Creating your own container images

There are lots of reasons why you might want to create your own Docker image.

  • You can’t find a container with all the tools you need on Docker Hub.

  • You want to have a container to “archive” all the specific software versions you ran for a project

  • You want to share your workflow with someone else.

Interactive installation

Before creating a reproducible installation, let’s experiment with installing software inside a container. Start the alpine container from before, interactively:

docker run -it alpine sh

Because this is a basic container, there’s a lot of things not installed – for example, python3.

/# python3

Output

sh: python3: not found

Inside the container, we can run commands to install Python 3. The Alpine version of Linux has a installation tool called apk that we can use to install Python 3.

/# apk add --update python3 py3-pip python3-dev

We can test our installation by running a Python command:

/# python3 --version

Once Python is installed, we can add Python packages using the pip package installer:

/# pip install cython

Exercise: Searching for Help

Can you find instructions for installing R on Alpine Linux? Do they work?

Once we exit, these changes are not saved to a new container by default. There is a command that will “snapshot” our changes, but building containers this way is not very reproducible. Instead, we’re going to take what we’ve learned from this interactive installation and create our container from a reproducible recipe, known as a Dockerfile.

If you haven’t already, exit out of the interactively running container.

/# exit

Put installation instructions in a Dockerfile

A Dockerfile is a plain text file with keywords and commands that can be used to create a new container image.

Every Dockerfile is composed of three main parts as shown below.

FROM <EXISTING IMAGE>
RUN <INSTALL CMDS FROM SHELL>
RUN <INSTALL CMDS FROM SHELL>
CMD <CMD TO RUN BY DEFAULT>

Let’s break this file down:

  • The first line, FROM, indicates which container we’re starting with.

  • The next two lines RUN, will indicate installation commands we want to run. These are the same commands that we used interactively above.

  • The last line, CMD indicates the default command we want the container to run, if no other command is provided.

Take a Guess

Do you have any ideas about what we should use to fill in the sample Dockerfile to replicate the installation we did above?

The recipe provided by this Dockerfile will use Alpine Linux as the base container, add Python and the Cython library, and set a default print command.

Create a new Docker image

So far, we just have a file. We want Docker to take this file, run the install commands inside, and then save the resulting container as a new container image. To do this we will use the docker build command.

We have to provide docker build with two pieces of information:

  • the location of the Dockerfile

  • the name of the new image. Remember the naming scheme from before? You should name your new image with your Docker Hub username and a name for the container, like this: USERNAME/CONTAINERNAME

All together, the build command will look like this:

docker build -t USERNAME/CONTAINERNAME .

The -t option names the container; the final dot indicates that the Dockerfile is in our current directory.

For example, if my user name was alice and I wanted to call my image alpine-python, I would use this command:

docker build -t alice/alpine-python .

Review!

  1. Think back to earlier. What command can you run to check if your image was created successfully? (Hint: what command shows the images on your computer?)

  2. We didn’t specify a tag for our image name. What did Docker automatically use?

  3. What command will run the container you’ve created? What should happen by default if you run the container? Can you make it do something different, like print “hello world”?

While it may not look like you have achieved much, you have already effected the combination of a lightweight Linux operating system with your specification to run a given command that can operate reliably on macOS, Microsoft Windows, Linux and on the cloud!

Boring but important notes about installation

There are a lot of choices when it comes to installing software - sometimes too many! Here are some things to consider when creating your own container:

  • Start smart, or, don’t install everything from scratch! If you’re using Python as your main tool, start with a Python container. We’ve used Alpine Linux as an example in this lesson, but it’s generally not a good container to start with because it is a less common version of Linux; using Ubuntu, Debian and CentOS are all good options for scientific software installations. The program you’re using might recommend a particular version of Linux; if this happens, start with that particular Linux container.

  • How big? How much software do you really need to install? When you have a choice, lean towards using smaller starting images and installing only what’s needed for your software, as a bigger image means longer download times to use.

  • Know (or Google) your Linux. Each version of Linux has a special set of tools specifically for installing software. The apk command we used above is the installer for Alpine Linux. The installers for various common Linux versions are listed below:

    • Ubuntu: apt or apt-get

    • Debian: deb

    • CentOS: yum

    Most common software installations are available to be installed via these tools. Searching for “install X on Y Linux” is always a good start for common software installations; if something isn’t available via the Linux distribution’s installation tools, try the options below.

  • Use what you know. You’ve probably used commands like pip or install.packages() before on your own computer – these will also work to install things in containers (if the basic scripting language is installed).

  • README. Many scientific software tools have a README or installation instructions that lay out how to install software. You want to look for instructions for Linux. If the install instructions include options like those suggested above, try those first.

In general, a good strategy for installing software is:

  • Make a list of what you want to install.

  • Look for pre-existing containers.

  • Read through instructions for software you’ll need to install.

  • Try installing everything interactively in your base container - take notes!

  • From your interactive installation, create a Dockerfile and then try to build the container again from that.

Share your new container on Docker Hub

Images that you release publicly can be stored on the Docker Hub for free. If you name your image as described above, with your Docker Hub username, all you need to do is run the opposite of docker pulldocker push.

docker push alice/alpine-python

Make sure to substitute the full name of your container!

In a web browser, open <https://hub.docker.com>, and on your user page you should now see your container listed, for anyone to use or build on.

Logging In

Technically, you have to be logged into Docker on your computer for this to work. Usually it happens by default, but if docker push doesn’t work for you, run docker login first, enter your Docker Hub username and password, and then try docker push again.

What’s in a name? (again)

You don’t have to name your containers using the USERNAME/CONTAINER:TAG naming scheme. On your own computer, you can call containers whatever you want and refer to them by the names you choose. It’s only when you want to share a container that it needs the correct naming format.

You can rename images using the docker tag command. For example, imagine someone named Alice has been working on a workflow container and called it workflow-test on her own computer. She now wants to share it in her alice Docker Hub account with the name workflow-complete and a tag of v1. Her docker tag command would look like this:

docker tag workflow-test alice/workflow-complete:v1

She could then push the re-named container to Docker Hub, using docker push alice/workflow-complete:v1