In my previous post, I described a workflow that connects data with an app that visualizes the data.
There's one step left: automatically deploying the web app from GitHub to a server after every push to the repo's default branch.
In any project that shows data to users, be it documentation or a linguistic database, data must be separated from its representation.
This is almost an axiom. You have to keep your data in an easy-to-edit, non-proprietary format, while the tools with which you show the data to users can be as complex as needed. Tools tend to get outdated, and your data cannot depend on them.
I have a Python library called tinybear that contains all simple tools I have used to work with files in different formats. It is published on pypi.
I was too lazy to write a blog post about publishing my project, but, in a nutshell, poetry makes these things rather easy.
Now, while moving in a direction of project management in IT, and having recently got a referral for a technical writer role, I decided, it was time to create at least some simple documentation for tinybear.