Jan 15-16, 2015
9:00 am - 4:30 pm
Instructors: Russell Alleen-Willems, Becca Blakewood, Tracy Fuentes, Emilia Gan, Chungho Kim, Ana Malagon, Maria Mckinley, Dominik Moritz, Ben Marwick, Marina Oganyan, Jaclyn Saunders, Peter Schmiedeskamp, Thomas Sibley, Rachael Tatman, Tiffany Timbers, Sam White, Earle Wilson
Helpers: Esther Le Grezause, Tania Melo
Software Carpentry's mission is to help researchers become more productive by teaching them basic lab skills for computing. This two-day hands-on workshop will cover basic concepts and tools; 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.
Please use the Etherpads (R room pad, Python room pad) and the #swcuw hashtag on Twitter during class. 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.
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.
Where: WRF Data Science Studio, Physics/Astronomy Tower (6th Floor), University of Washington, Seattle, WA. The workshop will be held in two rooms in the WRF Data Science Studio on the 6th floor of the Physics/Astronomy Tower. Get directions with OpenStreetMap or Google Maps.
We find that workshops go a lot better if people come in groups, e.g., 4-5 people from one lab, half a dozen from another department or institute, etc., so that they are less inhibited about asking questions, and can support each other afterwards. So while individual sign-ups are welcome, we encourage you to sign-up with a friend.
No previous programming skills or experience is required. The lesson contents and exercises are aimed at novices.
Contact: Please mail firstname.lastname@example.org 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||Building programs with Python or R|
To participate in a Software Carpentry workshop, you will need working copies of the software described below. Please make sure to install everything (or at least to download the installers) before the start of your workshop. Limited time will be available before the start of the workshop to assist with installation.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.
Bash is a commonly-used shell. Using a shell gives you more power to do more tasks more quickly with your computer.
Git is a state-of-the-art version control system. It 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.
Python is becoming very popular in scientific computing, and it's a great language for teaching general programming concepts due to its easy-to-read syntax. We teach with Python version 2.7, since it is still the most widely used. Installing all the scientific packages for Python individually can be a bit difficult, so we recommend an all-in-one installer.
R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we will use RStudio, an interactive development environment (IDE).
SQL is a specialized programming language used with databases. We use a simple database manager called SQLite, either directly or through a browser plugin.
Install Git for Windows by download and running the installer. This will provide you with both Git and Bash in the Git Bash program.
This installer requires an active internet connection
After installing Python and Git Bash:
nano is the editor installed by the Software Carpentry Installer,
it is a basic editor integrated into the lesson material.
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.
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
/Applications/Utilities). You may want
to keep Terminal in your dock for this workshop.
For OS X 10.8 and higher, install Git for Mac by downloading and running the installer. For older versions of OS X (10.5-10.7) use the most recent available installer for your OS available here. Use the Leopard installer for 10.5 and the Snow Leopard installer for 10.6-10.7.
ValueError unknown locale: UTF-8", see instructions on how to fix it here.
sqlite3 comes pre-installed on Mac OS X.
you may install the Firefox SQLite browser plugin described below.
The default shell is usually
but if your machine is set up differently
you can run it by opening a terminal and typing
There is no need to install anything.
If Git is not already available on your machine you can try
to install it via your distro's package manager
Kate is one option for Linux users.
In a pinch, you can use
which should be pre-installed.
You can download the binary files for your distribution
from CRAN. Or
you can use your package manager, e.g. for Debian/Ubuntu
apt-get install r-base or
yum install R.
Also, please install the
sqlite3 comes pre-installed on Linux.
you may install the Firefox SQLite browser plugin described below.
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 boot camp.)
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).
Instead of using
sqlite3 from the command line,
you may use this plugin
for Firefox instead.
To install it:
In newer versions of Firefox, the menu bar isn't always displayed. To make
it appear, use the
Alt key next to the space bar on your
keyboard, or consult
page from Firefox for additional help.