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Swarmauri notebook-cleanup tool for clearing code-cell outputs and execution counts from Jupyter notebooks.

Project description

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Swarmauri Tool Jupyter Clear Output

Removes outputs and execution counts from Jupyter notebooks using a Swarmauri tool wrapper. Ideal for cleaning notebooks before publishing or committing to version control.

Features

  • Clears output arrays from all code cells and resets execution_count to None.
  • Leaves markdown and raw cells untouched.
  • Works with notebooks already loaded into memory (dict/JSON structure).

Prerequisites

  • Python 3.10 or newer.
  • Dependencies: nbconvert, swarmauri_base, swarmauri_standard (installed automatically).

Installation

# pip
pip install swarmauri_tool_jupyterclearoutput

# poetry
poetry add swarmauri_tool_jupyterclearoutput

# uv (pyproject-based projects)
uv add swarmauri_tool_jupyterclearoutput

Quickstart

import json
from swarmauri_tool_jupyterclearoutput import JupyterClearOutputTool

notebook_data = json.loads(Path("notebooks/example.ipynb").read_text())

cleaner = JupyterClearOutputTool()
clean_notebook = cleaner(notebook_data)

Path("notebooks/example-clean.ipynb").write_text(json.dumps(clean_notebook, indent=2))

Tips

  • Run this tool before committing notebooks to keep diffs small and avoid leaking secrets in output cells.
  • Combine with Swarmauri pipelines that regenerate notebooks (e.g., parameterized runs) to ensure clean artifacts.
  • For large notebooks, consider streaming to disk rather than loading entirely into memory before clearing.

Want to help?

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

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