A while back I started using, and looking deeply into drone.io as a continuous integration system. The basic tldr; of drone.io is a build system that uses docker instances to build your code. At work we are running a server with drone.io running on it that performs builds of our go code.
Anyhow, very early on we felt that drone could be enhanced, by
allowing the repositories to specify volume mounts from the drone build system
file system into our drone build container. This allows us to do wacky stuff
like volume mount the docker socket to the running build container and use
the host’s docker daemon to perform
docker build commands from within the
build container without having to run docker within a docker container.
This proved so useful that drone adopted this idea into their product.
… Segue to Testing
As I have mentioned before we write numerous behavior tests. These tests work great for our QA department, and ease the communication gap between developers and QA and Product. I really like this style of testing due to the clearer communication. So a little while back we had merely a repository per micro-service of python based behavior tests, which were run when someone felt the need to run them. Not very Continuous.
We decided that pushes to these testing repos should be treated just like our code, and we should build testing artifacts which could be run within our automated pipeline. As these testing repos are not golang, we had to figure out how to build and install dependencies in our drone scheme, not to mention figure out how to pull requirements from private repositories with drone.
Building our Python Code
Lets start with a drone build script:
With a Dockerfile that looks like this:
The above is pretty simple for base use cases, where you just want to create a
docker container that has python, and pip install this repositories repos. But
what if your
requirements.txt contains a private repo location such as
Well, drone.io volume mount and python virtualenv to the rescue!
Check out the modified drone build script below:
Below is the new build.sh script:
And our new Dockerfile looks like this:
The result of this is a python docker image that runs our behavior tests when this docker container is run. The build.sh script uses the volume mounted ssh key to pip install any private repositories we need (like a common utilities library).