Extracting Numbers with Python Regex: A Simple Guide to Match Numbers After Words

Learn how to effectively use Python regex to extract numbers from strings following specific words. This guide provides step-by-step instructions and examples.
---

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 match numbers after words

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Extracting Numbers with Python Regex: A Simple Guide to Match Numbers After Words

Using regular expressions (regex) in Python is a powerful technique for string manipulation and parsing. If you're dealing with URLs or structured strings that contain numbers after specific keywords, you may find the need to extract those numbers for further processing. In this guide, we will walk through how to extract numbers that come after specified words in a string using Python regex.

The Problem: Extracting Numbers from a String

Imagine you have a URL like this:

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

Your goal is to extract the numbers associated with word1 and word2, returning values like this:

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

The challenge arises when your current regex pattern doesn't work as expected. For example, you may have tried a regex like \word1(.*)[0-9]/, but it doesn't correctly capture the numbers you want.

Solution: Using Named Groups in Regex

Step 1: The Correct Regex Pattern

To resolve this issue, we need to develop a regex pattern that efficiently captures the numbers associated with each word. Particularly, using named groups can enhance our regex pattern by giving names to the groups we want to extract. Here's the regex we will use:

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

Breaking it down:

^ asserts the start of the string.

.* matches any character (except for line terminators) as many times as possible.

word1/ and word2/ match their respective keywords literally, looking for the numbers that follow.

(?P<w1>\d+ ) and (?P<w2>\d+ ) are named groups that will capture sequences of one or more digits (\d).

The $ asserts the end of the string.

Step 2: Implementing the Regex in Python

Now that we have our regex pattern ready, we can use it within a Python script. Here's how you can do that:

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

Step 3: Running the Script

When you run this script, it should output the desired results:

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

This method allows you to cleanly and effectively capture the numbers following each specified word in the string without unnecessary complications.

Conclusion

Regex may seem daunting at first, but with the correct pattern, it can greatly simplify tasks like extracting data from strings. By applying named groups, you not only enhance readability but also make your code more maintainable. Whether you're parsing URLs, extracting numbers, or analyzing data logs, mastering regex is a significant skill in a developer's toolkit. Happy coding!