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Installing the RSM-MSBA-INTEL computing environment on Windows

Please follow the instructions below to install the rsm-msba-intel computing environment. It has Python, Jupyter Lab, R, Radiant, Rstudio, Postgres, Spark and various required packages pre-installed. The computing environment will be consistent across all students and faculty, easy to update, and also easy to remove if desired (i.e., there will not be dozens of pieces of software littered all over your computer).

Step 1: Upgrade Windows

Windows users must use Microsoft Windows 11, or Windows 10 Professional, Education, or Enterprise (64-bit). Students should be able to upgrade to Microsoft Windows 10 Education (64-bit) for free through their university. For Rady (UCSD) students, the steps in the upgrade process are shown in the following video: https://youtu.be/p0gcRbatO0w. The link to get Windows Education for students is shown below.

https://onthehub.com/download/free-software/windows-10-education-for-students/

Check if there are any updates available for your system by clicking on the Start icon and typing "Check for Updates". After upgrading to the latest version of Windows, open PowerShell and type winver. If you have windows 11 or the windows 10 version is 2004 or higher, as shown in the screenshot below, continue with Step 2.

Step 2: Install Windows Subsystem for Linux (WSL2)

To activate WSL2, start PowerShell as an administrator and copy-and-paste the code below:

dism.exe /online /enable-feature /featurename:Microsoft-Windows-Subsystem-Linux /all /norestart

Followed by:

dism.exe /online /enable-feature /featurename:VirtualMachinePlatform /all /norestart;

Next, restart your computer and re-open PowerShell to install Ubuntu. You will be asked to provide a username and password after install Ubuntu.

wsl --set-default-version 2
wsl --install -d Ubuntu-22.04

Important: Make sure to enter the same username and password you use to login to your computer. The username should not have any spaces or special characters.

Check your username for Windows and Ubuntu by executing the command below in both (1) a Windows PowerShell and (2) an Ubuntu terminal. The output in both cases should be the same.

whoami

Important: If you see root as the username please review the discussion in step 4 below. You will need to reset your username for WSL2.

Next, restart your computer and re-open PowerShell to check that Ubuntu is set as the default linux distribution:

wsl --list

This should return the below:

PS C:\WINDOWS\system32> wsl --list
Windows Subsystem for Linux Distributions:
Ubuntu-22.04 (Default)
docker-desktop-data
docker-desktop

If Ubuntu is not set as the default linux distribution, update the default setting and double check that it is now correct

wsl --setdefault Ubuntu-22.04
wsl --list

Step 3: Install Windows Tools

Download and install the Microsoft App Installer. After completing the install, open a new PowerShell terminal as a regular user and enter the commands below:

winget install -e Microsoft.VisualStudioCode;
winget install -e Docker.DockerDesktop;

This will install VS Code and Docker Desktop. If you are using Windows 10, you should also install Windows Terminal using the command below. Windows Terminal is available by default on Windows 11. We recommend you pin Windows Terminal and VS Code to the taskbar as you will use these tools regularly.

winget install -e Microsoft.WindowsTerminal;

Next, logout and back into Windows and then start Docker by clicking on the Whale icon that was added to your desktop (see image below).

docker

You will know if Docker is running if you see the icon above in your system tray. If the containers shown in the image are moving up and down, docker hasn't finished starting up yet. Once the docker application is running, click on the docker icon in the system tray and select "Settings".

Start by clicking on General to ensure "Use the WSL 2 based engine" is checked as in the screenshot below.

Next click on Resources > WSL INTEGRATION and ensure integration with Ubuntu is enabled as in the screenshot below

Optional: If you are interested, this linked video gives a brief intro to what Docker is: https://www.youtube.com/watch?v=YFl2mCHdv24

Step 4: Open an Ubuntu terminal to complete RSM-MSBA-INTEL computing environment setup

If you are using Windows Terminal you can click on the down-caret at the top of the window to start an Ubuntu terminal as shown in the screenshot below. Alternatively, you can click on the Windows Start icon and type "ubuntu" to start an Ubuntu terminal. Copy-and-paste the code below into the Ubuntu terminal and provide your password when prompted.

cd ~; sudo -- sh -c 'apt -y update; apt -y upgrade; apt -y install xdg-utils wslu zsh ntpdate python-is-python3; ntpdate pool.ntp.org'

Now Ubuntu should be up to date and ready to accept commands to clone the docker repo with documentation and launch scripts. Again, provide your password if prompted.

git clone https://github.com/radiant-rstats/docker.git ~/git/docker;

After running the commands above you will be able to start the docker container by typing ~/git/docker/launch-rsm-msba-intel.sh -v ~ from an Ubuntu terminal.

Next, determine your Windows username by running the code below from an Ubuntu terminal:

USERNAME=$(powershell.exe '$env:UserName'|tr -d '\r');
echo $USERNAME;

Finally, we will create and launch a script launch-rsm-msba.bat on your Desktop that you can double-click to start the container in the future.

The code below will try to determine if you have a Desktop folder that is Backed-Up to OneDrive.

if [ -d "/mnt/c/Users/$USERNAME/OneDrive/Desktop/" ]; then
  echo "Using Desktop backed up in OneDrive" >&2
  DTOP="/OneDrive/Desktop";
elif [ -d "/mnt/c/Users/$USERNAME/Desktop/" ]; then
  echo "Using Desktop folder in user home directory" >&2
  DTOP="/Desktop";
else
  DTOP="";
fi
if [ -n "$DTOP" ]; then
  echo "wt.exe wsl.exe ~/git/docker/launch-rsm-msba-intel.sh -v ~" > /mnt/c/Users/"$USERNAME$DTOP"/launch-rsm-msba.bat;
  chmod 755 /mnt/c/Users/"$USERNAME$DTOP"/launch-rsm-msba.bat;
  cd ~;
  ln -s /mnt/c/Users/"$USERNAME$DTOP"/ ./Desktop;
  /mnt/c/Users/"$USERNAME$DTOP"/launch-rsm-msba.bat;
else
  echo "Unable to determine location of Desktop folder on your system" >&2
  echo "The .bat file has been added to your home directory in Ubuntunu" >&2
  echo "wt.exe wsl.exe ~/git/docker/launch-rsm-msba-intel.sh -v ~" > /mnt/c/Users/"$USERNAME"/launch-rsm-msba.bat;
  chmod 755 /mnt/c/Users/"$USERNAME"/launch-rsm-msba.bat;
fi
ln -s /mnt/c/Users/"$USERNAME"/Dropbox ./Dropbox;
ln -s /mnt/c/Users/"$USERNAME"/Downloads ./Downloads;
ln -s "/mnt/c/Users/$USERNAME/Google Drive" "./Google Drive";
ln -s /mnt/c/Users/"$USERNAME"/OneDrive ./OneDrive;
ln -s /mnt/c/Users/"$USERNAME" ./win_home;

The created and launched script will finalize the installation of the computing environment. The first time you run this script it will download the latest version of the computing environment which can take some time. Wait for the image to download and follow any prompts. Once the download is complete you should see a menu as in the screen shot below.

Trouble shooting

If you see Base dir.: /root as shown in the image below there was an issue creating a new user at the beginning of Step 4.

From an Ubuntu terminal run the below but replace “your-id” by the id you want to use.

adduser your-id
sudo usermod -aG sudo your-id

Now, from a Powershell terminal run the below where, again, you should replace "your-id" by the appropriate id:

ubuntu2204 config --default-user your-id

Next, re-run the code from Step 4 above, starting with the command:

git clone https://github.com/radiant-rstats/docker.git ~/git/docker;

If you do not have a file called launch-rsm-msba.bat on your Desktop, you can create one by copy-and-pasting the code below in to a text file using notepad. The "pause" line can be removed later if all works well. Open VS Code or notepad, copy-and-paste the code below into the editor, and save the file as launch-rsm-msba.bat. After saving, double-click the file to start the docker container.

wt.exe wsl.exe ~/git/docker/launch-rsm-msba-intel.sh -v ~
pause

Step 5: Check that you can launch JupyterLab and Rstudio

You will know that the installation was successful if you can start JupyterLab and Rstudio. If you press 1 (and Enter) Jupyter Lab should start up in your default web browser. If you are asked for login credentials, the username is "jovyan" and the password is "jupyter". Have your browser remember the username and password so you won't be asked for it again.When you press 2 (and Enter) in the terminal, Rstudio should start up in a new tab in your web browser.

Important: Always use q (and Enter) to shutdown the computing environment

Jupyter:

Rstudio:

To finalize the setup, open a terminal in Jupyter lab, press q and Enter when prompted, and then run the code below in the same terminal:

setup;
exit;

Now open a new terminal in JupyterLab and you should see some icons

Updating the RSM-MSBA-INTEL computing environment on Windows

To update the container use the launch script and press 6 (and Enter). To update the launch script itself, press 7 (and Enter).

If for some reason you are having trouble updating either the container or the launch script open an Ubuntu terminal and copy-and-paste the code below. Note: You may have to right-click to get a copy-and-paste menu for the terminal. These commands will update the docker container, replace the old docker related scripts, and copy the latest version of the launch script to your Desktop.

docker pull vnijs/rsm-msba-intel;
rm -rf ~/git/docker;
git clone https://github.com/radiant-rstats/docker.git ~/git/docker;
~/git/docker/launch-rsm-msba-intel.sh -v ~;

Using VS Code

Microsoft's open-source integrated development environment (IDE), VS Code or Visual Studio Code, was the most popular development environment according to a Stack Overflow developer survey. VS Code is widely used by Google developers and is the default development environment at Facebook.

Run the code below from a PowerShell terminal after installing VS Code to install relevant extensions:

Invoke-WebRequest -Uri https://raw.githubusercontent.com/radiant-rstats/docker/master/vscode/extensions.txt -OutFile extensions.txt; 
cat extensions.txt |% { code --install-extension $_ --force};
del extensions.txt;

To learn more about using VS Code to write python code see the links and comments below. The recommended process to install Python on your system is described in a section below

Note that you can use Shift+Enter to run the current line in a Python Interactive Window:

When writing and editing python code you will have access to tools for auto-completion, etc. Your code will also be auto-formatted every time you save it using the "black" formatter.

VS Code also gives you access to a debugger for your python code. For more information see the link below:

You can even open and run Jupyter Notebooks in VS Code

A major new feature in VS Code is the ability to use AI to help you write code. For more information see the links below:

Connecting to postgresql

The rsm-msba-intel container comes with postgresql installed. Once the container has been started, you can access postgresql in different ways. The easiest is to use pgweb. Start pgweb and enter the code below in the "Scheme" tab:

postgresql://jovyan:[email protected]:8765/rsm-docker

To access postgresql from Jupyter Lab use the code below:

## connect to database
from sqlalchemy import create_engine, inspect
engine = create_engine('postgresql://jovyan:[email protected]:8765/rsm-docker')

## show list of tables
inspector = inspect(engine)
inspector.get_table_names()

For a more extensive example using Python see: https://github.com/radiant-rstats/docker/blob/master/postgres/postgres-connect.ipynb

Trouble shooting

If you see root as the username when you type whoami in an Ubuntu terminal you will need to reset your username for WSL2. Please review step 4 in the install process for more guidance.

If you cannot connect to postgresql it is most likely due to an issue with the docker volume that contains the data. The volume can become corrupted if the container is not properly stopped using q + Enter in the launch menu. To create a clean volume for postgres (1) stop the running container using q + Enter, (2) run the code below in a terminal, and (3) restart the container. If you are still having issues connecting to the postgresql server, please reach out for support through Piazza.

docker volume rm pg_data

Installing Python and R packages locally

To install the latest version of R-packages you need, add the lines of code shown below to ~/.Rprofile or copy-and-paste the lines into the Rstudio console.

if (Sys.info()["sysname"] == "Linux") {
  options(repos = c(
    RSPM = "https://packagemanager.posit.co/cran/__linux__/jammy/latest",
    CRAN = "https://cloud.r-project.org"
  ))
} else {
  options(repos = c(
    CRAN = "https://cloud.r-project.org"
  ))
}

This will be done for you automatically if you run the setup command from a terminal inside the docker container. To install R packages that will persist after restarting the docker container, enter code like the below in Rstudio and follow any prompts. After doing this once, you can use install.packages("some-other-package") in the future.

fs::dir_create(Sys.getenv("R_LIBS_USER"), recurse = TRUE)
install.packages("fortunes", lib = Sys.getenv("R_LIBS_USER"))

To install Python modules that will not persist after restarting the docker container, enter code like the below from the terminal in Jupyter Lab:

pip install pyasn1

After installing a module you will have to restart any running Python kernels to import the module in your code.

Using pip to install python packages

We recommend you use pip to install any additional packages you might need. For example, you can use the command below to install a new version of the pyrsm package that you will use regularly throughout the Rady MSBA program. Note that adding --user is important to ensure the package is still available after you restart the docker container

pip install --user --upgrade pyrsm

Removing locally installed packages

To remove locally installed R packages press 8 (and Enter) in the launch menu and follow the prompts. To remove Python modules installed locally using pip press 9 (and Enter) in the launch menu

Committing changes to the computing environment

By default re-starting the docker computing environment will remove any changes you made. This allows you to experiment freely, without having to worry about "breaking" things. However, there are times when you might want to keep changes.

As shown in the previous section, you can install R and Python packages locally rather than in the container. These packages will still be available after a container restart.

To install binary R packages for Ubuntu Linux you can use the command below. These packages will not be installed locally and would normally not be available after a restart.

sudo apt update;
sudo apt install r-cran-ada;

Similarly, some R-packages have requirements that need to be installed in the container (e.g., the rgdal package). The following two linux packages would need to be installed from a terminal in the container as follows:

sudo apt update;
sudo apt install libgdal-dev libproj-dev;

After completing the step above you can install the rgdal R-package locally using the following from Rstudio:

install.packages("rgdal", lib = Sys.getenv("R_LIBS_USER"))

To save (or commit) these changes so they will be present after a (container) restart type, for example, c myimage (and Enter). This creates a new docker image with your changes and also a new launch script on your Desktop with the name launch-rsm-msba-intel-myimage.sh that you can use to launch your customized environment in the future.

If you want to share your customized version of the container with others (e.g., team members) you can push it is to Docker Hub https://hub.docker.com by following the menu dialog after typing, e.g., c myimage (and Enter). To create an account on Docker Hub go to https://hub.docker.com/signup.

If you want to remove specific images from your computer run the commands below from a (bash) terminal. The first command generates a list of the images you have available.

docker image ls;

Select the IMAGE ID for the image you want to remove, e.g., 42b88eb6adf8, and then run the following command with the correct image id:

docker rmi 42b88eb6adf8;

For additional resources on developing docker images see the links below:

Cleanup

To remove any prior Rstudio sessions and locally installed R-packages, press 8 (+ Enter) in the launch menu. To remove locally installed Python modules press 9 (+ Enter) in the launch menu.

Note: It is also possible initiate the process of removing locally installed packages and settings from within the container. Open a terminal in Jupyter Lab or Rstudio and type clean. Then follow the prompts to indicate what needs to be removed.

You should always stop the rsm-msba-intel docker container using q (and Enter) in the launch menu. If you want a full cleanup and reset of the computational environment on your system, however, execute the following commands from a (bash) terminal to (1) remove prior R(studio) and Python modules, (2) remove all docker images, networks, and (data) volumes, and (3) 'pull' only the docker image you need (e.g., rsm-msba-intel):

rm -rf ~/.rstudio;
rm -rf ~/.rsm-msba;
rm -rf ~/.local/share/jupyter
docker system prune --all --volumes --force;
docker pull vnijs/rsm-msba-intel;

Getting help

Please bookmark this page in your browser for easy access in the future. You can also access the documentation page for your OS by typing h (+ Enter) in the launch menu. Note that the launch script can also be started from the command line (i.e., a bash terminal) and has several important arguments:

  • launch -t 3.0.0 ensures a specific version of the docker container is used. Suppose you used version 3.0.0 for a project. Running the launch script with -t 3.0.0 from the command line will ensure your code still runs, without modification, years after you last touched it!
  • launch -v ~/rsm-msba will treat the ~/rsm-msba directory on the host system (i.e., your macOS computer) as the home directory in the docker container. This can be useful if you want to setup a particular directory that will house multiple projects
  • launch -d ~/project_1 will treat the project_1 directory on the host system (i.e., your Windows computer) as the project home directory in the docker container. This is an additional level of isolation that can help ensure your work is reproducible in the future. This can be particularly useful in combination with the -t option as this will make a copy of the launch script with the appropriate tag or version already set. Simply double-click the script in the project_1 directory and you will be back in the development environment you used when you completed the project
  • launch -s show additional output in the terminal that can be useful to debug any problems
  • launch -h prints the help shown in the screenshot below

Trouble shooting

If there is an error related to the firewall, antivirus, or VPN, try turning them off to check if you can now start up the container. You should not be without a virus checker or firewall however! We recommend using Windows Defender. If you are not sure if Windows Defender is correctly configured, please check with IT.

Alternative "fixes" that have worked, are to restart docker by right-clicking on the "whale" icon in the system tray and/or restart your computer. It is best to quit any running process before you restart your computer (i.e., press q and Enter in the launch menu)

Optional

If you want to make your terminal look nicer and add syntax highlighting, auto-completion, etc. consider following the install instructions linked below:

https://github.com/radiant-rstats/docker/blob/master/install/setup-ohmyzsh.md