framework
datasette-dashboards
framework | datasette-dashboards | |
---|---|---|
9 | 2 | |
1,857 | 132 | |
7.5% | - | |
9.9 | 7.9 | |
about 7 hours ago | 2 days ago | |
TypeScript | Python | |
ISC License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
framework
- Observable Framework – The best dashboards are built with code
- Observable Framework 1.1
-
Interesting Ideas in Observable Framework
Thanks for the feedback. We have a PR open to make it easier to register new interpreters (without needing to fallback to .sh or .exe); it’ll let you specify the interpreter associated with a given file extension (e.g., .kts for Kotlin). https://github.com/observablehq/framework/pull/935
As for inputs-driving-data-loaders, that does go against the grain a bit since Framework favors static data snapshots so that the built site is self-contained and performant. But a technique that works well is to generate Parquet files in data loaders representing the superset of data that you want to interact with, and then using DuckDB/SQL in the client to extract the subset you want to visualize. This tends to perform well, though obviously it’s dependent on the size of the superset you want to interact with.
- Observable Framework: A static site generator for data apps, dashboards, reports
-
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.
datasette-dashboards
-
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
-
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!
What are some alternatives?
evidence - Business intelligence as code: build fast, interactive data visualizations in pure SQL and markdown
sqlite-utils - Python CLI utility and library for manipulating SQLite databases
owid-grapher - A platform for creating interactive data visualizations
datasette-graphql - Datasette plugin providing an automatic GraphQL API for your SQLite databases
dataflow - An experimental self-hosted Observable notebook editor, with support for FileAttachments, Secrets, custom standard libraries, and more!
datasette-dateutil - dateutil functions for Datasette
obsplot - Observable Plot bindings for R
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
pyobsplot - Observable Plot in Jupyter notebooks and Quarto documents
vega-lite - Visualizations created using the Vega-Lite language