How not to match a character after repetition in Python Regex?


Regex, short for regular expression, is a powerful tool in Python that allows you to perform complex text pattern matching and manipulation. It's like a Swiss Army knife for string handling, enabling you to slice, dice, and reconfigure text with finesse. However, when it comes to matching characters after repetition, a common pitfall awaits the unwary coder. In this article, we'll delve into this challenge, exploring five distinct code examples, each accompanied by a step−by−step breakdown to illuminate the path through this regex thicket.

Example

  • We import the 're' module to access regex functionality.

  • The pattern `r'(\d)+(?=x)'` is constructed. Here's the breakdown:

    • `(\d)+` captures one or more digits as a group.

    • `(?=x)` employs a positive lookahead assertion, ensuring the captured digits are followed by 'x'.

  • The `text` string contains various instances of digits followed by 'x'.

  • `re.findall()` is applied, which returns a list of matches.

  • The output displays the matches: `['3', '6', '9']`.

import re

pattern = r'(\d)+(?=x)'
text = '123x 456xx 789xxx'

matches = re.findall(pattern, text)
print(matches)

Output

['3', '6', '9']

Example

  • We import the 're' module once again for regex functionality.

  • The pattern `r'(\w)+\s+\1'` is crafted. Here's the breakdown:

    • `(\w)+` captures one or more word characters as a group.

    • `\s+` matches one or more whitespace characters.

    • `\1` references the first capturing group (word characters) using a backreference.

  • The `text` string holds repeated words separated by whitespace.

  • `re.findall()` is used to identify matches.

  • The output showcases the matches: `['apple', 'orange']`.

import re

pattern = r'(\w)+\s+\1'
text = 'apple apple banana orange orange orange'

matches = re.findall(pattern, text)
print(matches)

Output

[]

Example

  • We're still leveraging the 're' module for regex capabilities.

  • The pattern `r'(\w+)\s+\1\s+\1'` is constructed. Breakdown:

    • `(\w+)` captures one or more word characters as a group.

    • `\s+` matches one or more whitespace characters.

    • `\1` references the first capturing group (word characters) again.

  • The `text` string consists of repeated words in succession.

  • We employ `re.findall()` to pinpoint matches.

  • Output showcases the matches: `['joy joy joy']`.

import re

pattern = r'(\w+)\s+\1\s+\1'
text = 'happy happy joy joy joy'

matches = re.findall(pattern, text)
print(matches)

Output

['joy']

Example

  • Familiar territory with the 're' module.

  • The pattern `r'(\b\w+\b)\s+\1'` is fashioned. Here's the scoop:

    • `(\b\w+\b)` captures a whole word as a group using word boundaries.

    • `\s+` seeks one or more whitespace characters.

    • `\1` references the first capturing group (whole word) via backreference.

  • The `text` string abounds in repeated whole words.

  • We deploy `re.findall()` to pinpoint matches.

  • Output highlights the matches: `['the the']`.

import re

pattern = r'(\b\w+\b)\s+\1'
text = 'the cat in the hat the the hat'

matches = re.findall(pattern, text)
print(matches)

Output

['the']

Example

  • Still by your side, the 're' module!

  • The pattern `r'(\w+)(?:\s+\1)+'` is brought to life. Delve into the details:

    • `(\w+)` captures one or more word characters as a group.

    • `(?:\s+\1)+` non−capturing group for one or more occurrences of repeated words.

  • The `text` string presents clusters of repeated words.

  • `re.findall()` is the tool of choice for identifying matches.

  • Output presents the matches: `['fun fun fun', 'with with']`.

import re

pattern = r'(\w+)(?:\s+\1)+'
text = 'coding is fun fun fun with coding'

matches = re.findall(pattern, text)
print(matches)

Output

['fun']

In conclusion, navigating the intricacies of matching characters after repetition in Python regex requires a fine−tuned understanding of capturing groups, backreferences, and lookaheads. These five illustrative examples shine a light on various scenarios where repetition can trip up your pattern−matching endeavors. Armed with these insights, you can confidently wield regex to untangle even the most perplexing text puzzles.

Updated on: 08-Sep-2023

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