Software Carpentry: Texas Tech University

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: Room 237-238, Science Bldg, Lubbock, TX 79409. 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 jfonner@tacc.utexas.edu for more information.

Schedule

Day 1

08:30	Troubleshoot your installation (optional)
09:00	Welcome and logistics
09:05	Beginner: Automating tasks with the Unix shell Advanced: Pythonic Data Analysis
10:30	Coffee
12:00	Lunch break
13:00	Version control with Git
14:30	Coffee
16:00	Wrap-up

Day 2

09:00	Beginner: Building programs with Python Advanced: Structured binary data files and metadata
10:30	Coffee
12:00	Lunch break
13:00	Data analysis with Pandas
14:30	Coffee
16:00	Wrap-up

Beginner: You recognize that scientists increasingly use lots of custom computer programs in order to do their data analysis, and you'd like to learn the foundational tools that permit scientists to automate work by following some common patterns. You might have even used some of these tools before, but would like a careful introduction to the rationale for the use of these tools in solving common computation challenges.

Advanced: You are already routinely use the Unix shell and write basic analysis scripts in Python, R, MATLAB, etc. While most of your data analysis already is using the tools in this workshop, and you know most of the basic data structures in your language, progress feels slow at times, and you suspect you might be able to automate and simplify complex tasks by learning some new patterns for solving common computational challenges.

Etherpad: https://etherpad.mozilla.org/2015-08-20-TTU.
We will use this Etherpad for chatting, taking notes, and sharing URLs and bits of code.

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...

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...

Data analysis with Pandas

Starting With Data
Index Slice Subset
Data Types and Format
Merging Data
Data Analysis Automation: Loops and Functions
Plotting with Matplotlib
Putting It All Together
Accessing SQL using Python
Source...

Advanced: Pythonic Data Analysis

Containers and iteration
Dictionaries
First class functions
Multipanel plotting
Filepath manipulation
Automation challenge
Source...

Advanced: Structured binary data files and metadata

Data management
Data processing
Data provenance
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.