为了证明正则表达式功能的强大之处,我们先用个小例子体现一下:
# 用之前学过的知识判断输入的是否是手机号码
def isPhoneNumber(str):
if len(str) != 11:
return False
elif str[0] != "1":
return False
# 这里只列出了常见的几种手机号码的开头
elif str[1:3] != "31" and str[1:3] != "32" and str[1:3] != "38" and str[1:3] != "39" and str[1:3] != "47" and str[1:3] != "51" and str[1:3] != "57" and str[1:3] != "78" and str[1:3] != "86" and str[1:3] != "88":
return False
for i in range(3, 11):
if str[i] < "0" or str[i] > "9":
return False
return True
phoneNumber = input("请输入您的手机号:")
print(isPhoneNumber(phoneNumber))
def isPhoneNumber(phoneNumber):
pat = r"^1(([3578]\d)|(47))\d{8}$"
print(re.match(pat, phoneNumber))
phoneNumber = input("请输入您的手机号:")
isPhoneNumber(phoneNumber)
相信你此刻已经感受到了它的强大之处,接下来就让我们开始正则表达式的学习。先来介绍一下 re 模块。
import re
# 扫描整个字符串,注意返回从起始位置成功的匹配
print(re.match("To", "To be a better man !")) # <_sre.SRE_Match object; span=(0, 2), match='To'>
print(re.match("To", "be To a better man !")) # None
print(re.match("to", "To be a better man !", flags=re.I))
# 扫描整个字符串,并返回第一个成功的匹配
print(re.search("To", "be To a better man !")) # <_sre.SRE_Match object; span=(3, 5), match='To'>
# 扫描整个字符串,并返回结果列表
print(re.findall("To", "To be a better man and to make right decision !", flags=re.I)) # ['To', 'to']
import re
print(re.findall(".", "To be a \n better man !"))
print(re.findall("[better]", "To be a \n better man !"))
print(re.findall("[^To be a]", "To be a \n better man !"))
print(re.findall("\d", "95 To be a better man ! 0831"))
print(re.findall("\w", "95 To be a better man ! 0831"))
print(re.findall("\s", "95 To be a better man ! 0831"))
import re
print(re.search("^To", "To be a better man !"))
print(re.search("!$", "To be a better man !"))
print(re.findall("\ATo", "To be a better man !\nTo be a better man !", re.M))
print(re.findall("^To", "To be a better man !\nTo be a better man !", re.M))
print(re.search(r"er\b", "better"))
说明:下方的 x、y、z 均为假设的普通字符,不是正则表达式的元字符,m n 表示非负整数
import re
# 贪婪匹配,尽可能多的匹配;非贪婪匹配,尽可能少的匹配
print(re.findall(r"(better)", "To be a better man !")) # ['better']
print(re.findall(r"a?", "aaaaaa")) # ['a', 'a', 'a', 'a', 'a', 'a', '']
print(re.findall(r"a*", "aaaaaa")) # ['aaaaaa', '']
print(re.findall(r"a+", "aaaaaaba")) # ['aaaaaa', 'a']
print(re.findall(r"a{3}", "aaaaaa")) # ['aaa', 'aaa']
print(re.findall(r"a{4,}", "aaaaaabaaaacaaa")) # ['aaaaaa', 'aaaa']
print(re.findall(r"a{4,5}", "aaaaaabaaaacaaa")) # ['aaaaa', 'aaaa']
print(re.findall(r"((M|m)ark)", "Mark mark")) # [('Mark', 'M'), ('mark', 'm')]
# 对 * 进行转义,进行非贪婪匹配
print(re.findall(r"//*.*?/*/", r"/* one */ /* two */ ")) # ['/* one */', '/* two */']
大家可以去写一下关于 QQ 、邮箱、电话、用户名、密码、IP地址、URL的正则表达式来练下手。
END
re模块深入了解
# 切割字符串
s = "To be a better man !"
print(s.split(" "))
print(re.split(r" +", s)) # 以一个或多个空格切割
# re.finditer() 函数,与 findall() 类似,扫描整个字符串,返回的是一个迭代器,节省内存
s = "To be a better man! To be a better man! To be a better man!"
x = re.findall(r"(better)", s)
print(x)
i = re.finditer(r"(better)", s) # 迭代器
while 1:
try:
j = next(i)
print(j)
except StopIteration as e:
break
re.sub(pattern, repl, string, count, flags=0) 与 re.subn(…) repl 用来替换的字符串,string 目标字符串,count 最多替换次数
作用:在目标字符串中以正则表达式的规则匹配字符串,再把他们替换成指定的字符串,可以指定替换的次数,如果不指定,替换所有的匹配字符串
区别:前者返回一个被替换的字符串,后者返回一个元组,元组的第一个元素为被替换的字符串,第二个元素为被替换的次数
s = "To be a better better better man!"
print(re.sub(r"(better)", "great", s))
print(type(re.sub(r"(better)", "great", s)))
print(re.subn(r"(better)", "great", s, 2))
print(type(re.subn(r"(better)", "great", s)))
# 分组
phone = "010-8888888"
d = re.match(r"((\d{3})-(\d{7}))", phone)
# 使用序号获取对应组的信息,group(0) 代表原始字符串
print(d.group(0))
# 第一组
print(d.group(1)) # 010-8888888
print(d.group(2)) # 010
print(d.group(3))
# 查看匹配的各组的情况
print(d.groups()) # ('010-8888888', '010', '8888888')
编译:当我们使用正则表达式时,re 模块会做两件事:
1.编译正则表达式,如果正则表达式本身不合法,会报错 2.用编译后的正则表达式去匹配对象,如果编译成正则对象,简化了匹配过程
pat= r"^1(([3578]\d)|(47))\d{8}$"
print(re.search(pat, "13588888888"))
# 编译成正则对象
phone = re.compile(pat)
print(phone.search("13588888888"))
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如有侵权,请联系 cloudcommunity@tencent.com 删除。