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Streamlit is a python library to build data apps. This is similar to observable, and evidence.

With uv, it is easy to see what streamlit looks like -- uv run --with streamlit streamlit hello -- this launches a demo app with a couple different visualization screens.

This is more along the lines of "UI controls that allow you to change the parameters of a chart/visualization" than evidence's "Dynamic report" approach.

Streamlit is a pythonic middle ground between reporting oriented evidence and a very visualization oriented observable.

another way to look at these three: streamlit is python, observable is javascript, and evidence is sql.

Evidence is "Business Intelligence as Code"; which means it allows you to build reports, and standard business data visualization ( charts, and basic graphics) using sql with markdown as the glue between various data and visualization elements. You can put to gether a dynamic report with a few interactive elements (e.g: filter data, change date ranges) that can be exported as "static" web pages. The exported web pages will also have interactive elements (e.g: tooltip on hover, charts that re-render when you change the data criteria). You can see the github; and examples

datasette is another player in this space -- "data applications using sql" space, but evidence goes much further by supporting various data backends, and having first class support for thinking in terms of reports, and standard visualization components like charts. Support for markdown is naturally expected.

The combination of markdown + code does put it in a group with jupyter, but the availability of dynamic controls also make you think of streamlit, but does not go as far as observable because observable, given it's pedigree with d3 etc., is a lot more capable visulization tool (think maps, and advanced dataviz techniques).

Data applications (usually), web application frameworks that make it easy to publish data as dynamic reports that have an element of interactivity to them that is not possible in static reports, they are often purpose-built to tell a story or present findings backed by data.

Frameworks

evidence is a lightweight framework for building data apps using SQL. It's open source and free to get started.

observable is another example -- that uses javascript

Briefer | The collaborative data platform -- "jupyter notebooks meet Notion-like documents. Briefer is the multiplayer notebook that let's you run SQL and Python, and turn notebooks into dashboards and Data Apps.

Mercury – Build Data Web Apps in Jupyter Notebook You don't need to know frontend frameworks, HTML, CSS or JavaScript. All in pure Python without leaving Jupyter Notebook.

my mercury account

Observable: Build expressive charts and dashboards with code -- Read the announcement of 2.0 -- Observable 2.0 | Observable. Mike Bostock of the NYT, d3 fame is the founder of observable.

Static sites for data apps?! a recording of the talk given by Robert Kosara of Observable.

See also evidence