>>> import re
>>> sorted(lst, key=lambda x: int(re.findall(r'\d+$', x)[0]))
['elm0', 'elm1', 'Elm2', 'elm9', 'elm10', 'Elm11', 'Elm12', 'elm13']

考虑到:

data = ['Elm11', 'Elm12', 'Elm2', 'elm0', 'elm1', 'elm10', 'elm13', 'elm9']

类似于SergO的解决方案，没有外部库的1-liner将是:

data.sort(key=lambda x: int(x[3:]))

or

sorted_data = sorted(data, key=lambda x: int(x[3:]))

解释:

该解决方案使用sort的关键特性来定义将用于排序的函数。因为我们知道每个数据条目前面都有'elm'，排序函数将字符串中第三个字符之后的部分(即int(x[3:]))转换为整数。如果数据的数值部分在不同的位置，那么函数的这部分将不得不改变。

下面是马克·拜尔回答的一个更加python化的版本:

import re

def natural_sort_key(s, _nsre=re.compile('([0-9]+)')):
    return [int(text) if text.isdigit() else text.lower()
            for text in _nsre.split(s)]

现在这个函数可以在任何使用它的函数中用作键，比如list。Sort, sorted, max，等等。

作为lambda:

lambda s: [int(t) if t.isdigit() else t.lower() for t in re.split('(\d+)', s)]

完全可重复的演示代码:

import re
natsort = lambda s: [int(t) if t.isdigit() else t.lower() for t in re.split('(\d+)', s)]
L = ["a1", "a10", "a11", "a2", "a22", "a3"]   
print(sorted(L, key=natsort))  
# ['a1', 'a2', 'a3', 'a10', 'a11', 'a22'] 

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'}]

为了记录，下面是Mark Byers的简单解决方案的另一个变体，类似于Walter Tross建议的解决方案，避免调用isdigit()。这不仅使它更快，而且还避免了可能发生的问题，因为与regex \d+相比，isdigit()将更多的unicode字符视为数字。

import re
from itertools import cycle

_re_digits = re.compile(r"(\d+)")


def natural_comparison_key(key):
    return tuple(
        int(part) if is_digit else part
        for part, is_digit in zip(_re_digits.split(key), cycle((False, True)))
    )

一个紧凑的解决方案，基于将字符串转换为List[Tuple(str, int)]。

Code

def string_to_pairs(s, pairs=re.compile(r"(\D*)(\d*)").findall):
    return [(text.lower(), int(digits or 0)) for (text, digits) in pairs(s)[:-1]]

示范

sorted(['Elm11', 'Elm12', 'Elm2', 'elm0', 'elm1', 'elm10', 'elm13', 'elm9'], key=string_to_pairs)

输出:

['elm0', 'elm1', 'Elm2', 'elm9', 'elm10', 'Elm11', 'Elm12', 'elm13']

测试

转换

assert string_to_pairs("") == []
assert string_to_pairs("123") == [("", 123)]
assert string_to_pairs("abc") == [("abc", 0)]
assert string_to_pairs("123abc") == [("", 123), ("abc", 0)]
assert string_to_pairs("abc123") == [("abc", 123)]
assert string_to_pairs("123abc456") == [("", 123), ("abc", 456)]
assert string_to_pairs("abc123efg") == [("abc", 123), ("efg", 0)]

排序

# Some extracts from the test suite of the natsort library. Permalink:
# https://github.com/SethMMorton/natsort/blob/e3c32f5638bf3a0e9a23633495269bea0e75d379/tests/test_natsorted.py

sort_data = [
    (  # same as test_natsorted_can_sort_as_unsigned_ints_which_is_default()
        ["a50", "a51.", "a50.31", "a-50", "a50.4", "a5.034e1", "a50.300"],
        ["a5.034e1", "a50", "a50.4", "a50.31", "a50.300", "a51.", "a-50"],
    ),
    (  # same as test_natsorted_numbers_in_ascending_order()
        ["a2", "a5", "a9", "a1", "a4", "a10", "a6"],
        ["a1", "a2", "a4", "a5", "a6", "a9", "a10"],
    ),
    (  # same as test_natsorted_can_sort_as_version_numbers()
        ["1.9.9a", "1.11", "1.9.9b", "1.11.4", "1.10.1"],
        ["1.9.9a", "1.9.9b", "1.10.1", "1.11", "1.11.4"],
    ),
    (  # different from test_natsorted_handles_filesystem_paths()
        [
            "/p/Folder (10)/file.tar.gz",
            "/p/Folder (1)/file (1).tar.gz",
            "/p/Folder/file.x1.9.tar.gz",
            "/p/Folder (1)/file.tar.gz",
            "/p/Folder/file.x1.10.tar.gz",
        ],
        [
            "/p/Folder (1)/file (1).tar.gz",
            "/p/Folder (1)/file.tar.gz",
            "/p/Folder (10)/file.tar.gz",
            "/p/Folder/file.x1.9.tar.gz",
            "/p/Folder/file.x1.10.tar.gz",
        ],
    ),
    (  # same as test_natsorted_path_extensions_heuristic()
        [
            "Try.Me.Bug - 09 - One.Two.Three.[text].mkv",
            "Try.Me.Bug - 07 - One.Two.5.[text].mkv",
            "Try.Me.Bug - 08 - One.Two.Three[text].mkv",
        ],
        [
            "Try.Me.Bug - 07 - One.Two.5.[text].mkv",
            "Try.Me.Bug - 08 - One.Two.Three[text].mkv",
            "Try.Me.Bug - 09 - One.Two.Three.[text].mkv",
        ],
    ),
    (  # same as ns.IGNORECASE for test_natsorted_supports_case_handling()
        ["Apple", "corn", "Corn", "Banana", "apple", "banana"],
        ["Apple", "apple", "Banana", "banana", "corn", "Corn"],
    ),

]

for (given, expected) in sort_data:
    assert sorted(given, key=string_to_pairs) == expected

奖金

如果字符串混合了非ascii文本和数字，您可能会对将string_to_pairs()与我在其他地方给出的函数remove_diacritics()组合感兴趣。