Notebooks and data apps
Notebooks and data apps are widely used by data teams to explore datasets, test ideas, and share results with other stakeholders.
- Notebooks (for example, Jupyter or Marimo) are often used for prototyping, exploratory analysis, and quick experiments.
- Data app frameworks (for example, Streamlit) allow you to turn Python code into interactive applications that can be shared with a broader audience.
All of these environments can access Bauplan through the Python SDK. All the client methods exposed by the Bauplan data platform can be called from a notebook cell or an app callback to query tables, run pipelines, create branches, or materialize results.
When using notebooks or apps, it is good practice to work on a data branch rather than directly on main
. Branches provide an isolated data sandbox in the lakehouse, so exploration and app queries can be run on production data without affecting the production environment. This allows to:
- create temporary environments for analysis or prototyping,
- pin apps or notebooks to a stable snapshot,
- and merge or discard changes once you are finished.
📄️ Jupyter Notebooks
Use Bauplan in Jupyter notebooks for interactive data exploration
📄️ marimo
Build reactive notebooks with Bauplan and Marimo
📄️ Streamlit
Create interactive data apps powered by Bauplan