Python-first notebook format
marimo stores notebooks as pure Python `.py` files, which makes them usable as scripts, reusable as modules, and easy to version with Git.
marimo
Claimmarimo is a next-generation Python notebook for exploring data, running SQL, and building interactive apps. Pure Python files, reactive execution, and app deployment.
Overview
marimo is a next-generation Python notebook for exploring data, running SQL, training models, and building interactive apps. It is presented as a reactive notebook stored as Git-friendly, reproducible Python, with the same notebook able to run as a script, module, or web app.
The product is open source and aimed at developers and data practitioners who want a single environment for notebook-style exploration and application delivery. The homepage and case studies show it being used for data exploration, experiment tracking, customer data analysis, dashboards, and internal tools across ML, backend, and analytics teams.
Features
Reactive execution
When a cell changes, marimo reruns affected cells automatically so code and outputs stay in sync and notebook state stays explicit.
Interactive notebook UI
The editor includes sliders, dropdowns, dataframe tables, selectable plots, autocomplete, hover tooltips, debugging panels, hotkeys, and vim keybindings for working directly in the notebook.
SQL and data exploration
Built-in SQL cells let users query dataframes and databases, with support for Polars, Pandas, PyArrow, DuckDB, SQLite, Postgres, MySQL, and other backends.
App and script outputs
Notebooks can be exported to WebAssembly-powered HTML or served as web apps with the marimo CLI, so the same notebook can be used as a shared application.
Developer and agent tooling
The product ships with a CLI, a library, a VS Code extension, and support for agent-assisted workflows through marimo pair.
Use Cases
Interactive data exploration
Use marimo to investigate datasets, run SQL, and iterate on transformations in a notebook that updates dependent cells automatically as you change code or values.
Notebook-to-app workflows
Use the notebook to move from analysis to a shareable app without rewriting the work in a separate framework, then serve it through the CLI or export it as HTML.
Python engineering workflows
Use marimo when the team wants notebooks that fit normal software practices such as Git versioning, module reuse, script execution, and testing with PyTest.
Internal data apps and dashboards
Use the built-in controls, SQL cells, and app deployment pattern for dashboards, internal tools, and customer-facing data experiences, as shown in the Sumble and Bunkerhill case studies.
Collaborative review and feedback
Use marimo in cross-functional settings where engineers, analysts, or domain experts need to review outputs and annotate work in the same interactive environment.
Pros and Cons
Pros
- Pure Python notebook files are easier to version, reuse, and run outside the notebook UI.
- Reactive execution reduces hidden state and keeps outputs aligned with code changes.
- Built-in interactive controls and SQL cells support exploratory data analysis in one place.
- The same notebook can be shared as an app or run as a script, which helps move from prototype to internal tool.
- Case studies show real team usage across ML, backend, radiology, sales, and analytics workflows.
Cons
- The pricing page provided here returns a 404, so pricing and tier details are not available from the supplied evidence.
- The source does not provide a complete integrations list or deployment matrix, so environment fit may need to be checked in the docs before adoption.
FAQ
What is marimo?
marimo is a Python notebook that stores notebooks as pure .py files. The homepage says notebooks can be run as scripts, shared as apps, versioned with Git, and used for data exploration and SQL work.
Is marimo free or paid?
The source describes marimo as an open source product, and the Sumble case study says it is free and open source. The pricing page itself returns a 404, so no paid-plan details are available from the provided evidence.
Can marimo notebooks be turned into apps?
Yes. The homepage says marimo notebooks can be exported to WebAssembly-powered HTML or served as web apps with the marimo CLI, and case studies show teams using marimo to deploy interactive apps internally.
Does marimo support SQL and dataframes?
The homepage says marimo supports built-in SQL cells and integrates with Polars, Pandas, PyArrow, DuckDB, SQLite, Postgres, MySQL, and other backends.
Who uses marimo?
The source supports teams using marimo for data exploration, model experimentation, interactive dashboards, and internal tools. It also shows it being used by ML engineers, backend engineers, radiologists, sales teams, and data scientists.
Quick Facts
- Category
- Python notebook
- Platform
- Web app, CLI, library, and VS Code extension
- Source domain
- marimo.io
- Primary users
- Developers, data scientists, ML engineers, and analytics teams
- Code format
- Pure Python `.py` files
- Pricing evidence
- Pricing page returns 404 in the provided source
Analytics of marimo
marimo· Monthly Visits 171.4K· Global Rank #205,482
Traffic data is for reference only.
- Monthly Visits
- 171.4K
- Global Rank
- #205,482
- Category Rank
- #3,758
- User Bounce Rate
- 37.9%
- Avg. Visit Duration
- 01:11
- Pages per Visit
- 3.76
Traffic Trends
| Apr | 171025 |
|---|---|
| May | 156621 |
| Jun | 171371 |
Traffic Sources
- Direct31.5%
- Search43.3%
- Referral18.7%
- Social5.20%
- Mail0.84%
- Affiliate0.00%
Top Regions
- United States19.4%
- Germany7.53%
- United Kingdom7.32%
- India5.21%
- Brazil4.21%
- Others56.3%