# Jupyter Notebook

> Kreirajte čiste, reproducibilne Jupyter bilježnice za dva primarna načina:

- Skill: `thedixitjain/jupyter-notebook-16` (Agent Skill, multi-file: 7 files)
- Install (CLI): `npx skillmds add thedixitjain/jupyter-notebook-16`
- Raw SKILL.md: https://api.skillmd.com/api/skills/thedixitjain/jupyter-notebook-16/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: thedixitjain (https://skillmd.com/u/thedixitjain)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/thedixitjain/jupyter-notebook-16

---

# Vještina za Jupyter Notebook

Kreirajte čiste, reproducibilne Jupyter bilježnice za dva primarna načina:

- Eksperimenti i istraživačka analiza
- Vodiči i nastavne radionice usmjerene na podučavanje

Dajte prednost uključenim predlošcima i pomoćnoj skripti za dosljednu strukturu i manje pogrešaka u JSON-u.

## Kada koristiti
- Kreirajte novu `.ipynb` bilježnicu iz početka.
- Pretvorite grube bilješke ili skripte u strukturiranu bilježnicu.
- Refaktorirajte postojeću bilježnicu kako bi bila reproduktivnija i lakša za pregled.
- Izradite eksperimente ili vodiče koji će ih čitati ili ponovo pokretati druge osobe.

## Stablo odluke
- Ako je zahtjev istraživački, analitički ili vođen hipotezom, odaberite `experiment`.
- Ako je zahtjev instruktivan, korak-po-korak ili namijenjen određenoj publici, odaberite `tutorial`.
- Ako uređujete postojeću bilježnicu, tretirajte je kao refaktor: sačuvajte namjeru i poboljšajte strukturu.

## Put vještine (postavite jednom)

```bash
export CODEX_HOME="${CODEX_HOME:-$HOME/.codex}"
export JUPYTER_NOTEBOOK_CLI="$CODEX_HOME/skills/jupyter-notebook/scripts/new_notebook.py"
```

User-scoped skills install under `$CODEX_HOME/skills` (default: `~/.codex/skills`).

## Radni tijek
1. Lock the intent.
Identify the notebook kind: `experiment` or `tutorial`.
Capture the objective, audience, and what "done" looks like.

2. Scaffold from the template.
Use the helper script to avoid hand-authoring raw notebook JSON.

```bash
uv run --python 3.12 python "$JUPYTER_NOTEBOOK_CLI" \
  --kind experiment \
  --title "Compare prompt variants" \
  --out output/jupyter-notebook/compare-prompt-variants.ipynb
```

```bash
uv run --python 3.12 python "$JUPYTER_NOTEBOOK_CLI" \
  --kind tutorial \
  --title "Intro to embeddings" \
  --out output/jupyter-notebook/intro-to-embeddings.ipynb
```

3. Fill the notebook with small, runnable steps.
Keep each code cell focused on one step.
Add short markdown cells that explain the purpose and expected result.
Avoid large, noisy outputs when a short summary works.

4. Apply the right pattern.
For experiments, follow `references/experiment-patterns.md`.
For tutorials, follow `references/tutorial-patterns.md`.

5. Edit safely when working with existing notebooks.
Preserve the notebook structure; avoid reordering cells unless it improves the top-to-bottom story.
Prefer targeted edits over full rewrites.
If you must edit raw JSON, review `references/notebook-structure.md` first.

6. Validate the result.
Run the notebook top-to-bottom when the environment allows.
If execution is not possible, say so explicitly and call out how to validate locally.
Use the final pass checklist in `references/quality-checklist.md`.

## Predlošci i pomoćna skripta
- Templates live in `assets/experiment-template.ipynb` and `assets/tutorial-template.ipynb`.
- The helper script loads a template, updates the title cell, and writes a notebook.

Script path:
- `$JUPYTER_NOTEBOOK_CLI` (installed default: `$CODEX_HOME/skills/jupyter-notebook/scripts/new_notebook.py`)

## Privremene i izlazne konvencije
- Use `tmp/jupyter-notebook/` for intermediate files; delete when done.
- Write final artifacts under `output/jupyter-notebook/` when working in this repo.
- Use stable, descriptive filenames (for example, `ablation-temperature.ipynb`).

## Ovisnosti (instalirajte samo kad je potrebno)
Prefer `uv` for dependency management.

Optional Python packages for local notebook execution:

```bash
uv pip install jupyterlab ipykernel
```

The bundled scaffold script uses only the Python standard library and does not require extra dependencies.

## Okruženje
No required environment variables.

## Karta referenci
- `references/experiment-patterns.md`: experiment structure and heuristics.
- `references/tutorial-patterns.md`: tutorial structure and teaching flow.
- `references/notebook-structure.md`: notebook JSON shape and safe editing rules.
- `references/quality-checklist.md`: final validation checklist.

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**Source:** [`microsoft/ai-agents-for-beginners`](https://github.com/microsoft/ai-agents-for-beginners) → `translations/hr/.agents/skills/jupyter-notebook/SKILL.md`