本职位的价值

我的观点是提供一个可以普遍应用的非正则表达式解决方案。 我将创建三个函数:

find_first_digit，这是我从@AnuragUniyal借来的。它将查找字符串中第一个数字或非数字的位置。 Split_digits是一个生成器，它将字符串分成数字块和非数字块。当它是数字时，它也会产生整数。 Natural_key只是将split_digits包装成一个元组。这是我们用来排序，最大，最小的键。

功能

def find_first_digit(s, non=False):
    for i, x in enumerate(s):
        if x.isdigit() ^ non:
            return i
    return -1

def split_digits(s, case=False):
    non = True
    while s:
        i = find_first_digit(s, non)
        if i == 0:
            non = not non
        elif i == -1:
            yield int(s) if s.isdigit() else s if case else s.lower()
            s = ''
        else:
            x, s = s[:i], s[i:]
            yield int(x) if x.isdigit() else x if case else x.lower()

def natural_key(s, *args, **kwargs):
    return tuple(split_digits(s, *args, **kwargs))

我们可以看到它是一般的，因为我们可以有多个数字块:

# Note that the key has lower case letters
natural_key('asl;dkfDFKJ:sdlkfjdf809lkasdjfa_543_hh')

('asl;dkfdfkj:sdlkfjdf', 809, 'lkasdjfa_', 543, '_hh')

或保留大小写敏感:

natural_key('asl;dkfDFKJ:sdlkfjdf809lkasdjfa_543_hh', True)

('asl;dkfDFKJ:sdlkfjdf', 809, 'lkasdjfa_', 543, '_hh')

我们可以看到它以适当的顺序对OP的列表进行排序

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

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

但它也可以处理更复杂的列表:

sorted(
    ['f_1', 'e_1', 'a_2', 'g_0', 'd_0_12:2', 'd_0_1_:2'],
    key=natural_key
)

['a_2', 'd_0_1_:2', 'd_0_12:2', 'e_1', 'f_1', 'g_0']

我的正则表达式等价于

def int_maybe(x):
    return int(x) if str(x).isdigit() else x

def split_digits_re(s, case=False):
    parts = re.findall('\d+|\D+', s)
    if not case:
        return map(int_maybe, (x.lower() for x in parts))
    else:
        return map(int_maybe, parts)
    
def natural_key_re(s, *args, **kwargs):
    return tuple(split_digits_re(s, *args, **kwargs))

a = ['H1', 'H100', 'H10', 'H3', 'H2', 'H6', 'H11', 'H50', 'H5', 'H99', 'H8']
b = ''
c = []

def bubble(bad_list):#bubble sort method
        length = len(bad_list) - 1
        sorted = False

        while not sorted:
                sorted = True
                for i in range(length):
                        if bad_list[i] > bad_list[i+1]:
                                sorted = False
                                bad_list[i], bad_list[i+1] = bad_list[i+1], bad_list[i] #sort the integer list 
                                a[i], a[i+1] = a[i+1], a[i] #sort the main list based on the integer list index value

for a_string in a: #extract the number in the string character by character
        for letter in a_string:
                if letter.isdigit():
                        #print letter
                        b += letter
        c.append(b)
        b = ''

print 'Before sorting....'
print a
c = map(int, c) #converting string list into number list
print c
bubble(c)

print 'After sorting....'
print c
print a

应答:

气泡排序作业

如何在python中一次读一个字母的字符串

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。

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。

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)))
    )

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:-)