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Regular expression (also abbreviated to regex) really is a powertool any programmer should know. It was and is one of the things I most liked learning, as it provides you with immediate, godlike powers that can speed up your (data science) workflow tenfold.
I’ve covered many regex related topics on this blog already, but thought I’d combine them and others in a nice curated overview — for myself, and for you of course, to use.
If you have any materials you liked, but are missing, please let me know!
Contents
Introduction & Learning
Reading
- https://github.com/ziishaned/learn-regex
- https://www.oreilly.com/content/an-introduction-to-regular-expressions/
- https://ryanstutorials.net/regular-expressions-tutorial/
Tutorials (interactive)
- https://regexone.com/
- https://www.hackerrank.com/domains/regex?filters%5Bsubdomains%5D%5B%5D=re-introduction
Video
Corey Shafer
The Coding Train
Language-specific
Python
- https://www.python-course.eu/re.php
- https://docs.python.org/2/howto/regex.html
- https://docs.python.org/2/library/re.html
- https://developers.google.com/edu/python/regular-expressions
Corey Shafer
R
- https://stringr.tidyverse.org/articles/regular-expressions.html
- https://paulvanderlaken.com/2017/10/03/regular-expressions-in-r-part-1-introduction-and-base-r-functions/
Roger Peng
Testing & Debugging
debuggex.com
regex101.com
regextester.com | regexpal.com
regexr.com
rubular.com
pythex.com
Fun
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