I really enjoyed this article, because now that I have a sampling of the class of problems that awk can help me with, I am more likely to use it. And it only took 10 minutes to get this overview. My brain is already buzzing with ideas on how I can use this with gron[1] that was mentioned a few days ago on HN.
We all need a compelling reason for a tool before investing the time for whatever Bible may exist, so "just grab" the Bible first instead isn't the most helpful advice :) But I do appreciate you flagging it!
[1] https://github.com/tomnomnom/gron
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P.S. For those who liked the writing style of this tutorial, you may enjoy these other ones on the IBM website by the same author Daniel Robbins: https://www.ibm.com/developerworks/views/linux/libraryview.j...
[0] https://en.wikipedia.org/wiki/Alfred_Aho
[1] https://en.wikipedia.org/wiki/Peter_J%2E_Weinberger
[2] https://en.wikipedia.org/wiki/Brian_Kernighan
[3] https://en.wikipedia.org/wiki/The_AWK_Programming_Language
Also, the gawk book is written by Arnold Robbins who is one of current maintainers of the tool and as per [1] gawk was started by David Trueman and Arnold.
[1] https://www.gnu.org/software/gawk/manual/html_node/Foreword3...
Yesterday, I wrote production level code using awk. It was either write the code in go which I figured would take all day. But I had really about an hour or so. 40 lines of shell script mixture of about 20 lines of awk and bash/sed/grep/tail/xargs/cut/cat/curl got the job done.
AWK is very freaking powerful if you learn to parse data with it.