比较常用的有(REs),(?P<name>REs),这是无名称的组和有名称的group,有名称的group,可以通过matchObject.group(name) 获取匹配的group,而无名称的group可以通过从1开始的group序号来获取匹配的组,如matchObject.group(1)。具体应用将在下面的group()方法中举例讲解 11.元字符(.) 元字符“.”在默认模式下,匹配...
>>> m = re.match(r"(\w+) (\w+)","Isaac Newton, physicist")>>> m.group(0)#The entire match'Isaac Newton'>>> m.group(1)#The first parenthesized subgroup.'Isaac'>>> m.group(2)#The second parenthesized subgroup.'Newton'>>> m.group(1, 2)#Multiple arguments give us a tuple....
group 默认为0,就是整个匹配。 Match.pos pos 的值,会传递给 search() 或match() 的方法 a 正则对象 。这个是正则引擎开始在字符串搜索一个匹配的索引位置。 Match.endpos endpos 的值,会传递给 search() 或match() 的方法 a 正则对象 。这个是正则引擎停止在字符串搜索一个匹配的索引位置。 Match....
回到regex.sub()。repl除了是字符串,还可以是函数。如果repl是函数,它的输入是match对象,返回一个最终想替换的字符串。 >>>defdashrepl(matchobj):...ifmatchobj.group(0)=='-':return' '...else:return'-'>>>re.sub('-{1,2}',dashrepl,'pro---gram-files')'pro--gram files'#-{1,2}匹配一...
Match.group([group1, …]) 根据输入的组号,返回一个或者多个匹配的子组。 组号意义 组号为 0,表示整个正则 pattern 匹配到的内容 组号为 [1..99] 的正整数,表示正则 pattern 里面相应的组匹配到的内容 对于命名组, 组号也可能是命名组的名字。 如果一个组被匹配多次,就返回最后一个匹配结果 组号为负数,或...
regex.match() 从头开始匹配零个或多个字符。如果匹配返回match对象,否则匹配None。可选参数pos和endpos作用同search。 regex.findall() 作用同re.findall(pattern,s,flags=0)。返回字符串中所有不重复(不重复指的是位置不重复)的匹配,以string列表的形式。字符串从左到右扫描,返回的匹配顺序如被发现的顺序。 此...
AdvertisementsThe regex functions We look for matches with regex functions. FunctionDescription matchDetermines if the RE matches at the beginning of the string. fullmatchDetermines if the RE matches the whole of the string. searchScans through a string, looking for any location where this RE matche...
match.groupdict(default=None)Returns a dictionary of named captured groups.match.groupdict() returns a dictionary of all named groups captured with the (?P<name><regex>) metacharacter sequence. The dictionary keys are the group names and the dictionary values are the corresponding group values:...
Ruff can be used to replaceFlake8(plus dozens of plugins),isort,pydocstyle,yesqa,eradicate,pyupgrade, andautoflake, all while executing tens or hundreds of times faster than any individual tool. Ruff is extremely actively developed and used in major open-source projects like: ...
... """ >>> regex.findall(text) ['support@example.com', 'sales@example.com'] The pattern variable holds a raw string that makes up a regular expression to match email addresses. Note how the string contains several backslashes that are escaped and inserted into the resulting string as ...