The Linux Philosophy for SysAdmins, Tenet 01 — Data Streams, the universal interface
Everything in Linux revolves around streams of data – particularly text streams.
I recently Googled “data stream” and most of the top hits are concerned with processing huge amounts of streaming data in single entities such as streaming video and audio, or financial institutions processing streams consisting of huge numbers of individual transactions. This is not what we are talking about here although the concept is the same and a case could be made that current applications use the stream processing functions of Linux as the model for processing many types of data.
Regular Expressions #4: Pulling it all together
This series delves into the practical applications of regular expressions within Linux tools such as grep, sed, and awk, demonstrating how to simplify and optimize command-line tasks. The articles guide readers from basic to more complex uses of regex, emphasizing their usefulness in data stream transformation and text manipulation across various tools and programming languages. Through hands-on examples and resource recommendations, the series aims to enhance the reader’s understanding and proficiency with regex in diverse scenarios.
Regular Expressions #3: grep — Data flow and building blocks
In Regular Expressions #1: Introduction, I covered what they are and why they’re useful. In Regular Expressions #2: An example, we looked at a more complex example of the uses of regular expressions.
In this third of four articles you’ll learn how to make tighter matches with your regexes.
Regular Expressions #2: An example
In the previous article, Regular Expressions #1: Introduction, I covered what they are and why they’re useful.
The example in this article highlights the power and flexibility of the Linux command line, especially regular expressions, for their ability to automate common tasks.
Regular Expressions #1: Introduction
Regular expressions don’t have to invoke anxiety and fear, although they do for many of us. The function of regular expressions is to provide a highly flexible tool for matching strings of characters in a stream of data. When a match is found, the program’s action can be as simple as to pass the line of data in which it’s found on to STDOUT, or as copmplex as replacing that string with another.
Working with data streams on the Linux command line
Learn to connect data streams from one utility to another using STDIO. Everything in Linux revolves around streams of data—particularly text streams. Data streams are...