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marimo-team/marimo

A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor. observed · 2026-08-28

github.com/marimo-team/marimo · homepage · Python · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

90/100

  • Activity 99
  • Release rhythm 86
  • Longevity 79
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 2
  • age_days: 1115
  • days_rel: 16
  • days_push: 7
  • n_releases_24m: 188

Full methodology

Adoption not part of the score

22500 stars · 1239 forks observed · 2026-08-28

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

marimo is a reactive Python notebook stored as pure Python files, where running a cell automatically re-runs dependent cells to keep code and outputs consistent. Notebooks can be executed as scripts, deployed as interactive web apps, queried with SQL, and edited with built-in AI assistance.

Use cases

  • replace jupyter notebooks with a reproducible reactive python notebook
  • build interactive data apps with sliders and widgets without callbacks
  • query dataframes and databases with sql in a notebook
  • run notebooks as python scripts with cli arguments
  • deploy a notebook as a shareable web app
  • version notebooks with git as pure python files
  • pair coding agents like claude code with a running notebook
  • explore and transform data with an ai-native editor

When to choose

  • you want reproducible notebooks with no hidden state and consistent outputs
  • you need notebooks stored as git-friendly pure python files
  • you want to turn a notebook into an interactive app or script without rewriting it
  • you need built-in sql support for dataframes, databases, and warehouses
  • you want AI-assisted code generation that understands your notebook's variables

When to avoid

  • your team and tooling are deeply invested in the jupyter/ipykernel ecosystem
  • you need cell-by-cell arbitrary execution order rather than reactive dataflow
  • you only need lightweight scratch experimentation with no reproducibility requirements
  • you rely on jupyter-specific extensions or widgets incompatible with marimo

Facets

application · maturity active

data-visualization developer-tools editor gui web-framework cli nlp machine-learning data-science data-science developer-tools machine-learning data-visualization web-development artificial-intelligence python cross-platform cli wasm notebook reactive-programming jupyter-alternative streamlit-alternative sql git-friendly interactive-widgets dataflow ai-native reproducibility web-server docker

10 sources

Member repositories

RepositoryRoleHealth v2
marimo-team/marimomain90

For agents

markdown · JSON · MCP: product_card(name="marimo-team/marimo")

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