University of Washington

HUB 145, 4001 Stevens Way NE and OUG 220, 4060 George Washington Ln NE, Seattle
Mar 17-18, 2014
9:00 am - 4:30 pm

Instructors: Bernhard Konrad, Jenny Bryan, Tommy Guy, Christina Koch, Lynne Williams, Trevor King

What: Our goal is to help scientists and engineers become more productive by teaching them basic computing skills like program design, version control, testing, and task automation. In this two-day bootcamp, short tutorials will alternate with hands-on practical exercises. Participants will be encouraged both to help one another, and to apply what they have learned to their own research problems during and between sessions. Attendants are offered online office hours: regular events to get one-on-one help from Software Carpentry instructors, online.

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.

Requirements: Participants must bring a laptop with a few specific software packages installed. (The list will be sent to participants a week before the bootcamp.)

Content: The syllabus for this bootcamp will include:

Contact: Please mail admin@software-carpentry.org for more information.


Syllabi

https://github.com/LJWilliams/2014-03-17-uw/graphs

Python

OUG 220
4060 George Washington Ln NE
Python syllabus

R

HUB 145
4001 Stevens Way NE
R syllabus

Schedule

Schedule is subject to change

March 17

Time Python R
8:30 - 9:00 Setup help Setup help
9:00 - 9:15 Overview and introduction Overview and introduction
9:15 - 10:45 Navigating in the shell R basics
10:45 - 11:00 Break Break
11:00 - 12:15 Shell scripts and automation Care and feeding of R objects
12:15 - 1:15 Lunch Lunch
1:15 - 2:45 Version Control Version Control
2:45 - 3:00 Break Break
3:00 - 4:30 Version Control (remote) Data Visualization

March 18

Time Python R
8:30 - 9:00 Setup help Setup help
9:00 - 10:30 Numpy, variables, slicing File organization and debugging
10:30 - 10:45 Break Break
10:45 - 12:15 Python flow control; Python functions The shell and remote version control
12:15 - 1:15 Lunch Lunch
1:15 - 2:30 Testing and command line arguments Data aggregation with R
2:30 - 2:45 Break Break
2:45 - 4:25 Intro to Databases Automation and pipelines
4:25 - 4:30 Wrap-up Wrap-up

Setup

For the Python class, please install the Bash shell, a text editor, Git, Python, and SQLite.

For the R class, please install the Bash shell, Git, R, and RStudio.

The Bash Shell

Bash is a commonly-used shell. Using a shell gives you more power to do more tasks more quickly with your computer.

Linux / Bash

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.

Mac OS X / Bash

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.

Windows / Git Bash

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

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.

Linux / Editor

Kate is one option for Linux users.

Mac OS X / Editor

We recommend Text Wrangler or Sublime Text.

Windows / Editor

Notepad++ is a popular free code editor for Windows.

Git

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.

Linux / Git

If Git is not already available on your machine you can try to install it via your distro's package manager (e.g. apt-get).

Mac OS X / Git

Installing Git may require you to first install XCode. This is a very large download (several gigabytes), so please do it before arriving at the bootcamp.

For Mac OS X 10.7 and 10.8:

Go to the Xcode website. Get XCode from the App Store making certain to install the command line tools (from the Download preferences pane). Git is included in the command line tools.

For Mac OS X 10.6

If you have Mac OS X 10.6, first get XCode by going to the Apple developer site. You have to sign in with an Apple ID linked to a Developer account. If you don't have one, you can register and create one. Once you log in, go to page 8 and find "XCode 3.2.6 and iOS SDK 4.3 for Snow Leopard". Click to open that section, and then download the .dmg file. Finally, install just git.

Windows / Git Bash

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

R and RStudio

Please follow these install instructions for R and RStudio.

Python

Python is becoming more and more popular in scientific computing, and it's a great language for teaching general programming concepts due to its easy-to-read syntax. We will be using Python version 2.7. Installing all the scientific packages for Python individually can be a bit difficult, so we recommend using an all-in-one installer.

Linux / Python

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.)

  1. Download the installer that matches your operating system and save it in your home folder.
  2. Open a terminal window..
  3. Type
    bash Anaconda-
    and then press tab. The name of the file you just downloaded should appear.
  4. 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).

Mac OS X / Python

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.)

  1. Download the installer that matches your operating system and save it in your home folder.
  2. Open a terminal window.
  3. Type
    bash Anaconda-
    and then press tab. The name of the file you just downloaded should appear.
  4. 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).

Windows / Python

For Windows we recommend the Enthought Canopy distribution since it seems to work well with Git Bash.

For other options check the Python4Astronomers page on installing scientific Python.

SQLite

SQLite is a software library that implements a self-contained, serverless, zero-configuration, transactional SQL database engine.

Linux / SQLite

Mac OS X / SQLite

  • Download sqlite-shell-osx-x86-SOMENUMBERS.zip from the SQLite download page.
  • Unzip the file.
  • Move SQLite3 to your Applications folder.

Windows / SQLite

  • Download sqlite-shell-win32-x86-SOMENUMBERS.zip from the SQLite download page.
  • Unzip the file.
  • Copy sqlite.exe into C:\Windows.

Topics

The Unix Shell

  • What and Why
  • Files and Directories
  • Creating Things
  • Pipes and Filters
  • Loops
  • Shell Scripts
  • Finding Things

Python

  • Values and Types
  • Indexing, Slicing, and Update Operators
  • Variables and Assignment
  • Repeating Things
  • Libraries, Grids, and Colors
  • Making Choices
  • Building Bigger Programs

Databases

  • Selecting
  • Removing Duplicates
  • Filtering
  • Calculating New Values
  • Ordering Results
  • Missing Data
  • Aggregation
  • Grouping
  • Combining Data
  • Creating and Modifying Tables
  • Transactions
  • Programming with Databases

Reference Guides