To help keep myself honest, I wanted to set up automated test runs on a few personal projects I host on Github. At first I gave Travis a try, since a number of projects I contribute to use it, but it felt a bit clunky. When I found Github had a new CI system in beta, I signed up for the beta and was accepted a few weeks later.
While it is still in development, the configuration language feels lean and powerful. In comparison, Travis’s configuration language has obviously evolved over time with some features not interacting properly (e.g. matrix expansion only working on the first job in a workflow using build stages). While I’ve never felt like I had a complete grasp of the Travis configuration language, the single page description of Actions configuration language feels complete.
The main differences I could see between the two systems are:
- A Github workflow is composed of multiple jobs right from the start.
- All jobs run in parallel by default. It is possible to serialise jobs (similar to Travis’s stages) by declaring dependencies between jobs.
- Each job specifies which VM image it will run on, with a choice of Ubuntu, Windows, or MacOS versions. If you choose Ubuntu, you can also specify a Docker container to run your build in, giving access to other Linux build environments.
- Each job can have a matrix attached, allowing the job to be duplicated according to a set of parameters.
- Jobs are composed of a sequence of steps. Unlike Travis’s fixed set of build phases, these are generic.
- Steps can consist of either code executed by the shell or a reference to an external action.
The first project I converted over was asyncio-glib, where I was using Travis to run the test suite on a selection of Python versions. My old Travis configuration can be seen here, and the new Actions workflow can be seen here. Both versions are roughly equivalent, although the actions/setup-python@v1 action doesn’t currently make beta releases of Python available. The result of a run of the workflow can be seen here.
For a second project (videowhisk), I am running the tests against the VM’s default Python image. For this project, I’m more interested in compatibility with the distro release’s GStreamer libraries than compatibility with different Python versions. I suppose I could extend this using the matrix feature to test on multiple Ubuntu versions, or containers for other Linux releases.
While I’ve just been using this to run the test suite, it looks like Actions can be used for a lot more. A project can have multiple workflows with different triggers, so it can also be used for automated triage of bugs or pull requests (e.g. request a review from a specific developer when a pull request is created that modifies files in a specific directory). It also looks like I could create a workflow to automatically publish to PyPI when I push a new tag to the repository that looks like a version number.
It will be interesting to see what this does to the larger ecosystem of “CI as a service” products built to work with Github. On the one hand having a choice is nice, but on the other hand it’s nice to have something well integrated. I really like Gitlab’s integrated CI system for projects I have hosted on various Gitlab instances, for example.