(2022-12-07) Udell Mastodon Steampipe And Rss
Jon Udell has a series on Mastodon, often involving creating a custom UI using Steampipe.
I was determined to write my Mastodon #introduction today. To get started I used the tag search in the dashboard I’m building.
The idea was to look at a bunch of other #introduction posts to get a feel for how mine should go
Recall that https://mastodon.social/tags/introduction
is the home page for that variant of the tag. There you can see introduction posts from people using the tag. Those posts typically include other tags
Then I remembered that certain classes of Mastodon page have corresponding RSS feeds, and wondered if the tag pages are members of one such class
The new ingredients, courtesy of the RSS feed, are: guid which links to an individual introduction like Kathy’s, published which is the day the introduction appeared, and categories which has the tags used in the introduction post. Sweet! Now I can scan the dashboard to get a sense of which introductions I want to check out.
This delights me in so many ways. When the blogosphere first emerged in the early 2000s, some of us discovered that the RSS protocol was capable of far more than just delivering feeds to RSS readers.
I’m equally delighted to show how Steampipe enables this modern exercise in RSS-powered integration. Steampipe was, originally, an engine for mapping results from JSON API endpoints to SQL tables. Over time, though, it has broadened its view of what constitutes an API. You can use Steampipe to query CSV files, or Terraform files, or — as we see here — RSS feeds.
Data comes in all kinds of flavors. Steampipe abstracts those differences and brings all the flavors into a common space where you can reason over them using SQL.
A month ago, when the Great Discontinuity happened, I started working on a Steampipe plugin to enable SQL queries against the Mastodon API, along with a companion Steampipe “mod” (suite of dashboards) to display and chart the results of those queries.
My own motivation, originally, was to do Mastodon analytics. I thought Steampipe’s SQLification of the API would be a handy way to discern and monitor activity trends during a period of extraordinary flux.
my focus shifted. I began to see the suite of dashboards as a Mastodon reader/browser that complements the web and phone clients, and that’s how I mainly use them now.
I think the key benefit is one of Edward Tufte’s core principles: information density
For me, at least, this approach has become an effective way to browse the fediverse, find interesting people, read what they boost, and keep track of my own activity.
A Bloomberg terminal for Mastodon
The outcome, so far, is a suite of dashboards that display tabular views (along with some charts) of the home, local, and federated timelines, of my toot history and my favorites, of my follows and followers, of my notifications, of searches for terms, people, and hashtags, and of the timelines formed by the lists to which I’ve assigned people I follow
No images? No links in toot content? What good is that?
my home timeline in the Steampipe dashboard. I can see a dozen items at a glance, and can easily scan 100 items in gulps of that size
When I described this effect to Greg Wilson he gave me the title for this post: “That sounds like the Bloomberg terminal for Mastodon.”
The underlying principle is one I’ve learned from Edward Tufte: present information at maximum density
To enhance the effect, I’ve begun to apply filters...
Create your own Mastodon UX
As a warmup exercise, I decided to first add a simple control for boosts that enables me to see my home timeline with or without boosts
Steampipe dashboards are built with two languages. HCL (Hashicorp configuration language) defines the UX widgets, and SQL fills them with data. In this case we’re selecting static values for the boosts input. But any Steampipe query can run there
The HCL code may be unfamiliar. Steampipe uses HCL because its core audience are DevSecOps pros who are familiar with Terraform, which is HCL-based. But its a pretty simple language that can be used to describe all kinds of resources.
The other thing to know, if you want to roll up your sleeves and try building your own dashboards, is that the developer experience is — again in my biased opinion! — pretty great because if you’re using an autosaving editor you’ll see your changes (to both HCL and SQL code) reflected in realtime.
realtime feedback when your SQL queries provoke Postgres errors. The experience feels very much like the one Bret Victor champions in Inventing on Principle. The core principle: “Creators need an immediate connection to what they’re creating.”
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