我不知道为什么这些都这么复杂。

对于大多数情况，简单的表达式([A-Z]+)就可以了

>>> re.sub('([A-Z]+)', r'_\1','CamelCase').lower()
'_camel_case'  
>>> re.sub('([A-Z]+)', r'_\1','camelCase').lower()
'camel_case'
>>> re.sub('([A-Z]+)', r'_\1','camel2Case2').lower()
'camel2_case2'
>>> re.sub('([A-Z]+)', r'_\1','camelCamelCase').lower()
'camel_camel_case'
>>> re.sub('([A-Z]+)', r'_\1','getHTTPResponseCode').lower()
'get_httpresponse_code'

要忽略第一个字符，只需添加look behind (?!^)

>>> re.sub('(?!^)([A-Z]+)', r'_\1','CamelCase').lower()
'camel_case'
>>> re.sub('(?!^)([A-Z]+)', r'_\1','CamelCamelCase').lower()
'camel_camel_case'
>>> re.sub('(?!^)([A-Z]+)', r'_\1','Camel2Camel2Case').lower()
'camel2_camel2_case'
>>> re.sub('(?!^)([A-Z]+)', r'_\1','getHTTPResponseCode').lower()
'get_httpresponse_code'

如果你想分离ALLCaps到all_caps，并期望字符串中的数字，你仍然不需要做两次单独的运行，只需使用|这个表达式((?<=[a-z0-9])[A-Z]|(?!^)[A-Z](?=[A-Z]))可以处理书中的几乎所有场景

>>> a = re.compile('((?<=[a-z0-9])[A-Z]|(?!^)[A-Z](?=[a-z]))')
>>> a.sub(r'_\1', 'getHTTPResponseCode').lower()
'get_http_response_code'
>>> a.sub(r'_\1', 'get2HTTPResponseCode').lower()
'get2_http_response_code'
>>> a.sub(r'_\1', 'get2HTTPResponse123Code').lower()
'get2_http_response123_code'
>>> a.sub(r'_\1', 'HTTPResponseCode').lower()
'http_response_code'
>>> a.sub(r'_\1', 'HTTPResponseCodeXYZ').lower()
'http_response_code_xyz'

这完全取决于你想要什么，所以使用最适合你需要的解决方案，因为它不应该过于复杂。

nJoy !

简洁，没有正则表达式，但HTTPResponseCode=> httpresponse_code:

def from_camel(name):
    """
    ThisIsCamelCase ==> this_is_camel_case
    """
    name = name.replace("_", "")
    _cas = lambda _x : [_i.isupper() for _i in _x]
    seq = zip(_cas(name[1:-1]), _cas(name[2:]))
    ss = [_x + 1 for _x, (_i, _j) in enumerate(seq) if (_i, _j) == (False, True)]
    return "".join([ch + "_" if _x in ss else ch for _x, ch in numerate(name.lower())])

这么多复杂的方法…… 只需找到所有“标题”组，并加入其小写变体与下划线。

>>> import re
>>> def camel_to_snake(string):
...     groups = re.findall('([A-z0-9][a-z]*)', string)
...     return '_'.join([i.lower() for i in groups])
...
>>> camel_to_snake('ABCPingPongByTheWay2KWhereIsOurBorderlands3???')
'a_b_c_ping_pong_by_the_way_2_k_where_is_our_borderlands_3'

如果你不想让数字像组的第一个字符或单独的组-你可以使用([A-z][a-z0-9]*)掩码。

为了好玩:

>>> def un_camel(input):
...     output = [input[0].lower()]
...     for c in input[1:]:
...             if c in ('ABCDEFGHIJKLMNOPQRSTUVWXYZ'):
...                     output.append('_')
...                     output.append(c.lower())
...             else:
...                     output.append(c)
...     return str.join('', output)
...
>>> un_camel("camel_case")
'camel_case'
>>> un_camel("CamelCase")
'camel_case'

或者，更有趣的是:

>>> un_camel = lambda i: i[0].lower() + str.join('', ("_" + c.lower() if c in "ABCDEFGHIJKLMNOPQRSTUVWXYZ" else c for c in i[1:]))
>>> un_camel("camel_case")
'camel_case'
>>> un_camel("CamelCase")
'camel_case'

看一看优秀的Schematics库

https://github.com/schematics/schematics

它允许你创建类型化的数据结构，可以序列化/反序列化从python到Javascript风格，例如:

class MapPrice(Model):
    price_before_vat = DecimalType(serialized_name='priceBeforeVat')
    vat_rate = DecimalType(serialized_name='vatRate')
    vat = DecimalType()
    total_price = DecimalType(serialized_name='totalPrice')

就我个人而言，我不确定在python中使用正则表达式的任何东西都可以被描述为优雅。这里的大多数答案只是做“代码高尔夫”类型的RE技巧。优雅的编码应该是容易理解的。

def to_snake_case(not_snake_case):
    final = ''
    for i in xrange(len(not_snake_case)):
        item = not_snake_case[i]
        if i < len(not_snake_case) - 1:
            next_char_will_be_underscored = (
                not_snake_case[i+1] == "_" or
                not_snake_case[i+1] == " " or
                not_snake_case[i+1].isupper()
            )
        if (item == " " or item == "_") and next_char_will_be_underscored:
            continue
        elif (item == " " or item == "_"):
            final += "_"
        elif item.isupper():
            final += "_"+item.lower()
        else:
            final += item
    if final[0] == "_":
        final = final[1:]
    return final

>>> to_snake_case("RegularExpressionsAreFunky")
'regular_expressions_are_funky'

>>> to_snake_case("RegularExpressionsAre Funky")
'regular_expressions_are_funky'

>>> to_snake_case("RegularExpressionsAre_Funky")
'regular_expressions_are_funky'