Python中正则表达式的用法实例汇总

正则表达式是Python程序设计中非常实用的功能，本文就常用的正则表达式做一汇总，供大家参考之用。具体如下：

一、字符串替换

1.替换所有匹配的子串

用newstring替换subject中所有与正则表达式regex匹配的子串

    result, number = re.subn(regex, newstring, subject)

2.替换所有匹配的子串（使用正则表达式对象）

    reobj = re.compile(regex)
    result, number = reobj.subn(newstring, subject)

二、字符串拆分

1.字符串拆分

    result = re.split(regex, subject)

2.字符串拆分（使用正则表示式对象）

    reobj = re.compile(regex)
    result = reobj.split(subject)

三、匹配

下面列出Python正则表达式的几种匹配用法：

1.测试正则表达式是否匹配字符串的全部或部分

    regex=ur"..." #正则表达式
    if re.search(regex, subject):
      do_something()
    else:
      do_anotherthing()

2.测试正则表达式是否匹配整个字符串

    regex=ur"...\Z" #正则表达式末尾以\Z结束
    if re.match(regex, subject):
      do_something()
    else:
      do_anotherthing()

3. 创建一个匹配对象，然后通过该对象获得匹配细节

    regex=ur"..." #正则表达式
    match = re.search(regex, subject)
    if match:
      # match start: match.start()
      # match end (exclusive): match.end()
      # matched text: match.group()
      do_something()
    else:
      do_anotherthing()

4.获取正则表达式所匹配的子串

    (Get the part of a string matched by the regex)

    regex=ur"..." #正则表达式
    match = re.search(regex, subject)
    if match:
      result = match.group()
    else:
      result = ""

5. 获取捕获组所匹配的子串

    (Get the part of a string matched by a capturing group)

    regex=ur"..." #正则表达式
    match = re.search(regex, subject)
    if match:
      result = match.group(1)
    else:
      result = ""

6. 获取有名组所匹配的子串

    (Get the part of a string matched by a named group)

    regex=ur"..." #正则表达式
    match = re.search(regex, subject)
    if match:
      result = match.group("groupname")
    else:
      result = ""

7. 将字符串中所有匹配的子串放入数组中

    (Get an array of all regex matches in a string)

    result = re.findall(regex, subject)

8.遍历所有匹配的子串

    (Iterate over all matches in a string)

    for match in re.finditer(r"<(.*?)\s*.*?/\1>", subject)
      # match start: match.start()
      # match end (exclusive): match.end()
      # matched text: match.group()

9.通过正则表达式字符串创建一个正则表达式对象

    (Create an object to use the same regex for many operations)

    reobj = re.compile(regex)

10.用法１的正则表达式对象版本

    (use regex object for if/else branch whether (part of) a string can be matched)

    reobj = re.compile(regex)
    if reobj.search(subject):
      do_something()
    else:
      do_anotherthing()

11.用法２的正则表达式对象版本

    (use regex object for if/else branch whether a string can be matched entirely)

    reobj = re.compile(r"\Z")　#正则表达式末尾以\Z 结束
    if reobj.match(subject):
      do_something()
    else:
      do_anotherthing()

12.创建一个正则表达式对象，然后通过该对象获得匹配细节

    (Create an object with details about how the regex object matches (part of) a string)

    reobj = re.compile(regex)
    match = reobj.search(subject)
    if match:
      # match start: match.start()
      # match end (exclusive): match.end()
      # matched text: match.group()
      do_something()
    else:
      do_anotherthing()

13.用正则表达式对象获取匹配子串

    (Use regex object to get the part of a string matched by the regex)

    reobj = re.compile(regex)
    match = reobj.search(subject)
    if match:
      result = match.group()
    else:
      result = ""

14.用正则表达式对象获取捕获组所匹配的子串

    (Use regex object to get the part of a string matched by a capturing group)

    reobj = re.compile(regex)
    match = reobj.search(subject)
    if match:
      result = match.group(1)
    else:
      result = ""

15.用正则表达式对象获取有名组所匹配的子串

    (Use regex object to get the part of a string matched by a named group)

    reobj = re.compile(regex)
    match = reobj.search(subject)
    if match:
      result = match.group("groupname")
    else:
      result = ""

16.用正则表达式对象获取所有匹配子串并放入数组

    (Use regex object to get an array of all regex matches in a string)

    reobj = re.compile(regex)
    result = reobj.findall(subject)

17.通过正则表达式对象遍历所有匹配子串

    (Use regex object to iterate over all matches in a string)

    reobj = re.compile(regex)
    for match in reobj.finditer(subject):
      # match start: match.start()
      # match end (exclusive): match.end()
      # matched text: match.group()

感兴趣的读者可以动手调试一下本文实例代码，相信会有新的收获。