How to leverage a private modules in your YAML Pipelines

I’ve made no secret about my love of DevOps, and to be honest, over the past few months it’s been more apparent to me than ever before that these practices are what makes developers more productive. And taking the time to setup these processes correctly are extremely valuable and will pay significant dividends over the life of the project.

Now that being said, I’ve also been doing a lot of work with Python, and honestly I’m really enjoying it. It’s one of those languages that is fairly easy to pickup but the options and opportunities based on it’s flexibility take longer to master. But one of the things I’m thankful we started doing was leveraging python modules to empower our code re-use.

The ability to leverage pip to install modules into containers creates this amazing ability to separate the business logic from the compute implementation.

To that end, there’s a pretty common problem, that I’m surprised is not more documented. And that’s if you’ve built python modules, and deployed them to a private artifact feed, how can you pull those same modules into a docker container to be used.

Step 1 – Create a Personal Access Token

The first part of this is creating a personal access token in ADO, which you can find instructions for here. The key to this though is the PAT must have access to the packages section, and I recommend read access.

Step 2 – Update DockerFile to accept an argument

Next we need to update our Dockerfile to be able to accept an argument so that we can pass that url. You’ll need to build out the url your going to use by doing the following:

https://{PAT}@pkgs.dev.azure.com/{organization}/{project id}/_packaging/{feed name}/pypi/simple/

Step 3 – Update YAML file to pass argument

This is done by adding the following to your docker file:

ARG feed_url=""
RUN pip install --upgrade pip
RUN pip install -r requirements.txt --index-url="${feed_url}"

The above will provide the ability to pass the url required for accessing the private feed into the process of building a docker image. This can be done in the YAML file by using the following:

- task: Bash@3
  inputs:
    targetType: 'inline'
    script: 'docker build -t="$(container_registry_name)/$(image_name):latest" -f="./DockerFile" . --build-arg feed_url="$(feed_url)"'
    workingDirectory: '$(Agent.BuildDirectory)'
  displayName: "Build Docker Image"

At this point, you can create your requirements file with all the appropriate packages and it will build when you run your automated build for your container image.