Bring your Jupyter widgets to Shiny.

Dozens of integrations, grouped by what you're building.

Each group opens a set of guides. Every guide shows the widget rendering, the user's gestures flowing back to Python, and the widget updating in place.

11

Charts

plotly · altair · bokeh · matplotlib …

09

Maps & geospatial

lonboard · maplibre · ipyleaflet · kepler.gl …

04

3D

k3d · pythreejs · pyvista · ipyvolume

06

Scientific

nglview · niivue · vizarr · mols2grid …

04

Tables & grids

itables · reactable · perspective · ipydatagrid

04

Data exploration

embedding-atlas · mosaic · quak · pygwalker

02

Networks

ipycytoscape · ipysigma

03

Input & drawing

drawdata · ipycanvas · ipyfilechooser

A few lines of Python, from widget to input.

Pick a widget. The highlighted call is how your app reads what the user did; flip between before and after the gesture.

app.py

beforeafter

Every example runs as-is: shiny run app.py. See all the guides →

Three ideas, every widget.

Learn them once with one widget and they carry over to all the others. Each one is a page in the guide.

01

Render

Return a figure, map, or scene from a decorated function. It fills its card like any Shiny output.

@render_plotly
def plot():
    return px.scatter(df, ...)

02

React

Every gesture is an accessor. Call it from any reactive context, the way you'd call input.x().

@render.data_frame
def picked():
    return plot.selected_rows(df)

03

Update in place

Change the live widget from Python. Here a summary of the selection is written onto the chart, and the lasso and zoom stay put.

@reactive.effect
def _summarize():
    rows = plot.selected_rows(df)
    plot.widget.layout.annotations = [
        dict(text=f"{len(rows)} countries…", ...)
    ]

When your app outgrows the basics.

Millions of rows

Draw on the GPU, aggregate on the server, or query only what's visible. Three approaches, measured.

Large data & performance →

AI exploration

Let a chat filter your data, read a selection, or steer a map. The LLM sees the same accessors you do.

AI exploration →

import anywidget, traitlets

class Counter(anywidget.AnyWidget):
    _esm = "…"
    count = traitlets.Int(0).tag(sync=True)

@render_widget
def counter():
    return Counter()

counter.read("count")

Your widget isn't listed?

Any ipywidget or anywidget renders with @render_widget, including one you write yourself.

Any widget →