python re.match example

Willy 182 Published: 07/20/2024

python re.match example

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Python's re module provides support for regular expressions (regex) - a sequence of characters that forms a search pattern, mainly for string manipulation. One of the most powerful and versatile tools in Python for working with text data.

Here are some examples:

import re
Simple Matching

phone_num = "123-456-7890"


pattern = r'd{3}-d{3}-d{4}'


match = re.match(pattern, phone_num)


print(match)  # Output: <_sre.SRE_Match object; match='123-456-7890'>

Group Matching

phone_num = "123-456-7890"


pattern = r'(d{3})-(d{3})-(d{4})'


match = re.match(pattern, phone_num)


print(match.groups())  # Output: ('123', '456', '7890')

Multiple Matches

text = "hello world, hello python"


pattern = r'bhellob'


matches = re.finditer(pattern, text)


for match in matches:


print(match)  # Output: Each match will be printed as a separate object

Non-Greedy Matching

text = "
This is a test
"

pattern = r'<[^>]*>'


match = re.search(pattern, text)


print(match.group())  # Output: '
', '
', '', 'a', ''
Positive Lookahead

text = "This is a test string"


pattern = r'test(?=.*string)'


match = re.search(pattern, text)


print(match)  # Output: <_sre.SRE_Match object; match='test'>

Negative Lookbehind

text = "This is a test string"


pattern = r'(?<!test).*'


match = re.match(pattern, text, re.I)


print(match.group())  # Output: ' This is a '

These examples demonstrate various features of the re module:

Simple Matching: The simplest use case for regular expressions in Python, where you match an exact string. Group Matching: You can capture specific parts of your pattern using parentheses, which creates groups that you can access later. Multiple Matches: When you need to find all occurrences of a pattern within a text, re.finditer is the way to go. Non-Greedy Matching: If you want to match something as few times as possible, use non-greedy quantifiers like .*?. Positive Lookahead: A positive lookahead asserts that a certain string will follow the current position in the text, without including it in your overall match. Negative Lookbehind: You can look behind the start of the match to ensure that you don't match something if it contains a certain pattern, for instance, "not preceded by test".

These are just a few examples of how powerful and versatile the re module is.

Python re match

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