trulens-notebook-execution

To execute Jupyter notebooks and capture outputs, you can use jupyter nbconvert to run notebooks end-to-end while preserving state. This approach displays structured progress per section, reducing manual execution overhead for quickstart tutorials and demos.

The best way to run TruLens quickstart tutorials is by executing them programmatically with jupyter nbconvert. This automates notebook execution, preserves state, captures outputs, and provides structured progress visibility for each notebook section.

Yes, you can manage API keys and environment requirements when running notebook-driven demos. The execution process supports environment isolation to safely handle API keys and ensure all environment prerequisites are met before running notebooks.

Yes, when executing notebooks via nbconvert for demos, the process provides live progress visibility. It shows structured progress per notebook section during execution, allowing you to track the notebook execution state in real time.

Yes, you need a Python environment to execute and validate example notebooks. The notebook execution process relies on jupyter nbconvert and a Python environment to run notebooks, capture outputs, and optionally support tracing and dashboards.