# markusschanta/awesome-jupyter

A curated list of awesome Jupyter projects, libraries and resources

Repository: https://github.com/markusschanta/awesome-jupyter
Canonical: https://ross.abutalabs.com/products/awesome-jupyter
License: CC-BY-SA-4.0
License Family: other
Topics: jupyter-notebook, jupyter, jupyterhub, jupyterlab, awesome, awesome-list, python, visualization, frontend, jupyterlab-extension, ipython, data-science, data-visualization
Last push: 2026-08-26T00:00:34+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 3293, "days_push": 8, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4662, forks 462 (observed 2026-08-28T04:08:56.468723+00:00)

## What it is
A curated awesome-list of Jupyter projects, libraries, extensions, and resources covering runtimes, visualization, collaboration, and publishing. It serves as a discovery index for the Jupyter ecosystem rather than a tool itself.

## Use cases
- find jupyterlab extensions for my workflow
- discover tools for sharing jupyter notebooks
- best libraries for data visualization in jupyter
- how to run jupyter notebooks in docker
- resources for teaching with jupyter notebooks
- tools for version controlling notebooks
- hosted jupyter notebook services comparison

## When to choose
- you want a broad, community-curated index of the Jupyter ecosystem
- you're exploring options for notebook runtimes, extensions, or hosting
- you need starting points for Jupyter-based data science workflows

## When to avoid
- you need a working tool rather than a list of links
- you need up-to-date maintenance status for every listed project
- you need official Jupyter documentation instead of a third-party index

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools, data-visualization, documentation
- domain: data-science, awesome-lists, developer-tools, data-visualization
- platform: python, cross-platform
- tags: awesome-list, jupyter, jupyterlab, notebooks, curated-list, ipython

## Member repositories
- markusschanta/awesome-jupyter (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:56.468723+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:19:26.711178+00:00, confidence not recorded.
  - readme: https://github.com/markusschanta/awesome-jupyter (fetched 2026-08-28T04:08:56.468723+00:00, sha 92ef96de5296)
- Data as of 2026-08-30T08:39:29.467469+00:00.