Linux Shell Programming Pocket Primer

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Free Download Linux Shell Programming: Pocket Primer
by Oswald Campesato
English | 2023 | ISBN: 1683926196 | 254 pages | True EPUB | 7.3 MB
The goal of this book is to introduce readers to an assortment of powerful command line utilities that can be combined to create simple, yet powerful shell scripts. While all examples and scripts use the "bash" command set, many of the concepts translate into other forms of shell scripting (ksh, sh, csh), including the concept of piping data between commands, regular expression substitution and the sed and awk commands. Aimed at a reader relatively new to working in a bash environment, the book is comprehensive enough to be a good reference and teach a few new tricks to those who already have some experience with creating shells scripts. The book features companion files with code samples from the book (available with Amazon proof of purchase for free downloading from the publisher by writing to [email protected]).

Features
+Covers extensive topics, code samples, and scripting utilities
+Includes material on piping data between commands, regular expression substitution, cleaning datasets, and the sed and awk commands
+Features companion files with code samples from the book (available with Amazon proof of purchase for free downloading from the publisher by writing to [email protected])
Table of Contents
1: Introduction. 2: Files and Directories. 3: Useful Commands. 4: Conditional Logic and Loops. 5: Filtering Data with grep. 6: Transforming Data with sed. 7: Doing Everything Else with awk. 8: Introduction to Shell Scripts and Functions. 9: Shell Scripts with the grep and awk Commands. 10: Miscellaneous Shell Scripts. Index.
About the Author
Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Cruz and specializes in Deep Learning, NLP, Android, and Python. He is the author/co-author of over forty-five books including Data Science Fundamentals Pocket Primer , Python 3 for Machine Learning, and the Python Pocket Primer (Mercury Learning).

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