Ross ROSS = Recommend OSS · open-source software intelligence for agents

Bokeh

Interactive Data Visualization in the browser, from Python observed · 2026-10-17

github.com/bokeh/bokeh · homepage · TypeScript · BSD-3-Clause (permissive) observed · 2026-10-17

Health v2 · maintenance only

77/100

  • Activity 100
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 5321
  • days_rel: n/a
  • days_push: 4
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

20458 stars · 4269 forks observed · 2026-10-17

What it is AI-extracted, prompt v1, taxonomy v1, 2026-10-19, confidence 0.98

Bokeh is a Python library for creating interactive visualizations that run in modern web browsers. It supports standalone HTML output as well as server‑backed applications with live Python callbacks.

Use cases

  • Create interactive line, bar, and scatter plots in Jupyter notebooks.
  • Build dashboards with widgets and real‑time streaming data.
  • Embed responsive visualizations in web pages without writing JavaScript.
  • Develop Bokeh server applications that react to user input via Python callbacks.
  • Generate geographic maps and network graphs with hover tooltips.

When to choose

  • You need high‑performance interactivity for large or streaming datasets.
  • You prefer writing visualizations in Python and want optional JavaScript‑free output.
  • Your workflow includes Jupyter notebooks or ASGI web frameworks like FastAPI.
  • You want a mature, well‑documented library with extensive example gallery.

When to avoid

  • You require ultra‑low‑latency rendering that only WebGL‑based libraries provide.
  • You need a pure JavaScript library for front‑end developers without Python.
  • Your project demands a small bundle size for static sites.

Facets

library · maturity active

data-visualization web-framework data-science web-development data-visualization python browser interactive-plots javascript bokehjs notebook asgi streaming widgets widget server jupyter

10 sources

Member repositories

RepositoryRoleHealth v2
bokeh/bokehmain77
bokeh/bokeh-notebooksexamples10
bokeh/jupyter_bokehplugin74
bokeh/tutorialexamples60

For agents

markdown · JSON · MCP: product_card(name="bokeh/bokeh")

Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem