4 Feb, 2018
9:00 am - 5:00 pm
Instructors: Damien Irving
Helpers: Mitchell Black, Nic Hannah
Python is rapidly emerging as the programming language of choice for data analysis in the weather, climate and ocean sciences. By consulting online tutorials and help pages, most researchers in this community are able to pick up the basic syntax and programming constructs (e.g. loops, lists and conditionals). This self-taught knowledge is sufficient to get work done, but it often involves spending hours to do things that should take minutes, reinventing a lot of wheels, and a nagging uncertainty at the end of it all regarding the reliability and reproducibility of the results. To help address these issues, this Data Carpentry workshop will cover a suite of programming best practices that aren’t so easy to glean from a quick Google search.
Who: The course is aimed at graduate students and other researchers. Participants must already be using Python for their data analysis. They don't need to be highly proficient, but a strong familiarity with Python syntax and basic constructs such as loops, lists and conditionals (i.e. if statements) is required.
Where: Room 232, Mathews Building, UNSW Kensington Campus. Get directions with OpenStreetMap or Google Maps.
When: 4 Feb, 2018. 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 Data Carpentry's Code of Conduct.
Contact: Please email irving.damien@gmail.com for more information.
Surveys
Please be sure to complete these surveys before and after the workshop.
Timetable
| 09:00-10:30 | PyAOS software stack, software installation using conda, data visualisation |
| 10:30-11:00 | Morning tea (provided) |
| 11:00-12:30 | Functions, command line programs |
| 12:30-01:30 | Lunch (not provided) |
| 01:30-03:00 | Version control using Git and GitHub, vectorisation |
| 03:00-03:30 | Afternoon tea (provided) |
| 03:30-05:00 | Defensive programming, data provenance |
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
To participate in the 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.
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 Mac OS X is Bash, so no
need to install anything. You access Bash from the Terminal
(found in
/Applications/Utilities).
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
install anything.
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).
You will need an account at github.com for parts of the Git lesson. Basic GitHub accounts are free. We encourage you to create a GitHub account if you don't have one already. Please consider what personal information you'd like to reveal. For example, you may want to review these instructions for keeping your email address private provided at GitHub.
Git should be installed on your computer as part of your Bash install (described above).
For OS X 10.9 and higher, install Git for Mac
by downloading and running the most recent "mavericks" installer from
this list.
After installing Git, there will not be anything in your /Applications folder,
as Git is a command line program.
For older versions of OS X (10.5-10.8) use the
most recent available installer labelled "snow-leopard"
available here.
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 dnf install git.
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 a basic editor and the default that instructors use in the workshop. To install it, download the Data Carpentry Windows installer and double click on the file to run it. This installer requires an active internet connection.
Others editors that you can use are Notepad++ or Sublime Text. Be aware that you must add its installation directory to your system path. Please ask your instructor to help you do this.
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.
Others editors that you can use are Text Wrangler or Sublime Text.
nano is a basic editor and the default that instructors use in the workshop. It should be pre-installed.
Others editors that you can use are Gedit, Kate or Sublime Text.
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.
yes and
press enter to approve the license. Press enter to approve the
default location for the files. Type yes and
press enter to prepend Anaconda to your PATH
(this makes the Anaconda distribution the default Python).