Book Image

Hands-On Data Science with the Command Line

By : Jason Morris, Chris McCubbin, Raymond Page
Book Image

Hands-On Data Science with the Command Line

By: Jason Morris, Chris McCubbin, Raymond Page

Overview of this book

The Command Line has been in existence on UNIX-based OSes in the form of Bash shell for over 3 decades. However, very little is known to developers as to how command-line tools can be OSEMN (pronounced as awesome and standing for Obtaining, Scrubbing, Exploring, Modeling, and iNterpreting data) for carrying out simple-to-advanced data science tasks at speed. This book will start with the requisite concepts and installation steps for carrying out data science tasks using the command line. You will learn to create a data pipeline to solve the problem of working with small-to medium-sized files on a single machine. You will understand the power of the command line, learn how to edit files using a text-based and an. You will not only learn how to automate jobs and scripts, but also learn how to visualize data using the command line. By the end of this book, you will learn how to speed up the process and perform automated tasks using command-line tools.
Table of Contents (8 chapters)

Detached processing

Detached processing runs a command in the background. This means that terminal control is immediately returned to the shell process while the detached process runs in the background. With job control, these back grounded processes can be resumed in the foreground or killed directly.

How to background a process

Remember when we used the double ampersand to conditionally execute two commands that run one after another? By using a single ampersand, you can fork a process in the background and let it run. Let's use the command to save to a new file and run in the background:

cat all_reviews.csv | awk -F ","  '{print $4}' | grep -i Packt > background_words.txt &

This will take...