“If you can’t measure it, you can’t improve it.”
(Update 03/17/2019): As I am currently writing this, I am quite behind on my seven-part series on concurrency models in Python, as begun in this post back in January. If I have mentioned this to you in person as something I wanted to do and to check my blog for updates, I apologize for the lack of progress on this front. It is still on my roadmap. Ideally, I’ll finish it up before PyCon 2019, and posts will be updated out of order (posted after this for their original due dates in January and February). Newer posts will be created after this one.
I had discovered Keep a Changelog shortly before joining my current company, and I was impressed by its arguments for why you should keep and maintain a good changelog. That need became ever more visible in my current role, where until very recently, there wasn’t a dedicated product manager for our small team. If I didn’t maintain a changelog, I’d make it more difficult for myself to inform internal customers, prospective additions to the team, or stakeholders about the work done on this project, and I’d lose a lot of the hard-earned knowledge to the void forever, with all the consequent and compounding problems that result from lossy communications. So I decided to maintain a changelog and see how it would help my development workflow, and if I could glean any insights from it after maintaining it for a while.
Migrations of unstructured data are nigh impossible: You may notice that the current “Keep a Changelog” points have Deprecated, Fixed, Security, Unreleased, and [YANKED] bullets. I think an older version of the site had only the “[ADDED] [CHANGED] [REMOVED]” bullets that I use here. I think the new bullets are an improvement, as a higher granularity of metrics may mean better-formed KPIs. I continued to use the old schema because using different schemas in the same changelog may be confusing to newcomers, because I don’t expect my tool to deal with security issues within enterprise environments, and because a manual re-write of a changelog is at the very bottom of a literal mountain of feature requests, bugs, and other issues I have on my plate.
Granularity varied but trended higher over time: When I first started off, I oftentimes just listed what happened, and didn’t add much detail (e.g.
[ADDED] Dependency 'py4j'.). Later on, I described why I was doing something (e.g.
[ADDED] Dependency 'pyjks' to convert OpenSSL-generated public keys into Java truststores.). I think this definitely helps in jogging my memory and detail why any particular action is important, and helps to automatically build the shared understanding when communicating the vision of a product.
There’s not enough information about what changes apply to a particular release: This is rectified in the newer release of our product, but for this release, I only keep the major/minor version numbers, and not the build versions or the patch versions. This means at a glance of the changelog, you can’t tell which features are available for a particular release. In practice, I use GitLens and
git blameto identify what changes are applicable between which releases, and more frequently the pull requests for a recent feature (which I make sure to always have the full changelog updates before merging). Oftentimes, since I’ve been working on this by myself for more than a year, I can do a simple mental recall if somebody has a question. This obviously isn’t scalable; hence the new changes to be implemented.
I do wish there were more [REMOVED] updates: At this point, I have made 174 [ADDED], 141 [CHANGED], and only 14 [REMOVED] updates to the project. I have found when I needed to remove some features, I do it in one fell swoop, and it’s because I had slowly added functionality to make all that code irrelevant. Still, there’s a lot of legacy code left in the product, and porting over functionality to new paradigms I’ve recently learned or implemented is slow going. I think we have a good balance between developer velocity and supporting customers, but without additional developers to give a real second opinion, that hypothesis remains untested. Deprecations are also unheard of in this product, and would be a highly welcome addition to my development workflows.
All in all, I’ve found maintaining a changelog to be highly worth it. It’s pretty much the only document that I constantly update and remember to update (design documents, flight rules, etc. become outdated at a brisk pace), I love the portability and independence it gives from deployment platforms (no GitHub releases and form-filling on web apps), and it’s great for giving a birds-eye view of what I have done.
(Correction on 2019/05/11): The above mentioned changelog was originally made available as part of this blog post. Due to a misunderstanding, it has been taken down.