A starting point for discovering the wonderful world of Git and GitHub in the context of Research Workflows.

• Zoom: https://berkeley.zoom.us/j/162527059
• Sign up for github, and verify your email.
• Live chat for our workshop: [](https://gitter.im/dlab-berkeley/git-fundamentals?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge

Note: We'll install git together as a group during today's workshop, however you're welcome to go ahead on your own if you like.

• Command line tools (you'll need this!):

  • GitHub recommends the official Git installer
  • I recommend homebrew for hackers on OS X
  • And it's easier to use your package manager (apt, yum, ...) for Unix, etc.

• GUI tools

  • GitHub Desktop App
  • SourceTree
  • Many others are available, and you can search for even more!

• Integration for your text editor!

  • Atom
  • Vim fugitive
  • Emacs Magit
  • Sublime Text 2

• To choose a default editor to use with git:

Atom	$ git config --global core.editor "atom --wait"
nano	$ git config --global core.editor "nano -w"

Any time you need quick access to a shell command line somewhere other than your laptop you can use (for free!) Google Cloud Shell: https://cloud.google.com/shell/

Try launching Cloud Shell now in your browser by clicking this link:

https://console.cloud.google.com/home/dashboard?cloudshell=true

Then run these commands in the Cloud Shell window:

git clone https://github.com/dlab-berkeley/git-fundamentals/
cd git-fundamentals
./rstudio-on-gcp.sh

Software Carpentry tutorial: https://swcarpentry.github.io/git-novice/

• Basic commands cheat sheet(s) (Note the links to other cheat sheets!)
• Gamified git
• GitHub sponsors this.
• Where does "help" go from GitHub? Here.
• Linux commands cheat sheet (also mostly works for OS X command line).
• git - the simple guide
• The visual git guide

• Read the Flight rules for Git, a guide for using Git and what to do when things go wrong.

Flight Rules are the hard-earned body of knowledge recorded in manuals that list, step-by-step, what to do if X occurs, and why. Essentially, they are extremely detailed, scenario-specific standard operating procedures.

• A problem-focused exploration of git features is available in @jkitzes' Data Science Lessons
• An IPython notebook (of course!) from @fperez.