Skip to main content

A library for making reactive notebooks and apps

Project description

A reactive Python notebook that's reproducible, git-friendly, and deployable as scripts or apps.

Docs · Discord · Examples

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, executable as scripts, and deployable as apps.

Highlights.

  • reactive: run a cell, and marimo automatically runs all dependent cells
  • interactive: bind sliders, tables, plots, and more to Python — no callbacks required
  • reproducible: no hidden state, deterministic execution
  • executable: execute as a Python script, parametrized by CLI args
  • shareable: deploy as an interactive web app, or run in the browser via WASM
  • git-friendly: stored as .py files
pip install marimo && marimo tutorial intro

Try marimo at our online playground, which runs entirely in the browser!

Jump to the quickstart for a primer on our CLI.

A reactive programming environment

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.

Deterministic execution order. Notebooks are executed in a deterministic order, based on variable references instead of cells' positions on the page. Organize your notebooks to best fit the stories you'd like to tell.

Synchronized UI elements. Interact with UI elements like sliders, dropdowns, and dataframe transformers, and the cells that use them are automatically re-run with their latest values.

Performant runtime. marimo runs only those cells that need to be run by statically analyzing your code.

Compatible with expensive notebooks. You can optionally disable expensive cells to prevent them from automatically running, or configure the runtime to be lazy and mark affected stales as stale instead of automatically running them.

Batteries-included. marimo comes with GitHub Copilot, Black code formatting, HTML export, fast code completion, a VS Code extension, and many more quality-of-life features.

Quickstart

Installation. In a terminal, run

pip install marimo  # or conda install -c conda-forge marimo
marimo tutorial intro

Or run in Gitpod.

Click this link to open the repo in a Gitpod Workspace:

https://gitpod.io/#https://github.com/marimo-team/marimo

Create notebooks.

Create or edit notebooks with

marimo edit

Run apps. Run your notebook as a web app, with Python code hidden and uneditable:

marimo run your_notebook.py

Execute as scripts. Execute a notebook as a script at the command line:

python your_notebook.py

Automatically convert Jupyter notebooks. Automatically convert Jupyter notebooks to marimo notebooks with the CLI

marimo convert your_notebook.ipynb > your_notebook.py

or use our web interface.

Tutorials. List all tutorials:

marimo tutorial --help

Questions?

See the FAQ at our docs.

Learn more

marimo is easy to get started with, with lots of room for power users. For example, here's an embedding visualizer made in marimo (video):

Check out our docs, the examples/ folder, and our gallery to learn more.

Tutorial Inputs Plots Layout

Contributing

We appreciate all contributions! You don't need to be an expert to help out. Please see CONTRIBUTING.md for more details on how to get started.

Questions? Reach out to us on Discord.

Community

We're building a community. Come hang out with us!

Inspiration ✨

marimo is a reinvention of the Python notebook as a reproducible, interactive, and shareable Python program, instead of an error-prone JSON scratchpad.

We believe that the tools we use shape the way we think — better tools, for better minds. With marimo, we hope to provide the Python community with a better programming environment to do research and communicate it; to experiment with code and share it; to learn computational science and teach it.

Our inspiration comes from many places and projects, especially Pluto.jl, ObservableHQ, and Bret Victor's essays. marimo is part of a greater movement toward reactive dataflow programming. From IPyflow, streamlit, TensorFlow, PyTorch, JAX, and React, the ideas of functional, declarative, and reactive programming are transforming a broad range of tools for the better.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

marimo-0.6.13.tar.gz (9.9 MB view details)

Uploaded Source

Built Distribution

marimo-0.6.13-py3-none-any.whl (10.1 MB view details)

Uploaded Python 3

File details

Details for the file marimo-0.6.13.tar.gz.

File metadata

  • Download URL: marimo-0.6.13.tar.gz
  • Upload date:
  • Size: 9.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.10.14

File hashes

Hashes for marimo-0.6.13.tar.gz
Algorithm Hash digest
SHA256 797112296ddb6782b9ba617650e19ef7c52cb73194872ebf93555a90601657ac
MD5 c0a9cf363e430caefa6c80305e0fdb85
BLAKE2b-256 2d2034c8e91640fdab22e11fc55366a620b1baa592ea99f2ed5f1f0c1332ffd1

See more details on using hashes here.

File details

Details for the file marimo-0.6.13-py3-none-any.whl.

File metadata

  • Download URL: marimo-0.6.13-py3-none-any.whl
  • Upload date:
  • Size: 10.1 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.10.14

File hashes

Hashes for marimo-0.6.13-py3-none-any.whl
Algorithm Hash digest
SHA256 ee40f66a8b829b1cb32de536a569fd6f3604e0ac4472142840bfb515df1156b6
MD5 3f7889fcc2fd0033ba53cb416a7a2512
BLAKE2b-256 1e6f8ad5b8aef18a0c1d62d138b0008c35677bf772e5f55a39244fee5059d23e

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page