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。

试试这个:

import re

def natural_sort(l): 
    convert = lambda text: int(text) if text.isdigit() else text.lower()
    alphanum_key = lambda key: [convert(c) for c in re.split('([0-9]+)', key)]
    return sorted(l, key=alphanum_key)

输出:

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

代码改编自这里:排序人类:自然排序顺序。

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。

我建议您简单地使用关键字参数sorted来实现所需的列表 例如:

to_order= [e2,E1,e5,E4,e3]
ordered= sorted(to_order, key= lambda x: x.lower())
    # ordered should be [E1,e2,e3,E4,e5]

我使用的算法是padzero_with_lower，定义如下:

import re

def padzero_with_lower(s):
    return re.sub(r'\d+', lambda m: m.group(0).rjust(10, '0'), s).lower()

该算法发现:

查找并填充任意长度的数字，直到足够大的长度，例如10 然后，它将字符串转换为小写

下面是一个用法示例:

print(padzero_with_lower('file1.txt'))   # file0000000001.txt
print(padzero_with_lower('file12.txt'))  # file0000000012.txt
print(padzero_with_lower('file23.txt'))  # file0000000023.txt
print(padzero_with_lower('file123.txt')) # file0000000123.txt
print(padzero_with_lower('file301.txt')) # file0000000301.txt
print(padzero_with_lower('Dir2/file15.txt'))  # dir0000000002/file0000000015.txt
print(padzero_with_lower('dir2/file123.txt')) # dir0000000002/file0000000123.txt
print(padzero_with_lower('dir15/file2.txt'))  # dir0000000015/file0000000002.txt
print(padzero_with_lower('Dir15/file15.txt')) # dir0000000015/file0000000015.txt
print(padzero_with_lower('elm0'))  # elm0000000000
print(padzero_with_lower('elm1'))  # elm0000000001
print(padzero_with_lower('Elm2'))  # elm0000000002
print(padzero_with_lower('elm9'))  # elm0000000009
print(padzero_with_lower('elm10')) # elm0000000010
print(padzero_with_lower('Elm11')) # elm0000000011 
print(padzero_with_lower('Elm12')) # elm0000000012
print(padzero_with_lower('elm13')) # elm0000000013

测试了这个函数后，我们现在可以使用它作为我们的键。

lis = ['elm0', 'elm1', 'Elm2', 'elm9', 'elm10', 'Elm11', 'Elm12', 'elm13']
lis.sort(key=padzero_with_lower)
print(lis)
# Output: ['elm0', 'elm1', 'Elm2', 'elm9', 'elm10', 'Elm11', 'Elm12', 'elm13']

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。