Install & Set Up Docker For Use With eddy4R

This tutorial provides the basics on how to set up Docker on one's local computer and then connect to an eddy4R Docker container in order to use the eddy4R R package. There are no specific skills needed for this tutorial, however, you will need to know how to access the command line tool for your operating system (basic instructions given).

In the tutorial below, we give the very barest of information to get Docker set up for use with the NEON R package eddy4R. For more information on using Docker, consider reading through the content from CyVerse's Container Camp's Intro to Docker.

Install Docker

To work with the eddy4R–Docker image, you first need to sign up for an account at DockerHub.

Once logged in, getting Docker up and running on your favorite operating system (Mac/Windows/Linux) is very easy. The "getting started" guide on Docker has detailed instructions for setting up Docker. Unless you plan on being a very active user and devoloper in Docker, we recommend starting with the stable channel (not edge channel) as you may encounter fewer problems.

• Mac
• Windows
• Linux

If you're using Docker for Windows make sure you have shared your drive.

If you're using an older version of Windows or MacOS, you may need to use Docker Machine instead.

Test Docker installation

Once you are done installing Docker, test your Docker installation by running the following command to make sure you are using version 1.13 or higher.

You will need an open shell window (Linux; Mac=Terminal) or the Docker Quickstart Terminal (Windows).

docker --version
	

When run, you will see which version of Docker you are currently running.

Note: If you run just the word docker you should see a whole bunch of lines showing the different options available with docker. Alternatively you can test your installation by running the following:

docker run hello-world

Notice that the first line states that the image can't be found locally. The next few lines are pulling the image, so if you were to run the hello-world prompt again, it would already be local and you'd see the message start at "Hello from Docker!".

If these steps work, you are ready to go on to access the eddy4R-Docker image that houses the suite of eddy4R R packages. If these steps have not worked, follow the installation instructions a second time.

Accessing eddy4R

Download of the eddy4R–Docker image and subsequent creation of a local container can be performed by two simple commands in an open shell (Linux; Mac = Terminal) or the Docker Quickstart Terminal (Windows).

The first command docker login will prompt you for your DockerHub ID and password.

The second command docker run -d -p 8787:8787 -e PASSWORD=YOURPASSWORD stefanmet/eddy4r:1.0.0 will download the latest eddy4R–Docker image and start a Docker container that utilizes port 8787 for establishing a graphical interface via web browser.

• docker run: docker will preform some process on an isolated container
• -d: the container will start in a detached mode, which means the container run in the background and will print the container ID
• -p: publish a container to a specified port (which follows)
• 8787:8787: specify which port you want to use. The default 8787:8787 is great if you are running locally. The first 4 digits are the port on your machine, the last 4 digits are the port communicating with RStudio on Docker. You can change the first 4 digits if you want to use a different port on your machine, or if you are running many containers or are on a shared network, but the last 4 digits need to be 8787.
• -e PASSWORD=YOURPASSWORD: define a password environmental variable to use upon login to the Rstudio instance. YOURPASSWORD can be anything you want.
• stefanmet/eddy4r:1.0.0: finally, which container do you want to run.

Now try it.

docker login 

docker run -d -p 8787:8787 -e PASSWORD=YOURPASSWORD stefanmet/eddy4r:1.0.0

This last command will run a specified release version (eddy4r:1.0.0) of the Docker image. Alternatively you can use eddy4r:latest to get the most up-to-date development image of eddy4r.

If you are using data stored on your local machine, rather than cloud hosting, a physical file system location on the host computer (local/dir) can be mounted to a file system location inside the Docker container (docker/dir). This is achieved with the Docker run option -v local/dir:docker/dir.

Access RStudio session

Now you can access the interactive RStudio session for using eddy4r by using any web browser and going to http://host-ip-address:8787 where host-ip-address is the internal IP address of the Docker host. For example, if your host IP address is 10.100.90.169 then you should type http://10.100.90.169:8787 into your browser.

To determine the IP address of your Docker host, follow the instructions below for your operating system.

Windows

Depending on the version of Docker, older Docker Toolbox versus the newer Docker Desktop for Windows, there are different way to get the docker machine IP address:

• Docker Toolbox - Type docker-machine ip default into cmd.exe window. The output will be your local IP address for the docker machine.
• Docker Desktop for Windows - Type ipconfig into cmd.exe window. The output will include either DockerNAT IPv4 address or vEthernet IPv4 address that docker uses to communicate to the internet, which in most cases will be 10.0.75.1.

Mac

Type ifconfig | grep "inet " | grep -v 127.0.0.1 into your Terminal window. The output will be one or more local IP addresses for the docker machine. Use the numbers after the first inet output.

Linux

Type localhost in a shell session and the local IP will be the output.

Once in the web browser you can log into this instance of the RStudio session with the username as rstudio and password as defined by YOURPASSWORD. Once complete you are now in a RStudio user interface with eddy4R installed and ready to use.

Additional information about the use of RStudio and eddy4R packages in Docker containers can be found on the rocker-org/rocker website and the eddy4RWiki pages.

Using eddy4R

To learn to use the eddy4R package to calculate fluxes, please visit the eddy4R vignette (link pending).