On Your Own Machine

This guide will help you get started setting up an environment on your personal computer for completing the labs and MPs. We will only support working locally with Docker, but we may list other options for students who can support themselves.

The slides that are being used by staff in lab can be found here

For those who are unfamiliar with these terms, here is a short explanation of what each method means and the pros and cons of each.

• Working locally with Docker: you download a disk image and software required to create a standardized coding environment. You will still be able to access and use the files stored on your own machine.
  • Pros: Supported by CS 225 Staff. You don’t need to worry about installing any development tools (e.g. valgrind, gdb) on your operating system. You also will not need to worry about your code behaving differently when we grade it.
  • Cons: You will have to download and install some commercial software.
• Working natively: you download code and tools onto your own machine before working. You run commands on your own machine’s environment during development.
  • Pros: Code running natively will have fewer overheads, and have full access to your system’s resources. The process of setting up text editor and working environment prepares your machine for future coding projects.
  • Cons: Since your machine is very likely different from our testing environment, you will need to test your code separately to ensure you get the same results as our grading runs.

Using Git

We will be using git to provide starter code in this class. You are not required to use it yourself but if you wish we have the following instructions to create a private repo for this course.

Setup Your Git Repository

Working with Docker

1) Installing Docker

Docker is a lightweight container engine used to emulate OS-level virtual environments. For this class, it will serve as an all-in-one tool for your development environment.

• Docker Desktop (Recommended for Windows/Mac/Linux)

You can install Docker using Docker Desktop. Be sure to run Docker Desktop once installed, as it has some ‘first-time setup’ in order to actually install Docker on your system.

Warning: There is a separate installer between Intel and M1 Macs!

Note: Docker Desktop is commercial software, and while it is possible to use Docker without it, we will not provide support if you choose to use an alternative.

2) Installing VS Code

If you have not already installed VS Code, you are encouraged to download the software at the following link: VS Code

Once it is installed, install the Dev Containers extension by either searching in the Extensions tab or using the following link: Dev Containers

You can access the Extensions tab by clicking on the ‘Extensions’ icon in the navigation bar. While you are free to add other extensions based on your own preferences, make sure you have Dev Containers installed before continuing.

3) Adding the course Dockerfile

The Dockerfile is used to describe a standard environment for software to run in. The Docker software will use this file to create a container with the described environment. For this course, our Dockerfile will provide you with an Ubuntu-based environment that has the necessary software and debugging tools for C++ preinstalled.

Create a new directory for your CS225 course work (e.g. ‘cs225’, though it can be named anything).

Inside the directory, create a new file named Dockerfile (with no file extensions), and copy the contents below into the file. Make sure to save!

FROM gcevans/cs225-container:fa23
ENTRYPOINT bash

Note: If you did the Git Repository setup before this, you can create the Dockerfile in the folder you cloned. Alternatively, you can create a new directory, and drag your cloned folder into that directory. In that case, your new folder will contain the Dockerfile as well as the folder you cloned from setting up the Git Repository.

Tip: Docker containers runs code on your computer. As with installing any other software, it is a good idea to make sure that it comes from a trusted source. Although it is not required for this course, the underlying Dockerfile for this environment will always be publicly available for you to review in this repository.

4) Building your environment

Using the Dev Containers extension on VSCode, run the command Open Folder in Container. You can do this by either clicking on the bottom left-hand corner widget (the green X-shaped button) or by pressing F1 (or Ctrl+Shift+P) and typing in the command.

Note: The command may not show up immediately after clicking on the widget. You can search the command name to bring it up in the resulting dialog box, or when you activate the command palette by pressing F1 (or Ctrl+Shift+P).

Open the folder you created previously, and make sure you select the ‘From ‘Dockerfile’ option in the popup.

Note: If this option does not appear, make sure that you selected the directory containing the Dockerfile, and that the Dockerfile is saved.

VS Code may ask if you want to install any additional features. Click OK without selecting any additional features do not install any extra features.

The initial process can take some time as your computer downloads the required files and builds your environment. With a good computer and internet connection, this should not take longer than 5-10 minutes.

If done correctly, you should see a .devcontainer folder in your directory. You should now be able to edit your local files inside VS Code and use the VS Code terminal to run them in your new environment.

The environment should automatically close when you close the folder within VS Code, or when you quit VS Code. You can then always reopen it by running the Dev Containers: Open Folder in Container command again.

VM Setup FAQ

Working with WSL (unsupported, Windows-only)

If you are unable to use the Docker-based environment for this class, an alternative, but unsupported WSL image can be used instead. Only use this if Docker does not work.

WSL Guide: