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

jupyter-naas/awesome-notebooks resource

[Legacy] Data & AI Notebook templates catalog organized by tools, following the IMO (input, model, output) framework for easy usage and discovery.. observed · 2026-08-28

github.com/jupyter-naas/awesome-notebooks · homepage · Jupyter Notebook · BSD-3-Clause (permissive) observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • 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 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 2163
  • days_rel: n/a
  • days_push: 681
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

3014 stars · 489 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A curated catalog of production-ready Jupyter Notebook templates organized by tool and structured with an Input-Model-Output (IMO) framework. It serves as a template library for building data products like dashboards and automation/AI engines.

Use cases

  • find jupyter notebook templates for data analysis
  • build a dashboard from a notebook template
  • automate tasks with ready-made python notebooks
  • learn how to structure notebooks with input model output
  • connect to third-party apis from a notebook template
  • kickstart a data product with reusable notebook components

When to choose

  • you want pre-built, production-ready notebook templates instead of starting from scratch
  • you need examples of integrating Jupyter with third-party tools via APIs
  • you want a consistent IMO structure for organizing data workflows

When to avoid

  • you need actively maintained or updated templates, as the repository is marked legacy
  • you want a software library or package rather than a collection of notebooks
  • you require templates without any data science setup skills

Facets

dataset · maturity maintenance

developer-tools data-science data-visualization workflow-automation machine-learning data-science developer-tools tutorials awesome-lists python jvm cross-platform jupyter-notebooks notebook-templates awesome-list imo-framework data-products legacy automation

2 sources

Member repositories

RepositoryRoleHealth v2
jupyter-naas/awesome-notebooksmain32

For agents

markdown · JSON · MCP: product_card(name="jupyter-naas/awesome-notebooks")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem