jupyter-notebook

name

jupyter-notebook

description

Search and edit Jupyter notebooks through safe text-based workflows when the assistant should not handle raw .ipynb JSON directly. Use when you need to inspect, search, change, review, or patch a notebook by either searching it through a ripgrep preprocessor or converting it to a readable text notebook with Jupytext and syncing the changes back into the original .ipynb file while preserving outputs when possible.

Jupyter Notebook Search and Editing via Jupytext

Overview

Use this skill when the task is "search or modify a notebook", but working on raw .ipynb JSON directly is not practical.

This skill covers two notebook-safe operations:

1. Search notebook content through rg with scripts/rg_ipynb_preprocessor.py.
2. Edit notebook content through a temporary Jupytext text representation and sync it back to .ipynb.

Default workflow:

1. Search notebook content safely when you need to locate cells or text inside .ipynb.
2. Convert the current .ipynb notebook into a readable text notebook in a temporary location.
3. Edit the text notebook instead of the .ipynb.
4. Sync the edited text back into the original .ipynb.

This skill is intentionally narrow. It is not about maintaining paired notebooks long term. It is a bridge for notebook search and editing.

Quick Start

Check tool

Before editing a notebook, verify that jupytext is available:

bash scripts/check_jupytext.sh

Export notebook to text

Convert a notebook into a readable Python text notebook in py:percent format. Always pass an explicit output path, and prefer a temporary file under TMPDIR:

tmp_py="${TMPDIR:-/tmp}/notebook.edit.py"
bash scripts/export_text_notebook.sh notebook.ipynb "$tmp_py"

Search notebook content with rg

When searching .ipynb files, do not search the raw notebook JSON directly. Use the ripgrep preprocessor so the search sees cell sources and text outputs, while base64-heavy outputs are omitted:

rg --pre ./scripts/rg_ipynb_preprocessor.py --pre-glob '*.ipynb' 'pattern' .

This is the preferred search path for notebook content because it avoids noisy matches inside serialized output blobs such as image/png. rg --pre executes the preprocessor directly, so the script must be executable.

If you want that behavior to apply to ordinary recursive rg runs without repeating --pre and --pre-glob every time, use a temporary ripgrep config:

tmp_rg="${TMPDIR:-/tmp}/rg-ipynb-pre.rc"
printf '%s\n' \
  '--pre' \
  './scripts/rg_ipynb_preprocessor.py' \
  '--pre-glob' \
  '*.ipynb' > "$tmp_rg"

RIPGREP_CONFIG_PATH="$tmp_rg" rg 'pattern' .
rm -f "$tmp_rg"

With that config in place, rg 'pattern' . will automatically preprocess any .ipynb files encountered during the search, even though the command itself does not target *.ipynb explicitly.

Sync text back to notebook

After editing the text notebook, update the original .ipynb:

bash scripts/update_ipynb_from_text.sh "$tmp_py" notebook.ipynb

If notebook.ipynb already exists, the script copies the existing notebook into a temporary workspace and uses Jupytext's --update --to notebook flow there so that notebook outputs and metadata are preserved when possible.

If the target .ipynb does not exist, the script creates a new notebook with no outputs.

Standard Workflow

When asked to edit a notebook:

1. Run bash scripts/check_jupytext.sh.
2. Create a temporary text path, e.g. tmp_py="${TMPDIR:-/tmp}/$(basename path/to/notebook.ipynb .ipynb).edit.py".
3. Export the target notebook with bash scripts/export_text_notebook.sh path/to/notebook.ipynb "$tmp_py".
4. Read and edit the generated text notebook.
5. Sync changes back with bash scripts/update_ipynb_from_text.sh "$tmp_py" path/to/notebook.ipynb.
6. Remove the temporary text file if it is no longer needed.

When asked to search code that could be in a notebook, or when searching notebook content before editing, use:

rg --pre ./scripts/rg_ipynb_preprocessor.py --pre-glob '*.ipynb' 'pattern' path/to/notebooks

For repeated notebook searches in one shell session, you can also point RIPGREP_CONFIG_PATH at a temporary config containing the same --pre and --pre-glob arguments, then run plain commands such as rg 'pattern' path/to/notebooks.

Format Choice

The default text format is py:percent because it is easy to read and round-trip safely with Jupytext:

# %%
import pandas as pd

# %%
df.head()

The user does not need to manage paired notebooks manually. The .py file is usually a temporary editing artifact and should live in TMPDIR unless the user explicitly wants to keep it.

Important Notes

• Prefer editing the generated text notebook, not the raw JSON inside .ipynb.
• Prefer searching .ipynb through scripts/rg_ipynb_preprocessor.py, not through the raw notebook JSON.
• jupytext --update --to notebook is the safest default when updating an existing notebook because it updates input cells while preserving outputs and metadata.
• jupyter itself is not required for this editing bridge. Only jupytext is required.
• If jupytext is missing, tell the user and provide installation guidance rather than guessing another conversion path.

References

• For the exact command behavior, see references/jupytext-roundtrip.md.