More than Jupyter. MINEO Notebooks combine Python, interactive widgets, AI assistant blocks, and Data App deployment in one collaborative workspace.
File View Block Kernel Help 
Quarterly breakdown by region with growth projections.
df = mineo.query("SELECT region, SUM(revenue) FROM sales GROUP BY region")
px.bar(df, x="region", y="revenue", title="Q4 Revenue")
Key insight: North America drives 43% of total revenue. APAC showed the strongest growth at +23% QoQ, driven by expansion in Japan and Australia.
df.sort_values("revenue", ascending=False).head()
| Region | Revenue | Growth |
|---|---|---|
| North America | $1.8M | +12% |
| Europe | $1.1M | +8% |
| APAC | $820K | +23% |
| LATAM | $480K | -3% |
Author in Python, enrich with visual controls, and ship the same notebook as a polished Data App.
Mix code, markdown, assistant, widgets, and snippets inside one notebook.
Each session gets its own encrypted execution context, kernel state, logs, and packages.
Work with your team in real time, keep version history, and publish as a live Data App.
MINEO notebooks are not just code cells. They are a structured workspace for analysis, controls, documentation, and AI-assisted work.
Write Python, document your logic, and reuse common building blocks without leaving the notebook.
Add SQL queries, charts, KPIs, forms, uploads, and layouts to turn notebooks into interactive user-facing experiences.
Use MINEO Assistant directly inside the notebook to explain, generate, and refine code or analysis block by block.
The notebook experience is backed by isolated workers, managed kernels, project context, and APIs that let notebooks orchestrate more than just cells.
Notebook sessions run in their own workers with encrypted communication and session-specific context.
Keep shared context across blocks, inspect memory and logs, access project variables, and query datasources or workbenches from code.
Bring extra Python packages into the running worker and keep moving without rebuilding infrastructure.
Link notebooks to project files and resources so outputs connect cleanly to the rest of your workspace.
Use project and environment variables directly inside notebooks and snippets.
Track notebook evolution with built-in version history and Git-oriented workflows.
Work with teammates in the same notebook using comments and real-time editing.
A notebook can stay technical for builders and still become a polished Data App for stakeholders. Layouts, widgets, and app mode close that gap.
Structure blocks into cleaner interfaces that feel like Data Apps, not raw notebooks.
Let Data App users filter, upload, select, and explore without touching code.
Publish the same notebook as a production-ready Data App without rebuilding it somewhere else.
Technical references, implementation details and examples for teams building on MINEO.
Start with Python, add widgets and assistant blocks, then ship it as a live Data App.
