.timeit('sorted(l3+["0"], key=NaturalStringB)', number=10000, globals=globals()))
189.7340817489967
>>> print(timeit.timeit('sorted(l3+["0"], key=NaturalOrdering.by(OrderingType.PerCharacterSwapCase))', number=10000, globals=globals()))
69.34636392899847
>>> print(timeit.timeit('natsort.natsorted(l3+["0"], alg=natsort.ns.GROUPLETTERS | natsort.ns.LOWERCASEFIRST)', number=10000, globals=globals()))
98.2531585780016

自然排序既相当复杂，又定义模糊。不要忘记事先运行unicodedata.normalize(…)，并考虑使用str.casefold()而不是str.lower()。可能有一些微妙的编码问题我还没有考虑到。因此，我尝试性地推荐natsort库。我快速浏览了一下github存储库;代码维护非常出色。

All the algorithms I've seen depend on tricks such as duplicating and lowering characters, and swapping case. While this doubles the running time, an alternative would require a total natural ordering on the input character set. I don't think this is part of the unicode specification, and since there are many more unicode digits than [0-9], creating such a sorting would be equally daunting. If you want locale-aware comparisons, prepare your strings with locale.strxfrm per Python's Sorting HOW TO.

我写了一个基于http://www.codinghorror.com/blog/2007/12/sorting-for-humans-natural-sort-order.html的函数，它增加了传递自己的“键”参数的能力。我需要这样才能执行包含更复杂对象(不仅仅是字符串)的列表的自然排序。

import re

def natural_sort(list, key=lambda s:s):
    """
    Sort the list into natural alphanumeric order.
    """
    def get_alphanum_key_func(key):
        convert = lambda text: int(text) if text.isdigit() else text 
        return lambda s: [convert(c) for c in re.split('([0-9]+)', key(s))]
    sort_key = get_alphanum_key_func(key)
    list.sort(key=sort_key)

例如:

my_list = [{'name':'b'}, {'name':'10'}, {'name':'a'}, {'name':'1'}, {'name':'9'}]
natural_sort(my_list, key=lambda x: x['name'])
print my_list
[{'name': '1'}, {'name': '9'}, {'name': '10'}, {'name': 'a'}, {'name': 'b'}]

data = ['elm13', 'elm9', 'elm0', 'elm1', 'Elm11', 'Elm2', 'elm10']

让我们分析一下数据。所有元素的数字容量为2。在常见的字面部分“elm”中有3个字母。

所以，元素的最大长度是5。我们可以增加这个值以确保(例如，增加到8)。

记住这一点，我们有一个简单的解决方案:

data.sort(key=lambda x: '{0:0>8}'.format(x).lower())

没有正则表达式和外部库!

print(data)

>>> ['elm0', 'elm1', 'Elm2', 'elm9', 'elm10', 'Elm11', 'elm13']

解释:

for elm in data:
    print('{0:0>8}'.format(elm).lower())

>>>
0000elm0
0000elm1
0000elm2
0000elm9
000elm10
000elm11
000elm13