In this course, we'll be using a variety of different software programs to write, manage, and execute the code that we write. Unfortunately, one of the most frustrating and confusing barriers to working with code is simply getting your machine properly set up. This repository aims to provide sufficient information for setting up your machine, and troubleshooting the process. Do your best to follow instructions and search for help online, but don't waste too much time (e.g., more than 15 minutes) before contacting your professor or TA.

Note, classroom machines for this course should have all appropriate software already installed and ready to use.

Contents

• Resources
• Summary
• Git
  • GitHub
• Command-line Tools (Bash)
  • Mac
  • Windows
• Python
  • Anaconda
• Text Editors
  • Visual Studio Code
  • Atom
  • SublimeText
  • PyCharm

The resources for this module are links to recommended software, collected here for easy access.

• git (and Git Bash)
  • GitHub (sign up)
  • optional: Bash on Windows
• Python (Anaconda)
• Visual Studio Code

In short, you'll need to install the following programs: see below for more information / options.

• Git: A set of tools for tracking changes to code (especially when collaborating with others). This program is already installed on Macs.

  • GitHub: A web service for hosting code online. You don't actually need to install anything GitHub (it uses git), but you'll need to sign up for the service.

• Bash: A command-line interface for controlling your computer. git is a command-line program so you'll need a command shell to use it. Macs already have a Bash program called Terminal. On Windows, installing git will also install a Bash shell called Git Bash, or you can try the (experimental) Linux subsystem for Windows 10.

• Python: a general purpose programming language, but one that is often used when working with data. This will be our primary language for the quarter (though we will explore some others as well). "Installing Python" actually means installing tools that will let your computer understand and run Python code.

  • Anaconda: is a distribution of the Python language, which includes a large number of additional add-on packages that we will be using (and can be difficult to install on their own). This is the recommended way of installing Python; we will be assuming that you have installed all of tools provided with the distribution.

• Visual Studio Code: A lightweight text editor that supports programming in lots of different languages.

  • You are welcome to use another text editor if you wish; some further suggestions are included.

The following sections have additional information about the purpose of each component, how to install it, and alternative configurations.

If you run into any installation/configuration challenges, please let us know on course Slack Channel so that others can anticipate the same issues.

git is a version control system that provides a set of commands that allow you to manage changes to written code, particularly when collaborating with other programmers (much more on this in module 4). For now, you'll need to download and install the software. Note, if you are using a Windows machine, this will also install a program called Git Bash, which provides a text-based interface for executing commands on your computer. For alternative/additional Windows command-line tools, see below.

GitHub is a website that is used to store copies of code that are being managed with git (think "Imgur for code"). These learning modules are on GitHub (check out the URL!). You will also be using GitHub to turn in your programming assignments.

In order to use GitHub, you'll need to create a free GitHub account, if you don't already have one. You should register a username that is identifiable as you (e.g., based on your name or your UW NetID). This will make it easier for us to collaborate and for the teaching staff to figure out who submitted what, rather than needing to figure out who 'LeetDesigner2099' is. This can be the start of a professional account you may use for the rest of your career!

The command-line provides a text-based interface for giving instructions to your computer (much more on this in module 2). In this course, we'll use the command-line for navigating our computer's file structure, running programs, and executing commands that allow us to keep track of changes to the code we write (i.e., version control with git).

In order to use the command-line, you will need to use a command shell (a.k.a. a command prompt). This is a program that provides the interface to type commands into. In particular, we'll be working with the Bash shell, which provides a particular set of commands common to Mac and Linux machines.

On a Mac you'll want to use the built-in app called Terminal. You can open it by searching via Spotlight (hit Cmd (⌘) and Spacebar together, type in "terminal", then select the app to open it), or by finding it in the Applications/Utilities folder.

On Windows, we recommend using Git Bash, which you should have installed along with git (above). Open this program to open the command-shell. This works great, since we'll often be using the command-line for performing version control.

• Note that Windows does come with its own command-prompt, called the DOS Prompt, but it has a different set of commands and features. Powershell is a more powerful version of the DOS prompt if you really want to get into the Windows Management Framework. But Bash is more common for the kinds of computer programming that we'll be doing, and so we will be focusing on that set of commands.

Alternatively, the 64-bit Windows 10 Anniversary update (August 2016) does include a beta version of an integrated Bash shell. You can access this by enabling the subsystem for Linux and then running bash in the command prompt. This is currently (Dec 2016) "beta" technology, but will suffice for our purposes if you can get it running.

The primary programming language we will use throughout the course is Python. It's a very powerful, general-purpose programming language that is "friendly" enough that it is often used for information and data sciences. However, in order to have the computer run your programs, you will need to install the interpreter that the computer uses.

Important note: There are two different versions of Python that exist in the world: Python 2 (latest: 2.7) and Python 3 (latest: 3.6). While mostly similar, the newer Python 3 version added a few basic differences that make it incompatable with Python 2. But a lot of existing programs were slow to change over to Python 3, effectively causing two different versions to exist in active use (kind of like people not switching from Windows XP). Python 3 is considered the "current" version, with Python 2 being "legacy".

In this course we will be working with Python 3. Thus you will want to make sure that you install Python 3, and that documentation and examples you reference is for Python 3 (rather than Python 2)!

There are a number of ways to get Python installed on your machine: in fact, you may have a version (probably Python 2) installed on your computer already! However, the recommended approach for programming for data science is to install the Anaconda. Anaconda is a pre-packaged bundle of common Python tools and packages that are commonly used in data science—many of which we will be utilizing (including Jupytr for running interactive "notebooks", and pandas for large-scale data work). And the best part: Anaconda makes it easy to get all the pieces installed and ready to use!

To install Anaconda (and Python along with it), simply download the Python 3.6 installer, run the executable, and follow the instructions. This should install Python and all the required packages.

• You can confirm that everything is set up correctly by opening the Command Shell you installed above and typing python --version. You should see text that looks something like:

  Python 3.6.0 :: Anaconda 4.3.1 (x86_64)
  

  confirming that Python is installed and available.

In order to write code, you need somewhere to write it (we don't want to write it in MS Word!). There are a variety of available programs that provide an interface for editing code. A major advantage of these programs is that they provide automatic formatting/coloring for easier interpretation of the code, along with cool features like auto-completion and integration with version control.

There are lots of different text editors out there, all of which have slightly different appearances and features. You only need to download and use one of the following programs (we recommend Visual Studio Code as a default), but feel free to try out different ones to find something you like (and then evangelize about it to your friends!)

Visual Studio Code (or VS Code; not to be confused with Visual Studio) is an open-source editor developed by Microsoft. While it focuses on web programming and JavaScript, it readily supports lots of languages including Python, and provides a number of community-built extensions for adding even more features. Although fairly new, it is updated regularly and has has become one of my main editors for programming.

Click the "Download" button to download the installer (e.g, .exe) file, then double-click on that to install the application.

Once you've installed VS Code, the trick to using it effectively is to get comfortable with the Command Palette. If you hit Cmd+Shift+P, VS Code will open a small window where you can search for whatever you want the editor to do. For example, if you type in markdown you can get list of commands related to Markdown files (including the ability to open up a preview).

• While VS Code can handle Python code just fine out of the box, to be most effective when writing code you'll want to add an extension with additional Python support. We recommend Don Jayamanne's extension: you can easily install this by using the command-palette (open it up and type "extension" to find the "Install Extensions" option). Note that you can disable the pervasive "style warnings" by adding # pylint: skip-file to the top of a script file.

For more information about using VS Code, see the documentation, which includes videos if you find them useful.

Atom is a text editor built by the folks at GitHub and has been gaining in popularity. It is very similar to VS Code in terms of features, but has a somewhat different interface and community. It has a similar command-palette to VS Code, and is arguably even nicer about editing Markdown specifically (its built-in spell-check is a great feature, especially for documents that require lots of written text). The document you are reading was authored in Atom.

SublimeText is a very popular text editor with excellent defaults and a variety of available extensions (though you'll need to manage and install extensions to achieve the functionality offered by other editors out of the box). While the software can be used for free, every 20 or so saves it will prompt you to purchase the full version. This is my application of choice for when I just write to write a plain text file.

PyCharm is a full-featured Python IDE (integrated development environment) developed by JetBrains. It has more features than you can shake a stick at, including a large number of features that won't be relevant for us. It is more powerful, but also somewhat "heavier" (read: slower). You would be interested in the Community Edition of the software.