Software Carpentry: IMAS

General Information

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 paper "Best Practices for Scientific Computing".

Who: The course is aimed at graduate students and other researchers.

Where: UTAS waterfront Hobart. Get directions with OpenStreetMap or Google Maps.

Requirements: Participants must bring a laptop with a few specific software packages installed (listed below). They are also required to abide by Software Carpentry's Code of Conduct.

Contact: Please mail DaSH for more information.

Schedule

This workshop was run within the regular Data Science Hobart Sessions (DaSH). These informal regular sessions that focus on up-skilling the local community in computer skills (these are held at 9-ish every-ish Friday morning). It was decided by organisers and the regular attendees that the Software Carpentry Course material would make a great series to include. Mike and Tom, recently graduated SWC instructors, agreed to organise and run the sessions. Overall this format worked very well. It was open to all comers, with sessions largely focused on entry level issues and instruction.

General feedback and outcomes

People thought the sessions were very useful, especially our focus on the background, the why to use, the when to use, before the how.
Whilst the sessions were mostly based at entry level (zero coding expereince), adapting to the background of who was in attendence, experienced users also in attendence all mentioned how they still got a few 'tips' out of these intro-sessions, a testament to the design of the lessons.
An external institution requested a separate session on higher level R tools and approaches.
The 'early start' Q&A sessions were very popular with helpers and attendees.
The format of a 'start session' for each lesson, with the expectation of completing the lessons later worked very well.
Re arranging the schedule of lessons such that SQL was second, and Git was last worked well.
- SQL fit very well conceptually at the beginning (second session), as it allows the natural framing of how 'large existing managed datasets' interact 'small personal esoteric datasets'. It also was a very easy language to teach and learn, as it uses keywords, rather than index-notation, to call/execute commands, making it a bit more intuative for entry-level students.
- Git worked well as the final session. It fit easily into 'where too now', whilst also tying together all the other tools.

Day 0 (setup only): 2015-06-26

09:00-11:00	Introduction to Software Carpentry
	Getting set up - Installing VirtualBox, SWC VM; Getting access to the wifi network.
	The benefits of learning how to use code
	Best Practice Science
	Attendence: ~60

Day 1: 2015-07-03

08:30-09:00	Q&A session based on previous week: Answer questions, sort through issues.
09:00-11:00	Topic 1: The Unix Shell (bash)
	Sort out any set-up issues people had during the last week.
	Gave an intro to bash: background, why and when to use it, etc.
	Then we moved into the SWC bash lesson we did as much as we could (about the first 2-3 parts), there was an expectation of attendees doing homework to finish the lesson.
	Attendence: ~60

Day 2: 2015-07-10

08:30-09:00	Q&A session based on previous week/s: Answer questions, sort through issues.
09:00-11:00	Topic 2: SQL (simple query language)
	Gave an intro on SQL - What it is, why its used and under what circumstances it is best to use it.
	Then moved into the SWC SQL lesson we did as much as we could (about the first 2-3 parts), there was an expectation of attendees doing homework to finish the lesson.
	Attendence: ~60

Day 3: 2015-07-17

08:30-09:00	Q&A session based on previous week/s: Answer questions, sort through issues.
09:00-11:00	Topic 3: The R language
	Gave an intro of about R - What it is, why its used and under what circumstances it is best to use it.
	Then moved into the SWC R lesson we did as much as we could (about the first 2-3 parts), there was an expectation of attendees doing homework to finish the lesson.
	Attendence: ~40

Day 4: 2015-07-24

08:30-09:00	Q&A session based on previous week/s: Answer questions, sort through issues.
09:00-11:00	Topic 4: The python language
	Gave an intro of about python - What it is, why its used and under what circumstances it is best to use it, as well as how it is different to R.
	Then moved into the SWC python lesson we did as much as we could (about the first 2-3 parts), there was an expectation of attendees doing homework to finish the lesson.
	Attendence: ~40

Day 5: 2015-07-31

08:30-09:00	Q&A session based on previous week/s: Answer questions, sort through issues.
09:00-11:00	Topic 5: Git (a version control system)
	Gave an intro about Version Control - What it is, why its used and under what circumstances it is best to use it. Including how this approach is different to alternatives.
	Then moved into the SWC Git lesson we did as much as we could (about the first 2-3 parts), there was an expectation of attendees doing homework to finish the lesson.
	We then gave an example of a working git repository, how to find it, how to clone it to your personal computer, how to push-to and pull-from.
	Attendence: ~40

Poster

Syllabus

The Unix Shell

Files and directories
History and tab completion
Pipes and redirection
Looping over files
Creating and running shell scripts
Finding things
Reference...

Programming in Python

Using libraries
Working with arrays
Reading and plotting data
Creating and using functions
Loops and conditionals
Defensive programming
Using Python from the command line
Reference...

Programming in R

Working with vectors and data frames
Reading and plotting data
Creating and using functions
Loops and conditionals
Using R from the command line
Reference...

Version Control with Git

Creating a repository
Recording changes to files: add, commit, ...
Viewing changes: status, diff, ...
Ignoring files
Working on the web: clone, pull, push, ...
Resolving conflicts
Open licenses
Where to host work, and why
Reference...

Managing Data with SQL

Reading and sorting data
Filtering with where
Calculating new values on the fly
Handling missing values
Combining values using aggregation
Combining information from multiple tables using join
Creating, modifying, and deleting data
Programming with databases
Reference...

Setup

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.

The Bash Shell

Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.

Windows

Install Git for Windows by downloading and running the installer. This will provide you with both Git and Bash in the Git Bash program.

Mac OS X

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). You may want to keep Terminal in your dock for this workshop.

Linux

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

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).

Windows

Git should be installed on your computer as part of your Bash install (described above).

Mac OS X

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.

Linux

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 yum install git.

Text Editor

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.

Windows

nano is a basic editor and the default that instructors use in the workshop. To install it, download the Software 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.

Mac OS X

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 Text Wrangler or Sublime Text.

Linux

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

Python is a popular language for scientific computing, and great for general-purpose programming as well. Installing all of its scientific packages individually can be a bit difficult, so we recommend an all-in-one installer.

Regardless of how you choose to install it, please make sure you install Python version 2.x and not version 3.x (e.g., 2.7 is fine but not 3.4). Python 3 introduced changes that will break some of the code we teach during the workshop.

We will teach Python using the IPython 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).

Windows

Download and install Anaconda.
Download the default Python 2 installer (do not follow the link to version 3). Use all of the defaults for installation except make sure to check Make Anaconda the default Python.

Mac OS X

Download and install Anaconda.
Download the default Python 2 installer (do not follow the link to version 3). Use all of the defaults for installation.

Linux

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.)

Download the installer that matches your operating system and save it in your home folder. Download the default Python 2 installer (do not follow the link to version 3).
Open a terminal window.
Type
```
bash Anaconda-
```
and then press tab. The name of the file you just downloaded should appear.
Press enter. You will follow the text-only prompts. When there is a colon at the bottom of the screen press the down arrow to move down through the text. Type 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).

Once you are done installing the software listed above, please go to this page, which has instructions on how to test that everything was installed correctly.

R

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

Windows

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE.

Mac OS X

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.

Linux

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R). Also, please install the RStudio IDE.

SQLite

SQL is a specialized programming language used with databases. We use a simple database manager called SQLite in our lessons.

Windows

The Software Carpentry Windows Installer installs SQLite for Windows. If you used the installer to configure nano, you don't need to run it again.

Mac OS X

SQLite comes pre-installed on Mac OS X.

Linux

SQLite comes pre-installed on Linux.

If you installed Anaconda, it also has a copy of SQLite without support to readline. Instructors will provide a workaround for it if needed.