May 8-9, 2017
Instructors: Steve Bond, John Didion, David McGaughey
Helpers: Vinai Roopchansingh, Zhi Liu
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 manuscript "Best Practices for Scientific Computing".
Who: The course is aimed at students and researchers at the NIH who want to begin unlocking some of the computational tools that will allow them to manipulate their data more powerfully and with greater flexibility. This workshop if for a beginner audience, so you don't need to have any previous knowledge of the tools that will be presented.
Where: The workshop will take place in the glass walled training room at the rear of the NIH library in Bldg. 10.
Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating sytem (not a tablet, Chromebook, etc.). Several specific software packages must be installed prior to the workshop (listed below). If you do not have installation privileges on the hardware you will be bringing, please contact your system administrator at least a week beforehand. All participants are also required to abide by Software Carpentry's Code of Conduct.
Please be sure to complete these surveys before and after the workshop.
|08:45||Automating tasks with the Unix shell|
|13:00||Building programs with Python 1/2|
|08:45||Building programs with Python 2/2|
|13:00||Version control with Git|
We will use this Etherpad for chatting, taking notes, and sharing URLs and bits of code.
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.
Python is a popular language for general-purpose programming that has been widely adopted for scientific computing. Unfortunately, installing all of its scientific packages individually can be difficult, so we will be relying on an all-in-one installer called Anaconda.
For all instructions below, please ensure you install Python version 3
bash Miniconda3-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).
conda create -n bash m2-base git jupyter pandas tornado=4.4 console_shortcut activate bash conda install -c swc nanoContinue to press [Enter] at any prompts and wait for the 'C:\' to return after each command before progressing (the first step can take many minutes and look like it's stuck, so please be patient).
The default shell in all versions of Mac OS X is Bash.
conda install git jupyter pandas
The default shell is usually Bash, but if your machine is set up
differently you can run it by opening a terminal and typing
conda install git jupyter pandas
You will need an account at github.com for the Git lesson. Basic GitHub accounts are free, so please create one if you haven't already. You should also consider what personal information you'd like to reveal. For example, you may want to review these instructions for keeping your email address private.
It's nice to write code in a text editor that has been
optimized for it, with features like syntax highlighting
and autocomplete. For this workshop we will be using a stripped-down
editor called Nano that is already on your system and can be run directly from the shell environment.
Below are a few free options that you might find more feature-rich once you
become comfortable with the basic material. These are optional!
Also note, the default text editor on Mac OS X and Linux is usually set to something called 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 get back to the shell.