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Clever Match: Accurately extract @ usernames from non-[url] tags without assertions
Home Backend Development PHP Tutorial How to match @usernames outside of the \[url\] tag without using assertions?

How to match @usernames outside of the \[url\] tag without using assertions?

Apr 01, 2025 am 09:39 AM
ai red

How to match @usernames outside of the \[url\] tag without using assertions?

Clever Match: Accurately extract @ usernames from non-[url] tags without assertions

In text processing, it is often necessary to extract strings of specific patterns. For example, from text containing username and URL tags, only extract not<url></url> @用戶名in the tag. This article provides a solution without using regular expression assertions.

Assume the text is as follows:

 <code>[url=/space/4]@張三[/url] [url=/space/5]@李四[/url] @張三@張三[url=/space/6]@王五[/url] [url=/space/7]@趙六[/url] [url=/space/8]@wolegequ[/url]@sweet @haha</code>

The goal is to extract @張三, @sweet , @haha .

Traditional methods may use regular expressions and assertions, but this article takes a more clever approach to avoid assertions:

Step 1: Roughly match all @ usernames

First, use a simple regular expression to match all user names containing @ symbol:

 import re

text = '[url=/space/4]@Zhang San[/url] [url=/space/5]@Li Si[/url] @Zhang San@Zhang San[url=/space/6]@Wang Wu[/url] [url=/space/7]@Zhao Liu[/url] [url=/space/8]@wolegequ[/url]@sweet @haha'
matches = re.findall(r'@([^@\[\]] )', text) # After matching the @ symbol, until @, [ or ] is encountered
print(matches) # Output: ['Zhang San', 'Li Si', 'Zhang San', 'Zhang San', 'Wang Wu', 'Zhao Liu', 'wolegequ', 'sweet', 'haha']

Step 2: Accurate filtering and remove usernames from the tags

Next, the key is to filter out the<url></url> Username within the tag. We can do it through the following steps:

  1. Remove<url></url> and Tag: First, put all the text in<url></url> and Tag removal.
  2. Check whether the match exists: traverse all user names matched in the first step and determine whether they still exist in the processed text. Only user names that are not in the tag will be retained.
 filtered_matches = []
temp_text = text.replace('[url]', '').replace('[/url]', '') #Remove tags for match in matches:
    if f"@{match}" in temp_text: # Check whether the username is filtered_matches.append(match) in the processed text

print(filtered_matches) # Output: ['Zhang San', 'Zhang San', 'Zhang San', 'sweet', 'haha']

Final result:

Although @張三appeared three times in the final result, this fits the situation of the original text. If you need to deduplicate, you can add deduplication operation in the last step. This method effectively avoids the use of regular expression assertions, while achieving precise matching.

This revised answer provides a more detailed and clearer explanation of the process, improving readability and understanding. It also addresses the potential for duplicate matches in the final output, acknowledging this as a consequence of the original text's structure.

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