How to implement regular expressions in Python

Python regular expression

Regular expression itself is knowledge independent of programming language, but it is also dependent on programming language. Basically, the programming language we use provides Of course, there are some differences in its implementation. Some support more functions and some support less.

Because regular expressions are a widely used tool in practice, I think it is unreliable to learn without language.

Introduction to regular expression functions

Regular expression main API relationship diagram

This diagram is mine Personally, I think I have basically clarified the relationship between the functions here. Their functions are:

• match matches the regular expression from the beginning of the text and returns the matching object. If not, return None

• #search matches the regular expression in the entire text and returns the first matching object. If not, return None.

• sub Use regular expressions for text replacement (function of regular expressions: search and replace)

• findall matches regular expressions from the entire text An expression that returns all matching results as a list.

• finditer matches a regular expression from the entire text, returning all matching results as an iterator.

• split Use regular expressions to split text

As you can see here, ·re· there are many functions that can be used immediately, Then re.compile There are many functions with the same name below. Directly under the ·re· module are officially provided functions for easy use. The most orthodox way to use them is through re.compile. So, for the next content, I basically use re.compile and the methods below to achieve it.

re.compile function

compile The function is used to compile regular expressions and generate a regular expression (Pattern) object for match( ) and search() and other functions.

Syntax:

re.compile(pattern[, flags])

• pattern: a regular expression in the form of a string

• flags optional, indicating matching pattern , such as ignoring case, multi-line mode, etc., the specific parameters are:

• re.I Ignore case

• re. L multi-line mode

• re.S is '.' and any character including newline ('.' does not include newline)

• re.U represents the special character set \w, \W, \b, \B, \d, \D, \s, \S and relies on the Unicode character attribute database

• re. ##Learning Template

Next we will gradually learn the content of regular expressions, which is very interesting! Interesting and Excited!

Here is a sample template that will be used all the time. This template is the most important thing in this blog, and subsequent content will be expanded based on it. So, please understand it well.

import re

s = 'runoob 123 google 456'
result1 = re.findall(r'\d+', s)

pattern = re.compile(r'\d+') # 查找数字
result2 = pattern.findall(s)
result3 = pattern.findall(s, 0, 20)


print(result1)
print(result2)
print(result3)


"""
output:
[‘123'， ‘456']
[‘123'， ‘456']
[‘123'， ‘45']
"""

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Note: The regular expression regexp will use the

r

prefix before starting. The purpose of this is In order to avoid using a lot of escape characters in regular expressions, which destroys the overall readability.

Python’s regular expressions include many very easy-to-use methods, but I won’t introduce them too much here. We will always use the above pattern, because those easy-to-use methods are just a kind of encapsulation of it, and learning to use this basic method will naturally lead to others.

The matching object can obtain information about the regular expression. Its most important methods and properties are:

Methods/Properties

Purpose

group()Return the regular matching stringstart()Return the starting position of the matchend()Return the end position of the matchspan( )Return a tuple containing the matching (start, end) position

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