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.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
5 releases in the last 90 days, the latest 17 days ago, with 367 contributors on GitHub.
Use Cases & Benefits
- Provides a reactive Python notebook environment that ensures reproducible experiments, supports SQL queries, script execution, app deployment, and version control with git.
- Delivers automatic dependency tracking and reactive execution of cells, eliminating hidden state and manual re-running, while storing notebooks as pure Python files.
- Use for building reproducible and interactive data science experiments with automatic updates on variable changes and UI element interactions.
- Use for creating shareable, deployable Python notebooks as interactive web apps or slides with integrated SQL and AI-assisted code generation.
- Ideal for data engineers and analysts querying and manipulating large datasets interactively using SQL and reactive dataframes within a Python-native environment.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
A reactive Python notebook that's reproducible, git-friendly, and deployable as scripts or apps.
marimo is a reactive Python notebook: run a cell or interact with a UI element, and marimo automatically runs dependent cells (or marks them as stale), keeping code and outputs consistent. marimo notebooks are stored as pure Python (with first-class SQL support), executable as scripts, and deployable as apps.
Try marimo at our online playground, which runs entirely in the browser!
Jump to the quickstart for a primer on our CLI.
marimo guarantees your notebook code, outputs, and program state are consistent. This solves many problems associated with traditional notebooks like Jupyter.
A reactive programming environment. Run a cell and marimo reacts by automatically running the cells that reference its variables, eliminating the error-prone task of manually re-running cells. Delete a cell and marimo scrubs its variables from program memory, eliminating hidden state.
Compatible with expensive notebooks. marimo lets you configure the runtime to be lazy, marking affected cells as stale instead of automatically running them. This gives you guarantees on program state while preventing accidental execution of expensive cells.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
1.4K+156
Open issues
632+24
Compared with peers in AI
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| D4Vinci/Scrapling | 101.1K | +6.3K | 75 | 6 days ago |
| thedotmack/claude-mem | 115.8K | +4.7K | 75 | today |
| heygen-com/hyperframes | 82.3K | +4.0K | 75 | today |
| harry0703/MoneyPrinterTurbo | 142.0K | +3.8K | 75 | 3 days ago |
| github/spec-kit | 149.2K | +2.6K | 75 | today |
| marimo-team/marimo | 23.4K | — | 64 | 17 days ago |
| Category median | 115.8K | +4.0K | 75 | — |
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