Skip to main content

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.