datasette-dashboards
htl
| datasette-dashboards | htl | |
|---|---|---|
| 2 | 1 | |
| 131 | 296 | |
| - | 1.7% | |
| 7.9 | 0.0 | |
| 3 days ago | 10 months ago | |
| Python | JavaScript | |
| Apache License 2.0 | ISC License |
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datasette-dashboards
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Observable 2.0, a static site generator for data apps
Me too, and that lead to developing the « datasette-dashboards » plugin[0]. I use this for my company where all the data is gathered by connectors scheduled in CI, storing data in Git, and triggering a SQLite db build and Datasette deployment. « BI as Code » if you will
[0] https://github.com/rclement/datasette-dashboards
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The interesting ideas in Datasette (2018)
https://github.com/rclement/datasette-dashboards
It is still very alpha but usable if you know Vega syntax.
Looking for some contributors to bring Datasette to the level of Metabase!
htl
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Observable 2.0, a static site generator for data apps
From the Observable Framework point of view, you’re very welcome to use Apache ECharts or any other library instead of Observable Plot, since you can import whatever you like and it’s all just JavaScript.
Since there was a lot of interest in this thread, Mike added a page to the docs with an ECharts example: https://observablehq.com/framework/lib/echarts
There are two pieces of that example code specific to Framework: the html`` tagged template literal creates a DOM element (see https://github.com/observablehq/htl, also usable outside Framework), and the display function inserts it into the document above the code block (see https://observablehq.com/framework/javascript/display). Note that, whereas Observable Plot takes an options object and returns a DOM element, ECharts instead takes a DOM element and mutates it — but in general they should be equally easy to use in Framework.
Like Plot (and Vega-Lite, another great option), ECharts is also now one of Framework’s built-in “recommended libraries” (see https://observablehq.com/framework/javascript/imports#implic...), meaning that if you reference `echarts` Framework will lazy-load it for you. Adding that was a two-line diff: https://github.com/observablehq/framework/pull/811/files#dif.... But I wanna emphasize that Framework doesn’t have to explicitly “support” a given library for you to use it. “Supporting” in this case just means the convenience of saving you a one-line import statement. But don’t wait for our blessing!! Use whatever.
What are some alternatives?
sqlite-utils - Python CLI utility and library for manipulating SQLite databases
plot - A concise API for exploratory data visualization implementing a layered grammar of graphics
datasette-graphql - Datasette plugin providing an automatic GraphQL API for your SQLite databases
obsplot - Observable Plot bindings for R
datasette-dateutil - dateutil functions for Datasette
evidence - Business intelligence as code: build fast, interactive data visualizations in pure SQL and markdown
datasette-chatgpt-plugin - A Datasette plugin that turns a Datasette instance into a ChatGPT plugin
opendata.cern.ch - Source code for the CERN Open Data portal
datasette-ripgrep - Web interface for searching your code using ripgrep, built as a Datasette plugin
pulseui - Real-time interactive database applications
vega-lite - Visualizations created using the Vega-Lite language
observable-codespace - Codespace prerequisites for starting with Observable Framework.