---
id: ipynb
version: "0.5.1"
license: BSD
license_treatment: permissive
maintenance: dormant
---

# ipynb — Package / Module importer for importing code from Jupyter Notebook files (.ipynb)

License: permissive · Maintenance: dormant · Downloads: 103.9K/mo

## What it is and what it does

ipynb lets you treat Jupyter Notebook files (.ipynb) as importable Python modules. Instead of manually copying code from notebooks or exporting to .py files, you can import them directly using standard Python import syntax. The package provides two modes: full import executes all code in the notebook and exposes top-level definitions, while definitions-only import skips computational work and brings in only function/class definitions, import statements, and ALL_CAPS constants—useful when a notebook contains analysis code you don't want to re-run.

The package has no runtime dependencies and installs cleanly. However, it has been dormant since late 2017 with no recent maintenance, so it may not be tested against current Jupyter or Python versions. It works well for simple notebook-to-module workflows but is not actively developed.

Use it for:

- Reuse functions and classes defined in analysis notebooks across multiple projects without manual copying.
- Import utility notebooks as libraries in production code while keeping analysis and helper code in notebook form.
- Build modular notebook-based projects where some notebooks serve as reusable modules for others via relative imports.
- Extract only the definitions (functions, classes, constants) from a notebook without re-running exploratory or computational cells.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Imports Jupyter Notebook (.ipynb) files as Python modules, executing their code and making top-level definitions available just like regular .py imports.

Yes, if you need to import Jupyter Notebooks as modules and are working with a stable, older codebase. The low install friction and permissive license make it safe to try. However, the dormant maintenance status (no updates since 2017) means you should verify compatibility with your Jupyter and Python versions before relying on it in new projects. For modern notebook-to-module workflows, check whether newer alternatives exist.

## Install

pip install ipynb
uv add ipynb
poetry add ipynb

## Installing ipynb

Before you install: Installation is frictionless with no runtime dependencies. The package is dormant—last release was 2017-10-23 and no commits since 2024-04-15—so expect no active maintenance or bug fixes, though the core functionality remains stable for straightforward use cases.

License in practice: BSD permissive license allows free use, modification, and distribution with minimal restrictions, making it safe to adopt in most projects without licensing concerns.

Quickstart:

pip install ipynb

import ipynb.fs.full.server  # Import all code from server.ipynb
# Or import only definitions:
import ipynb.fs.defs.server  # Import classes, functions, imports, and ALL_CAPS constants

Verify before relying:

- Whether the package works reliably with modern Jupyter versions and recent Python releases (no version constraints specified in metadata).
- Whether relative imports work correctly in all contexts, particularly across different project structures.

## Package facts

- License: BSD (permissive)
- Python support: unspecified
- Install friction: low
- Maintenance: dormant
- Downloads: 103.9K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

import jupyter notebook as module, jupyter notebook importer, ipynb file import, load notebook code as library, notebook module loader, jupyter code reuse, import .ipynb files, jupyter-integration, code-reuse

[View on SkillFed](https://skillfed.io/packages/ipynb) · [View on PyPI](https://pypi.org/project/ipynb/)