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Скачать или смотреть Mastering Python Regex for Multiline String Matching

  • vlogize
  • 2025-10-02
  • 0
Mastering Python Regex for Multiline String Matching
Python regex matching multiline stringpythonregex
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Описание к видео Mastering Python Regex for Multiline String Matching

Discover how to effectively use `Python regex` to match multiline strings and extract specific content seamlessly.
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This video is based on the question https://stackoverflow.com/q/62641472/ asked by the user 'Houssam Hsm' ( https://stackoverflow.com/u/13457080/ ) and on the answer https://stackoverflow.com/a/62641759/ provided by the user 'xpqz' ( https://stackoverflow.com/u/4432671/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Python regex matching multiline string

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
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Mastering Python Regex for Multiline String Matching

When working with text data in Python, especially when it involves multiline strings, one might often find the need to extract specific information using regular expressions, or regex. Whether you are handling data from reports or user inputs, Python's regex module can be a powerful tool. In this guide, we will explore a common problem related to regex matching in multiline strings and provide a clear solution.

The Challenge

Imagine you have a multiline string that contains various details, and you want to extract specific segments of the text. Here's a sample string we will work with:

[[See Video to Reveal this Text or Code Snippet]]

The goal is to extract everything between the Applicants: and Inventors: lines, which in our case would be the following strings:

Silixa Ltd.

Chevron U.S.A. Inc. (Incorporated in USA - California)

However, if you try to use the re.MULTILINE flag in your regex, you may not achieve the desired result. Let's take a look at an initial attempt at capturing this information.

Initial Attempt Using re.MULTILINE

Here's what the initial regex code looks like:

[[See Video to Reveal this Text or Code Snippet]]

Output:

[[See Video to Reveal this Text or Code Snippet]]

As you can see, this code only captures the Silixa Ltd. portion, but not the additional information that follows. So, how do we address this limitation?

The Solution Using re.DOTALL

To successfully capture everything you need between the Applicants and Inventors keywords, you should switch to using the re.DOTALL flag. This flag allows the dot (.) to match newline characters, which is exactly what you need for multiline strings.

Here is the revised code:

[[See Video to Reveal this Text or Code Snippet]]

Expected Output:

[[See Video to Reveal this Text or Code Snippet]]

Breakdown of the Regex:

Applicants: – Specifies where the capture starts.

(.*?) – Captures everything between Applicants: and Inventors: non-greedily (as little as possible).

Inventors: – Specifies where the capture ends.

Why Does This Work?

The key reason this works, as mentioned, is the re.DOTALL flag. Under normal circumstances, the . character does not match newline characters, which can make it challenging to capture multiline data; however, with re.DOTALL, the dot can now match any character including newlines.

Conclusion

Regex can be a formidable tool for text processing when used effectively. By understanding the use of flags like re.DOTALL versus re.MULTILINE, you can significantly enhance your ability to extract the data you need from multiline strings in Python. Give this a try in your programming projects and see how it simplifies your text handling tasks!

For further exploration, consider trying to modify the regular expression to capture different patterns or data structures. Happy coding!

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