💻 programming

marimo

The next generation of Python notebooks

#Open source
#cooperation
#data science
#Python
#notebook
marimo

Product Details

Marimo is an open source Python reactive notebook that is reproducible, git-friendly, executable as a script, and shareable as an application. It responds to cell changes by automatically running affected cells, eliminating the tedious work of managing notebook state. Marimo's UI elements such as data frame GUIs and charts make data processing fast, futuristic and intuitive. Marimo notebooks are stored as .py files and can be used with git version control, run as Python scripts, or import symbols into other notebooks or Python files and lint or format them using your favorite tools. All in a modern, AI-powered editor.

Main Features

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- Reactive execution: run a cell and Marimo will respond by automatically running the affected cells, eliminating the need to manually manage notebook state.
2
- Interactive elements: Provides reactive UI elements such as data frame GUI and charts, making data processing intuitive and fast.
3
- Code and Model Experimentation: Quickly experiment with code and models, binding UI elements to Python values.
4
- Python-first design: Notebooks are written in pure Python, stored as .py files, and can be used with git version control.
5
- Reproducible execution: the notebook is executed in a deterministic order, there is no hidden state, when a cell is deleted marimo deletes its variables and updates the affected cells.
6
- Collaboration friendly: Notebooks can be collaborated with git, small changes produce small differences, and notebooks can be exported as HTML or served as web applications.
7
- Developer experience: The editor includes GitHub Copilot, auto-completion, hover prompts, vim key bindings, code formatting, debugging panel and extensive hotkeys.

How to Use

1
1. Visit the marimo official website and download and install the Python package: run `pip install marimo` through the command line.
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2. Start marimo: After the installation is complete, enter `marimo tutorial intro` on the command line to start an introductory tutorial.
3
3. Explore the online playground: Visit the link provided to try out marimo's online programming environment.
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4. Create and edit notebooks: Use the marimo editor to create new notebooks or edit existing .py files.
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5. Run and share notebooks: Write code in the notebook, run cells, and use the marimo CLI to export the notebook to HTML or serve it as a web app.
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6. Collaboration and version control: Use git for notebook version control and collaboration.

Target Users

The target audience is Python developers, data scientists, and researchers. With its reactive programming environment, powerful interactivity, and collaboration capabilities, marimo is particularly suitable for professionals who need to perform complex data processing and analysis, as well as developers who want to quickly transform code and analysis results into shareable applications.

Examples

- Interactive Embedding Explorer: Created by the marimo team for interactive exploration of data and models.

- Neural Networks with Micrograd: Created by the marimo team for building and training neural networks.

- Trajectory Planning: Created by Philipp Schiele for computational experiments in spacecraft trajectory planning.

Quick Access

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