swarmauri_tool_jupyterexecutenotebook 0.9.3.dev5

A tool designed to execute all cells in a Jupyter Notebook using nbconvert’s ExecutePreprocessor, capturing outputs for testing and reporting.

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Swarmauri Tool Jupyter Execute Notebook

Executes all cells of a Jupyter notebook using nbclient and returns the executed NotebookNode with captured outputs.

Features

• Runs notebooks programmatically via the Swarmauri tool interface.
• Accepts optional per-cell timeout (default 30 seconds) and continues on cell errors.
• Returns the executed notebook object so downstream tools can inspect outputs or save it.

Prerequisites

• Python 3.10 or newer.
• Jupyter/nbconvert stack available (nbclient, nbformat, ipykernel, etc.—installed automatically).
• Notebook dependencies must be installed in the environment where the tool runs.

Installation

# pip
pip install swarmauri_tool_jupyterexecutenotebook

# poetry
poetry add swarmauri_tool_jupyterexecutenotebook

# uv (pyproject-based projects)
uv add swarmauri_tool_jupyterexecutenotebook

Quickstart

from swarmauri_tool_jupyterexecutenotebook import JupyterExecuteNotebookTool

executor = JupyterExecuteNotebookTool()
executed_nb = executor(
    notebook_path="notebooks/example.ipynb",
    timeout=120,
)

# Save the executed notebook
import nbformat, json
from pathlib import Path

Path("notebooks/example-executed.ipynb").write_text(
    nbformat.writes(executed_nb),
    encoding="utf-8",
)

Tips

• Increase timeout for notebooks with long-running cells to avoid CellTimeoutError.
• Set allow_errors=True (default in the tool) so execution continues after a failing cell while error traces are still recorded.
• Combine with JupyterClearOutputTool or conversion tools to build end-to-end notebook pipelines.

Want to help?

If you want to contribute to swarmauri-sdk, read up on our guidelines for contributing that will help you get started.