notebook-debug

To debug Jupyter notebook runtime errors, inspect the `.ipynb` file for tracebacks and cell execution issues. This process identifies the exact failing cell and extracts the error context needed to resolve the execution failure.

Executed notebook failures through papermill or jupytext often stem from cell execution issues or hidden tracebacks. Inspecting the `.ipynb` file outputs verifies whether all cells executed correctly and in the proper order to pinpoint the error.

Yes, you need `jq` installed to perform quick checks for tracebacks within `.ipynb` files. It enables fast querying of notebook outputs, while the `Read` tool handles detailed inspection of specific cell errors and execution issues.

The best way to verify notebook cell execution is to inspect the `.ipynb` file outputs for tracebacks. This checks that all cells executed correctly and in the proper sequence, highlighting any runtime errors that disrupted the pipeline.

Yes, you can debug marimo notebook execution issues by inspecting the executed notebook files. This approach applies to failed executions from various sources including marimo, extracting tracebacks to pinpoint the exact cell causing the runtime error.

When a data science notebook throws a traceback during execution, inspect the `.ipynb` file outputs to locate the error. Analyzing the traceback identifies the exact failing cell and provides the necessary context to fix the issue.