Event box

Date:
Tuesday, January 22, 2019
Time:
1:00pm - 3:00pm
Location:
WORKSHOPS: Data Science Center, 21536 Young Research Library

data: http://swcarpentry.github.io/shell-novice/data/data-shell.zip

The Unix shell has been around longer than most of its users have been alive. It has survived so long because it’s a power tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren’t typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources (including “high-performance computing” supercomputers). These lessons will start you on a path towards using these resources effectively.

Why do we learn to use the shell?

  • Allows users to automate repetitive tasks
  • And capture small data manipulation steps that are normally not recorded to make research reproducible

This lesson will introduce learners to fundamental skills needed for working with their computers through a command-line interface (using the bash shell). They will learn how to navigate their file system, computationally manipulate their files (e.g. copying, moving, renaming), search files, redirect output and write shell scripts.

This course will also cover why you might use the Bash shell and give some examples of typical usages.  WE will be using a collaborative note-taking tool as part of this workshop https://pad.carpentries.org/2019-01-22-bash.

Setup

To participate in a this workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.

The Carpentries maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.

The Bash Shell

Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.

Windows

Video Tutorial

  1. Install Nano, with is included in this executable provided by Software Carpentry: https://github.com/swcarpentry/windows-installer/releases/download/v0.3/SWCarpentryInstaller.exe
  2. Download the Git for Windows installer.
  3. Run the installer and follow the steps below:
    1. Click on "Next" four times (two times if you've previously installed Git). You don't need to change anything in the Information, location, components, and start menu screens.
    2. Select “Use the nano editor by default” and click on “Next”.
    3. Keep "Use Git from the Windows Command Prompt" selected and click on "Next". If you forgot to do this programs that you need for the workshop will not work properly. If this happens rerun the installer and select the appropriate option.
    4. Click on "Next".
    5. Keep "Checkout Windows-style, commit Unix-style line endings" selected and click on "Next".
    6. Select "Use Windows' default console window" and click on "Next".
    7. Click on "Install".
    8. Click on "Finish".
  4. If your "HOME" environment variable is not set (or you don't know what this is):
    1. Open command prompt (Open Start Menu then type cmd and press [Enter])
    2. Type the following line into the command prompt window exactly as shown:

      setx HOME "%USERPROFILE%"

    3. Press [Enter], you should see SUCCESS: Specified value was saved.
    4. Quit command prompt by typing exit then pressing [Enter]

This will provide you with both Git and Bash in the Git Bash program.

macOS

The default shell in all versions of macOS is Bash, so no need to install anything. You access Bash from the Terminal (found in /Applications/Utilities). See the Git installation video tutorial for an example on how to open the Terminal. You may want to keep Terminal in your dock for this workshop.

Linux

The default shell is usually Bash, but if your machine is set up differently you can run it by opening a terminal and typing bash. There is no need to install anything.

Registration has closed.

Event Organizer

Jamie Jamison
Leigh Phan
Profile photo of Data Science Center
Data Science Center