Software Carpentry's mission is to help scientists and engineers become more productive by teaching them basic lab skills for computing like program design, version control, data management, and task automation. This three-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 workshop is funded by NERC as part of the Advanced Training Short Courses programme (the application can be found here). Priority will thus be given to NERC-funded PhD students and early career researchers from the environmental sciences who should contact Andrew Walker for booking information. Some funding to cover travel and accommodation costs of these participants is avalable. Any unallocated spaces will be made generally avalable in mid December.
Instructors: Martin Callaghan, Aleksandra Pawlik, Andrew Walker, Aaron O'Leary, Peter Willetts
Helpers: Jo Leng, Grace Cox
Who: The course is aimed at postgraduate students and other scientists who are familiar with basic programming concepts (like loops, conditionals, arrays, and functions) but need help to translate this knowledge into practical tools to help them work more productively. Priority will be given to NERC-funded PhD students and early career researchers from the environmental sciences.
Requirements: Participants must bring a laptop with a few specific software packages installed (listed below).
Contact: Please mail email@example.com for more information.
|09:00||Arrival and Welcome|
|09:30||Using the shell to do more in less time|
|10:45||Using version control to manage information|
|13:00||Using version control to share information|
|15:15||Introduction to Python for Environmental Scientists|
|16:30||Sharing code: documentation and licencing|
|09:30||Python and good programming practice|
|13:00||Problem solving with Python|
|15:15||Handling and displaying environmental data with Python|
|16:15||Python and the shell|
|17:00||Pulling it all together|
The third day will attendees to begin to work together in small groups to develop useful tools for their own research. We will start with an introduction to the day at 09:00 and have a wrap-up session including time for groups show their progress from about 15:00. We will finish by 17:00 (lunch and breaks will be provided as detailed above).
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.
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.
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.
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 available here. Use the Leopard installer for 10.5 and the Snow Leopard installer for 10.6-10.7.
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.
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).
Sometimes the instructions above don't work. One way around this is to use a virtual machine (VM) rather than install software on their own computers. If all else fails you can try this using the following instructions:
There are a three extra tasks to undertake before the workshop in order to help make sure things run smoothly. Please try to do the following.
If you haven't already, please register for free accounts to
We would like to get started with bash quickly at the start of the workshop. It would be useful if everybody could take a look at the first three shell lessons, found here, here, and here, to either remind yourself of how a shell works, or to have a first look if this is new to you.
If you are new to Python, or you fear that your Python is rusty, it may be worth taking a look at an online introduction. Christopher Woods has a nice short introduction here. If you can follow this as far as "conditions", you are good to go. We will be reviewing this material anyway, so don't worry if you get stuck.
Finally, if you are confident, it may be worth checking your setup, following the steps outlined below. These tools can be useful in helping to diagnose problems either at, or before, the workshop.
To check you have the necessary software and tools:
We have gathered together the various links you will need and useful information below. These will remain accessable after the workshop and we will add to this list as the workshop progresses. Please read and abide by the code of conduct.
Much of the material we will be using during the workshop can be found online at github.com/andreww/SWC-leeds-intro. You will need this on your laptop. In order to download the material (and to check you have a working system with internet access) please start a new shell and type the following commands:
(typing return after each line). You should see something like "repository successfully cloned". Let us know if this does not work for you.
cd cd Desktop git clone https://github.com/andreww/SWC-leeds-intro
If you find yourself in a shell that you don't recognise, or in an editor that you can't get out of then see recognising prompts and how to exit.
Wilson G, Aruliah DA, Brown CT, Chue Hong NP, Davis M, et al. (2014) Best Practices for Scientific Computing. PLoS Biol 12(1): e1001745. doi:10.1371/journal.pbio.1001745.
Sandve GK, Nekrutenko A, Taylor J, Hovig E (2013) Ten Simple Rules for Reproducible Computational Research. PLoS Comput Biol 9(10): e1003285. doi:10.1371/journal.pcbi.1003285.
Noble WS (2009) A Quick Guide to Organizing Computational Biology Projects. PLoS Comput Biol 5(7): e1000424. doi:10.1371/journal.pcbi.1000424.
Ram K (2013) "git can facilitate greater reproducibility and increased transparency in science", Source Code for Biology and Medicine 2013, 8:7 doi:10.1186/1751-0473-8-7.
Glass, R. (2002) Facts and Fallacies of Software Engineering, Addison-Wesley, 2002. (PDF).