Software Carpentry: University of Toronto iSchool

University of Toronto iSchool

Feb 05-06, 2015

8:30 am - 4:00 pm

Instructors: Tom Wright, Thomas Guignard, Greg Wilson

Helpers: Amy Brown, James Iveniuk, Kristina Mitova, Kim Pham, Kathy Chung, Brigitte Mueller

General Information

Software Carpentry's mission is to help students, librarians and researchers get more done in less time and with less pain by teaching them basic 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.

Who: The course is aimed at students who are interested in developing a practical understanding of Data Analytics tools. Registration is open to all. Note that priority will be given to AIS members and students from the iSchool at the University of Toronto.

Volunteering opportunity: Want to help out during a session as a volunteer? Contact AIS (see below).

Where: iSchool Faculty of Information, Robarts Library, St. George Campus, University of Toronto. Get directions with OpenStreetMap or Google Maps.
The iSchool is in the Bissel building, which is essentially the north wing of the Robarts Library building. The event will take place in two different rooms:

Feb 5th - Room 417, Fourth floor of Bissel building (at the Inforum)
Feb 6th - Room 224/225, First floor of Bissel building

Requirements: A basic prior knowledge of the Python programming language is required for day 2 of the workshop. iSchool students who attended INF1340H Introduction to Information Systems, for example, should have the required Python skills to follow the course easily. 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 ais.ischool@utoronto.ca for more information.

Schedule

Day 1

09:00	Automating tasks with the Unix shell
10:30	Coffee
12:00	Lunch break
13:00	Programming with R
14:30	Coffee
16:00	Wrap-up

Day 2

09:00	Regular Expressions
10:30	Coffee
12:00	Lunch break
13:00	Data Syndication
14:30	Coffee
16:00	Wrap-up

Etherpad:
During the workshop, attendees took notes and shared URLs using an Etherpad.
A saved version of the Etherpad (slightly edited for readibility) is now available here.
If you'd rather use the original editable version: https://etherpad.mozilla.org/2015-02-05-toronto.

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 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...

Regular Expressions

Introduction: what are Regular Expressions and how do they work?
Operators and patterns: parsing, finding and extracting data
Writing a function in R using Regular Expressions

Data Syndication (using Python)

Finding, loading and parsing data
Analyzing data
Creating reusable functions to analyze data
Creating data sets
Publishing data
Open Data: How to write HTML to make your data harvestable and promote re-use

Setup

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 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.

Mac OS X

We recommend Text Wrangler or Sublime Text. In a pinch, you can use nano, which should be pre-installed.

Linux

Kate is one option for Linux users. In a pinch, you can use nano, which should be pre-installed.

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 download and running the installer. This will provide you with both Git and Bash in the Git Bash program.

Software Carpentry Installer

This installer requires an active internet connection.

After installing Python and Git Bash:

Download the installer.
If the file opens directly in the browser select File→Save Page As to download it to your computer.
Double click on the file to run it.

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.

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.

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.

Please make sure you install Python version 2.x - Python 3 introduced a lot of changes that will break some of the code we will be teaching.

Windows

Download and install Anaconda.
Use all of the defaults for installation except make sure to check Make Anaconda the default Python.

Mac OS X

Download and install Anaconda.
Use all of the defaults for installation except make sure to check Make Anaconda the default Python.

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 boot camp.)

Download the installer that matches your operating system and save it in your home folder.
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).