Dec 7, 2021
Instructors: Kyrre T. Låberg
Helpers: Dan Michael O. Heggø, Mohamed Abdelhalim
Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. 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.
When: Dec 7, 2021. Add to your Google Calendar.
Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below). They are also required to abide by Software Carpentry's Code of Conduct.
Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:
Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.
Contact: Please email firstname.lastname@example.org for more information.
|Selecting Data, Sorting and Removing Duplicates, Filtering
|Calculating new values, Missing Data, Combining Data
|Data Hygiene, Creating and Modifying Data
|Programming with Databases - Python/R (if sufficient interest)
We will use this collaborative document 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.
SQL is a specialized programming language used with databases. We use a simple database manager called SQLite in our lessons. We will also use a graphical user interface called DB Browser for SQLite.
If you installed Anaconda, it also has a copy of SQLite
without support to
Instructors will provide a workaround for it if needed.
Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.
cmd and press [Enter])
setx HOME "%USERPROFILE%"
SUCCESS: Specified value was saved.
exit then pressing [Enter]
This will provide you with both Git and Bash in the Git Bash program.
The default shell in all versions of macOS is Bash, so no
need to install anything. You access Bash from the Terminal
See the Git installation video tutorial
for an example on how to open the Terminal.
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
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 macOS 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 a basic editor and the default that instructors use in the workshop. It is installed along with Git.
nano is a basic editor and the default that instructors use in the workshop. See the Git installation video tutorial for an example on how to open nano. It should be pre-installed.
Python is a popular language for research computing, and great for general-purpose programming as well. Installing all of its research 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., 3.6 is fine).
We will teach Python using the Jupyter 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).
bash Anaconda3-and then press tab. The name of the file you just downloaded should appear. If it does not, navigate to the folder where you downloaded the file, for example with:
cd DownloadsThen, try again.
press enter to approve the license. Press enter to approve the
default location for the files. Type
press enter to prepend Anaconda to your
(this makes the Anaconda distribution the default Python).
Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.