Find us on GitHub

University of Washington - Seattle

March 31st - April 1st, 2016

9:00 am - 4:30 pm

Instructors: Ariel Rokem, Bernease Herman, Jes Ford, Bryna Hazelton, Dave Williams, Jeffrey Arnold, Jimmy O'Donnell, Abraham Flaxman, Valentina Staneva, Allison Smith, Billy Charlton

Helpers: Emilia Gan, Jeremy McGibbon, Rick Riehle, Margaret Hughes, Rachael Tatman, Dwight Barry, Adam Richie-Halford, Mike Vlah

General Information

Software Carpentry's mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".

Who: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: WRF Data Science Studio, Physics/Astronomy Tower (6th Floor), University of Washington, Seattle, WA. Get directions with OpenStreetMap or Google Maps.

Requirements: Participants must bring a laptop with a few specific software packages installed (listed below). They are also required to abide by Software Carpentry's Code of Conduct.

Contact: Please mail arokem@gmail.com for more information.

Schedule

Surveys

Please be sure to complete these surveys before and after the workshop.

Pre-workshop Survey

Post-workshop Survey

We are running two full concurrent sessions, one in each room. There are two key differences between the sessions. First is that one session will teach programming with Python and the other session will teach programming with R, all the other class content will be the same.

As a rough guide to choosing which language to learn, Python might be best for you if you're working in the natural or physical sciences, and if you're in the social sciences and humanities then R might be more valuable.

The second difference between the two sessions is that the instructors in the Python session mostly come from the natural and physical sciences, while the instructors in the R session mostly come from the social sciences and humanities. These is simply a convenient way to organise the lessons, and of course you're welcome to join whichever session you think will benefit you the most. The choice is completely up to you.

Day 1

09:00 Automating tasks with the Unix shell
10:30 Coffee break
10:45 Automating tasks with the Unix shell (cotd.)
12:00 Lunch break
13:00 Intro to Python or R
14:30 Coffee break
14:45 Intro to Python or R (cotd.)
16:00 Wrap-up

Day 2

09:00 Version control with Git
10:30 Coffee break
10:45 Version control with Git (cotd.)
12:00 Lunch break
13:00 Building programs with Python or R
14:30 Coffee break
14:45 Building programs with Python or R (cotd.)
16:00 Wrap-up

Etherpad: http://pad.software-carpentry.org/2016-03-31-uw.
We will use this Etherpad for chatting, taking notes, and sharing URLs and bits of code.

Syllabus

The Unix Shell

  • Files and directories
  • History and tab completion
  • Pipes and redirection
  • Looping over files
  • Creating and running shell scripts
  • Finding things
  • Reference...

Programming in Python

  • Using libraries
  • Working with arrays
  • Reading and plotting data
  • Creating and using functions
  • Loops and conditionals
  • Defensive programming
  • Using Python from the command line
  • Reference...

Version Control with Git

  • Creating a repository
  • Recording changes to files: add, commit, ...
  • Viewing changes: status, diff, ...
  • Ignoring files
  • Working on the web: clone, pull, push, ...
  • Resolving conflicts
  • Open licenses
  • Where to host work, and why
  • Reference...

Programming in R

  • Working with vectors and data frames
  • Reading and plotting data
  • Creating and using functions
  • Loops and conditionals
  • Using R from the command line
  • Reference...

Setup

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

We 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

  1. Download the Git for Windows installer.
  2. Run the installer and follow the steps bellow:
    1. Click on "Next".
    2. Click on "Next".
    3. Click on "Next".
    4. Click on "Next".
    5. Click on "Next".
    6. Select "Use Git from the Windows Command Prompt" 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.
    7. Click on "Next". Keep "Checkout Windows-style, commit Unix-style line endings" selected.
    8. Select "Use Windows' default console window" and click on "Next".
    9. Click on "Next".
    10. Click on "Finish".

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

Mac OS X

The default shell in all versions of Mac OS X is Bash, so no need to install anything. You access Bash from the Terminal (found in /Applications/Utilities). 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.

Git

Git is a version control system that lets you track who made changes to what when and has options for easily updating a shared or public version of your code on github.com. You will need a supported web browser (current versions of Chrome, Firefox or Safari, or Internet Explorer version 9 or above).

Windows

Git should be installed on your computer as part of your Bash install (described above).

Mac OS X

For OS X 10.9 and higher, install Git for Mac by downloading and running the most recent "mavericks" installer from this list. After installing Git, there will not be anything in your /Applications folder, as Git is a command line program. For older versions of OS X (10.5-10.8) use the most recent available installer labelled "snow-leopard" available here.

Linux

If Git is not already available on your machine you can try to install it via your distro's package manager. For Debian/Ubuntu run sudo apt-get install git and for Fedora run sudo yum install git.

Text Editor

When you're writing code, it's nice to have a text editor that is optimized for writing code, with features like automatic color-coding of key words. The default text editor on Mac OS X and Linux is usually set to Vim, which is not famous for being intuitive. if you accidentally find yourself stuck in it, try typing the escape key, followed by :q! (colon, lower-case 'q', exclamation mark), then hitting Return to return to the shell.

Windows

nano is a basic editor and the default that instructors use in the workshop. To install it, download the Software Carpentry Windows installer and double click on the file to run it. This installer requires an active internet connection.

Others editors that you can use are Notepad++ or Sublime Text. Be aware that you must add its installation directory to your system path. Please ask your instructor to help you do this.

Mac OS X

nano is a basic editor and the default that instructors use in the workshop. It should be pre-installed.

Others editors that you can use are Text Wrangler or Sublime Text.

Linux

nano is a basic editor and the default that instructors use in the workshop. It should be pre-installed.

Others editors that you can use are Gedit, Kate or Sublime Text.

Python

Python is a popular language for scientific computing, and great for general-purpose programming as well. Installing all of its scientific packages individually can be a bit difficult, so we recommend Anaconda, an all-in-one installer.

Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., 3.4 is fine).

We will teach Python using the IPython notebook, a programming environment that runs in a web browser. For this to work you will need a reasonably up-to-date browser. The current versions of the Chrome, Safari and Firefox browsers are all supported (some older browsers, including Internet Explorer version 9 and below, are not).

Windows

  1. Open http://continuum.io/downloads with your web browser.
  2. Download the Python 3 installer for Windows.
  3. Install Python 3 using all of the defaults for installation except make sure to check Make Anaconda the default Python.

Mac OS X

  1. Open http://continuum.io/downloads with your web browser.
  2. Download the Python 3 installer for OS X.
  3. Install Python 3 using all of the defaults for installation.

Linux

  1. Open http://continuum.io/downloads with your web browser.
  2. Download the Python 3 installer for Linux.
  3. Install Python 3 using all of the defaults for installation. (Installation requires using the shell. If you aren't comfortable doing the installation yourself stop here and request help at the workshop.)
  4. Open a terminal window.
  5. Type 
    bash Anaconda-
    and then press tab. The name of the file you just downloaded should appear.
  6. Press enter. You will follow the text-only prompts. When there is a colon at the bottom of the screen press the down arrow to move down through the text. Type yes and press enter to approve the license. Press enter to approve the default location for the files. Type yes and press enter to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).

R

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

Windows

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE.

Mac OS X

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.

Linux

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R). Also, please install the RStudio IDE.

License Blog GitHub Twitter Issues