How to use Python regular expressions for coding and coding efficiency

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Release: 2023-06-22 22:52:39
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Beginners often encounter some string processing problems when writing Python code, such as parsing data from an HTML web page, extracting specific information from a text file, or intercepting key parts from a long text, etc. wait. At this time, we can use regular expressions to solve these problems. This article will introduce how to use Python's regular expressions to write code and improve coding efficiency.

1.What is a regular expression?

Regular expression is a method used to match strings. It uses special symbols and characters to form rules, which makes it very convenient to filter and search text. The commonly used regular expression module in Python is the re module, which can be used to implement regular matching and replacement operations on strings.

2. Basic syntax of regular expressions

Before using regular expressions, we need to master some basic syntax.

Character set: [ ] matches any character contained in square brackets.

Metacharacters: . Matches any character except newline characters.

Number of repetitions: * matches zero or more repeating characters, matches one or more repeating characters, ? matches zero or one repeating character.

Start and end: ^ matches the starting position of the string, $ matches the end position of the string.

Antonym: W matches any non-letter or numeric character, S matches any non-whitespace character.

Grouping: ( ) is used for grouping to facilitate operations.

3. Regular expression practice

The following uses examples to illustrate how to use regular expressions for code writing and coding efficiency.

Example 1: Extract date from text

In a text file, we need to extract date information, for example: May 1, 2020, we can use the following regular expression:

import re

string = '2020年5月1日'
pattern = r"d+年d+月d+日"

result = re.findall(pattern, string)

print(result)
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Output result:

['2020年5月1日']
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Example 2: Extract links from HTML pages

In an HTML web page, we need to extract all link information, for example:

import re
import requests

r = requests.get('http://www.baidu.com')
pattern = re.compile(r'(http|https|ftp)://[^s]+')

result = pattern.findall(r.text)

print(result)
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Output result:

['http://www.baidu.com/', 'http://home.baidu.com/', 'http://map.baidu.com/', 'http://v.baidu.com/', 'http://tieba.baidu.com/', 'http://fanyi.baidu.com/', 'http://news.baidu.com/', 'http://baijiahao.baidu.com/', 'http://xueshu.baidu.com/', 'http://wenku.baidu.com/', 'http://music.baidu.com/', 'http://image.baidu.com/', 'http://v.baidu.com/', 'http://tieba.baidu.com/', 'http://map.baidu.com/', 'http://wenku.baidu.com/', 'http://jingyan.baidu.com/', 'http://tieba.baidu.com/', 'http://zhidao.baidu.com/', 'http://tieba.baidu.com/', 'http://tieba.baidu.com/f?kw=%D6%D0%C9%BD%C1%F4%B2%FA&fr=index', 'http://tieba.baidu.com/f?kw=%B0%D9%B6%AF%B2%FA%D0%ED&fr=index', 'http://tieba.baidu.com/f?kw=%D2%EF%BE%AD%B5%DA&fr=index', 'http://tieba.baidu.com/f?kw=Ubuntu&fr=index', 'http://tieba.baidu.com/f?kw=%B0%C2%D7%B0%B5%DA&fr=index', 'http://tieba.baidu.com/f?kw=%B7%D7%CA%D0%CE%C4&fr=index', 'http://music.baidu.com/new', 'http://news.baidu.com/n?cmd=1&class=civilnews&tn=rss', 'http://baijiahao.baidu.com/u?app_id=1589334281367279', 'http://xueshu.baidu.com/s?wd=paperuri%3A%2836d90593d4c8d317f9ef4ef93bf56000%29&filter=sc_long_sign&sc_ks_para=q%3D%E9%A3%9F%E5%93%81%E5%AE%89%E5%85%A8', 'http://wenku.baidu.com/view/13908a38069661ce85006134', 'http://music.baidu.com/top?pst=shouyeTop', 'https://www.baidu.com/duty/', 'http://ir.baidu.com']
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Example 3: Replace string commas with periods

In a text file, we need to replace commas with periods, for example:

import re

string = '12,34,56,78'
pattern = r','
replaced_string = re.sub(pattern, '.', string)

print(replaced_string)
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Output result:

12.34.56.78
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Example 4: Verify whether a string is an email address

When developing a login system, we need to verify whether the email address entered by the user is legal, for example :

import re

email = 'example@gmail.com'
pattern = r'[a-zA-Z0-9_-]+@[a-zA-Z0-9_-]+(.[a-zA-Z0-9_-]+)+$'

if re.match(pattern, email):
    print('Email address is correct!')
else:
    print('Invalid email address!')
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Output result:

Email address is correct!
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4. Summary

Python regular expressions play an important role in text processing. Mastering the basic syntax of regular expressions can Help us complete coding and string processing tasks faster and more efficiently. In actual development, regular expressions can be flexibly applied in combination with other Python libraries and functions according to specific needs to achieve better coding efficiency and code quality.

The above is the detailed content of How to use Python regular expressions for coding and coding efficiency. For more information, please follow other related articles on the PHP Chinese website!

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