The basic principle is to use a series of special characters and syntax to match and manipulate text data. Regular expressions typically include a pattern string that describes the text pattern to be matched, and one or more special characters and syntax that control how and what the result is. Regular expressions in Python are usually implemented using the re module

What is a regular expression?

Regular expression, also known as regular expression, (English: Regular Expression, often abbreviated as regex, regexp or RE in code), it is a concept in computer science. Regular expressions are often used to retrieve and replace text that matches a certain pattern. Many programming languages ​​support string manipulation using regular expressions. For example, Perl has a powerful regular expression engine built into it. The concept of regular expressions was originally popularized by tool software in Unix. A regular expression is a logical formula that operates on strings (including ordinary characters (for example, letters between a to z) and special characters (called "metacharacters")), which uses some predefined specific characters. , and the combination of these specific characters form a "rule string". This "rule string" is used to express a filtering logic for strings. A regular expression is a text pattern that describes one or more strings to match when searching for text.

1. Introduction to Examples

After talking a lot of nonsense, you may still be confused. Let’s explain it through examples. We can use regular expression testing tools, or python All is OK. First, we enter a piece of text.

hello, my name is Tina, my phone number is 123456 and my web is http://tina.com.

                               [a-zA-z]+://[^\s]*

We can get the web link, That is, the url in the text. Isn’t it amazing?

This is because it has its own matching rules, some of which are as follows.

You can check more matching rules by yourself.

?,*, ,\d,\w are all equivalent characters

? are equivalent to matching Length {0,1}

* is equivalent to matching length {0,}

is equivalent to matching length {1,}

\d Equivalent to [0-9]

\D Equivalent to [^0-9]

\w Equivalent to [A-Za-z_0-9]

\W Equivalent to [^A-Za-z_0-9]

2. MATCH ()

res = re.match('hello\s(\d+)sword')

Copy after login

res = re.match('hello.*(\d+)sword')

Copy after login

import re
 
useData = str(input('请输入字符串数据:'))
 
'''
匹配字符串中的数字,+是匹配前面的子表达式一次或多次
'''
digital = re.findall('\d+',useData)
 
print(digital)

The "." character matches any single character.

The "\" character is an escape character.

"[…]" is the character set.

"(.*?)" is the most commonly used character in python crawlers. It is called a greedy algorithm and can match any character.

import re
 
a=‘xxixxjshdxxlovexxsfhxxpythonxx'
 
data=re.findall(‘xx(.*?)xx')
 
print(data)

Run results

[‘I’,‘love’,‘python’]

概念说了一大堆，大家可能也记不住，我直接说几个案例，大家就能明白其他的道理。

这是某网的HTML，部分片段如下：

§123
 
§133
 
§156
 
§189

大家会发现只有中间的一段不一样，而不一样的数据就是我们想要的，我们怎么用正则表达式提取出来呢.

§(.*?)

就可以了，我们看看效果吧。

123
133
156
189

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