Mito

Mito Spreadsheet is an AI-powered, low-code platform that turns spreadsheets into Python-powered data apps and automation. It provides an in-editor experience where spreadsheet formulas are automatically translated into Python, enabling code completions, smart debugging, and AI-assisted chat directly within Jupyter-like environments. It supports running in Jupyter, Streamlit, and Dash, and aims to help teams accelerate data workflows from Excel-style tasks to interactive dashboards and data apps.

How to Use Mito Spreadsheet

1. Install Mito via Python package manager. Example: pip install mitosheet and pip install mito-ai.
2. Open in your notebook or app: Use Mito as a Jupyter extension or Streamlit component to start editing spreadsheets.
3. Edit and transform: Build formulas (e.g., VLOOKUP, pivots, graphs). Every edit is automatically converted to Python behind the scenes.
4. Leverage AI assistance: Use the AI chat to get Python code suggestions, explanations, and fixes within your data workflow.
5. Publish dashboards: Share interactive Streamlit or Dash dashboards that reflect the underlying spreadsheet automation.

Note: Mito emphasizes low-code automation, improved reproducibility, and fast iteration for data tasks.

Core Capabilities

• Spreadsheet Editor that converts edits to Python automatically
• 100+ transformations and data manipulations visible as code
• AI Chat integrated into the data workspace for explanations and code suggestions
• Code Completions to finish your thoughts and fix typos without leaving the editor
• Smart Debugging to explain errors and propose fixes with a click
• Easy setup in Jupyter, Streamlit, and Dash without additional infrastructure
• Extensions and environments: JupyterLab, Jupyter Notebooks, JupyterHub, SageMaker, Streamlit, Dash
• Ability to upgrade Python scripts to interactive dashboards (Streamlit/Dash)
• Open-source options and community resources via documentation and Discord/GitHub

How It Works

• You write or edit spreadsheet-like data; Mito translates edits into Python code in the background.
• Use Python-based transformations to build data apps and dashboards without heavy boilerplate.
• AI-assisted features help with code generation, debugging, and understanding complex data tasks.

Use Cases

• Spreadsheet-to-code automation: convert Excel-like tasks into Python workflows
• Lightweight data apps and dashboards for rapid prototyping
• Data quality checks, transformations, and exploratory analysis within a familiar interface

Safety and Legal Considerations

• Ensure proper handling of sensitive data and comply with organizational data governance policies when sharing dashboards or code.

Core Features

• AI-powered spreadsheet-to-Python transformation
• Real-time code completions and smart debugging
• AI Chat integrated into Jupyter environments for guidance
• One-step installation and minimal infrastructure requirements
• Supports Jupyter, Streamlit, and Dash deployments
• Publish and share interactive dashboards from spreadsheet-based workflows
• Open-source options and extensive documentation/community resources