THE FILE FIELD GUIDE

.ipynb

Jupyter Notebook

Data & Science

IPYNB is a Jupyter Notebook stored as JSON with code, narrative, outputs and kernel metadata. Separate viewing from executing cells; do not begin by running all cells in an unfamiliar notebook.

Main use: Store code, narrative and outputs in cells
Data type: Text data

All sections, questions and sources

Content reviewed：2026-10-19 · Editor：Kai

Opening steps

Choose your environment or purpose to see its steps.

JupyterLab / Notebook / compatible editor

Preserve the original and inspect a working copy in a compatible application.

Open a copy in JupyterLab or a compatible editor and first inspect code/saved outputs.
Identify kernel language, packages and referenced datasets.
Only execute reviewed code for an established purpose, starting with required cells in a dedicated environment.

Inspect the received file and its requirements

Establish dependencies and settings before proceeding.

Check delivered datasets, paths and environment definitions.
Inspect execution order and when saved outputs were produced.
Review code/outputs for keys and personal data.

Menu labels and support vary by app, OS and version. Preserve the original before making changes.

Troubleshooting by symptom

Kernel absent: ask about the required language/environment.
ModuleNotFoundError: inspect runtime dependencies rather than the file format.
Different results: inspect cell order, input data and randomness.
Large file: saved image/rich outputs may dominate size.

IPYNB → HTML / PDF / script

Export through nbconvert or equivalent, checking that unintended execution is not enabled.
Check required cells, saved outputs, external data and confidential content.

Scripts omit stored cell outputs; PDF/HTML do not include the executable environment.

Saved output does not prove reproducibility

Saved results may not correspond to current code/data. Reproduction requires agreed environment/data versions and execution procedure after code review.

Source for these steps：Jupyter · The Notebook file format / Jupyter · Using nbconvert as a command line tool / Jupyter · Security in the Jupyter Server

Worked example: checks before handoff

Example: agree on CSV version/columns and packages, providing a separate viewing HTML alongside the IPYNB master.

Source for these steps：Jupyter · The Notebook file format / Jupyter · Using nbconvert as a command line tool / Jupyter · Security in the Jupyter Server

Related-format differences

Related-format differences
Format / method	Purpose and preserved information
.ipynb	Store code, narrative and outputs in cells
PY / HTML	PY is Python source and HTML a viewing deliverable, not equivalent notebook/environment storage.
IPYNB → HTML / PDF / script	Scripts omit stored cell outputs; PDF/HTML do not include the executable environment.

Handling and security

Cells can manipulate files and make network requests. Do not run unknown notebooks wholesale; review outputs and keys before sharing.

Questions and answers

Is IPYNB Python-only?

Other kernels support other languages; the suffix does not establish the runtime.

Does trusting it prove the code is safe?

Display trust is distinct from code safety; inspect content and source.

Does clearing outputs package external data?

No; inventory datasets and environment information independently.

Format facts: name, steward and MIME type

Formal name: Jupyter Notebook
Steward / specification: Jupyter
MIME type: Consult the producer or delivery system. The extension alone does not establish a MIME type.

Primary and official sources

Software documentationThe Notebook file format
JSON structure containing cells, outputs and kernel metadata.
Jupyter · Link checked：2026-10-16
Software documentationUsing nbconvert as a command line tool
HTML/PDF/script export and execution options.
Jupyter · Link checked：2026-10-16
Software documentationSecurity in the Jupyter Server
Notebook trust, code execution and server exposure.
Jupyter · Link checked：2026-10-16