The Linux command line for scientific computing

Welcome to the class!

Below are the instructions on how to use this repository.

Note: The videos are restricted to ICL students and staff.

Setup

1. This class uses Jupyter Notebooks, decide if you want to use Google Colab or Anaconda on your own computer. Make sure that you test your setup before the class so you can follow from the start. Try the following on one or two notebooks

   • Method 1 - Google Colab in your browser and a command line application:

     • Log into your Google account
     • Click on blue Colab links below
     • When open, save the notebooks in your drive with "File"->"Save a copy in Drive". This will let you execute commands in the code cells.
     • In notebooks 2 to 8, test the first code cell to download the practice data - this will have to be done for each notebook during the class, the data does not persist
     • Windows users will also need a separate command line application; choose one of the following.
       • Git for Windows - relatively easy to install, no admin privileges required, installation video
       • Windows subsystem for Linux - recommended but requires admin privileges
     • Download practice files for use with a command line application. Place the data-shell directory on your desktop. Alternatively, you can use one of the following commands directly on the command line.
       • wget https://kmichali.github.io/SC-shell-novice/data/data-shell.zip; unzip data-shell.zip
       • curl https://kmichali.github.io/SC-shell-novice/data/data-shell.zip -o data-shell.zip; unzip data-shell.zip

   • Method 2 - Anaconda on your own computer (please note that Windows users reported problems with using the course notebooks without enabling Windows subsystem for Linux - see above):

     • Download this repository (that already includes the data) - instruction video
     • Open a notebook in Anaconda using Jupyter Notebook - instruction video
     • Jupyter Notebook contains in-built Terminal that will be used for command line practice
     • The practice files are already included in the repository

Using the repository for learning (if you are attending a Graduate School class, we will do this together)

1. In the directory "notebooks", there are eight notebooks with video links.
   • 01 - Introduction and setup
     • 
     • video
   • 02 - Navigating files and directories
     • 
     • video 1
     • video 2
   • 03 - Working with files and directories
     • 
     • video 1
     • video 2
   • 04 - Pipes and filters
     • 
     • video 1
     • video 2
   • 05 - For loops
     • 
     • video
   • 06 - Shell scripts
     • 
     • video 1
     • video 2
   • 07 - Finding things
     • 
     • video 1
     • video 2
   • 08 - Nelle's shell script
     • 
     • video 1
     • video 2
     • video 3
     • video 4
2. Open the first notebook in Anaconda or in Colab.
3. Keep doing so until you have seen all eight notebooks.

Happy scripting!

Notebooks 1 to 7 are based on a snapshot of the Unix Shell lesson from the Software Carpentry.

Further study

• Local tutorials - systematic with lots of examples (ICL access only) - Bash fundamentals, Bash scripting
• Steve Parke's Bash tutorial - with Linux administration spin
• The Linux documentation project - the most complete guide you can imagine
• The Bash hackers wiki - if you are looking for cool features
• Short examples to play with

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