Regularly remove html

In today's era of Internet information explosion, web pages are a very important way for us to obtain information. However, because the content of the web page is too complex and contains many HTML codes, it is difficult for us to directly extract the text from the web page for analysis and processing. Therefore, we need to use regular expressions to remove these HTML codes and extract useful text content.

First of all, we need to understand some characteristics of HTML tags. HTML tags generally start with < and end with >, and contain some tag names and attribute values ​​in the middle. For example:

This is the content of a webpage

, the name of this tag is "p", the attribute is "class='content'", and the text content is "This is a webpage The content of the web page".

Next, we can remove these HTML tags through regular expressions and extract the plain text in the web page. The following are some commonly used regular expressions:

1. Matches HTML tags

<¹ >

This regular expression can match HTML tags, where < represents the beginning of the tag, ¹ > means matching characters except >, means matching at least once , [] represents the character set, and ^ represents negation, so the content matched by this regular expression is HTML tags.

2. Remove HTML tags

<¹ >

You can remove HTML tags. Leave only plain text.

3. Remove HTML tags and spaces

s<¹ >s

This regular expression can remove HTML tags and spaces, leaving only plain text.

4. Remove HTML tags and line breaks

[
]*<¹ >[
]*

This regular expression can remove HTML tags and line breaks, leaving only plain text.

With the above regular expression, we can remove the HTML tags in the web page and extract useful text content. In daily work, we can apply these regular expressions to text editors, Python, Java and other programming languages ​​to extract and process the text content of web pages.

In short, regular expressions can help us process text content quickly and accurately, especially when processing web pages and other HTML codes. It is very convenient to use regular expressions to remove these codes, which improves our Work efficiency.

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