Jun 25-26 2015
9:00 am - 4:30 pm
Instructors: Sam White, Ariel Rokem, Ana Malagon, Thomas Sibley, Rachael Tatman, Peter Schmiedeskamp
Helpers: Thomas Sibley, Margaret Hughes, Jason Portenoy
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. The goal of the workshop is for participants to acquire skills to:
This workshop is supported by the UW eScience Institute. Priority will thus be given to UW-affiliated students, staff and faculty. We have a UW Software Carpentry email list that you can join to keep up with local plans, to get advice, ask questions, etc. after the workshop is over.
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, staff, faculty and other researchers at UW. No previous experience with programming is required. If you do have experience in the topics in the syllabus and want to help, send us an email. The instructors are UW students, staff, faculty and other active researchers. We use the #swcuw hashtag on Twitter during class.
Contact: Please mail email@example.com for more information.
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.
|09:00||Automating tasks with the Unix shell|
|13:00||Intro to Python or R|
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. Once you are done installing the software listed below, please go to this page, which has instructions on how to test that everything was installed correctly.
If you haven't already, please register for a free account at GitHub. If you have an edu email, you can register for a free educational account which has some features usually only found in paid accounts. We will use this service as part of the lesson on version control.
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.
nano is the editor installed by the Software
Carpentry Installer, it is a basic editor integrated into the
Notepad++ is a popular free code editor for Windows. Be aware that you must add its installation directory to your system path in order to launch it from the command line (or have other tools like Git launch it for you). Please ask your instructor to help you do this.
Kate is one option for
Linux users. In a pinch, you can use
should be pre-installed.
Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.
Install Git for Windows by downloading and running the installer. This will provide you with both Git and Bash in the Git Bash program.
It installs and configures
nano (Among other things)
This installer requires an active internet connection.
After installing Git Bash:
The default shell in all versions of Mac OS X is bash, so no
need to install anything. You access bash from the Terminal
/Applications/Utilities). You may want to keep
Terminal in your dock for this workshop.
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
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).
Git should be installed on your computer as part of your Bash install (described above).
For OS X 10.8 and higher, install Git for Mac
by downloading and running
After installing Git, there will not be anything in your
as Git is a command line program.
For older versions of OS X (10.5-10.7) use the
most recent available installer for your
here. Use the Leopard installer for 10.5 and the Snow
Leopard installer for 10.6-10.7.
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.
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 an all-in-one installer.
Regardless of how you choose to install it, please make sure you install Python version 2.x and not version 3.x (e.g., 2.7 is fine but not 3.4). Python 3 introduced changes that will break some of the code we teach during the workshop.
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).
We recommend the all-in-one scientific Python installer Anaconda. (Installation requires using the shell and if you aren't comfortable doing the installation yourself just download the installer and we'll help you at the workshop.)
bash Anaconda-and then press tab. The name of the file you just downloaded should appear.
yesand press enter to approve the license. Press enter to approve the default location for the files. Type
yesand press enter to prepend Anaconda to your
PATH(this makes the Anaconda distribution the default Python).