Hello!
I am pleased to announce a new version of my CLI text processing with GNU awk ebook. This book will dive deep into field processing, show examples for filtering features, multiple file processing, how to construct solutions that depend on multiple records, how to compare records and fields between two or more files, how to identify duplicates while maintaining input order and so on. Regular expressions will also be discussed in detail.
Book links
To celebrate the new release, you can download the PDF/EPUB versions for free till 06-April-2025.
Or, you can read it online at https://learnbyexample.github.io/learn_gnuawk/
Interactive TUI apps
- 80+ exercises: https://github.com/learnbyexample/TUI-apps/blob/main/AwkExercises
- Brief tutorial: https://github.com/learnbyexample/TUI-apps/blob/main/AwkTutorial
Feedback
I would highly appreciate it if you’d let me know how you felt about this book. It could be anything from a simple thank you, pointing out a typo, mistakes in code snippets, which aspects of the book worked for you (or didn’t!) and so on.
Happy learning :)
Well, if you are comfortable with Python scripts, there’s not much reason to switch to
awk. Unless perhaps you are equatingawkto Python as scripting languages instead of CLI usage (likegrep,sed,cut, etc) as my ebook focuses on. For example, if you have space separated columns of data,awk '{print $2}'will give you just the second column (no need to write a script when a simple one-liner will do). This of course also allows you to integrate with shell features (like globs).As a practical example, I use
awkto filter and process particular entries from financial data (which is in csv format). Just a case of easily arriving at a solution in a single line of code (which I then save it for future use).Also AWK is made to be fast, right? I suppose doing something in CPython in a non efficient way might not be noticeable with a bit of text, but would show up with a large enough data stream.